USE CASE · ATEX WORKER SAFETY AIANWENDUNGSFALL · PERSONENERKENNUNG ATEXUSE CASE · ATEX WORKER SAFETY AIUSE CASE · ATEX WORKER SAFETY AIUSE CASE · ATEX WORKER SAFETY AIUSE CASE · ATEX WORKER SAFETY AI

ATEX worker safety AI
for hazard-zone monitoring.
Personenerkennung KI
für ATEX-Zonen und Schutzbereiche.
ATEX worker safety AI
for hazard-zone monitoring.
ATEX worker safety AI
for hazard-zone monitoring.
ATEX worker safety AI
for hazard-zone monitoring.
ATEX worker safety AI
for hazard-zone monitoring.

A LiDAR + camera pair detects when a worker enters a hazardous area — ATEX zone, crane swing radius, conveyor pull-cord zone, automated cell — and feeds slow-down or hard-stop signals into the safety PLC before the worker is at risk. Works in dust, fog and low light. Every event is logged for the safety officer's audit trail. Custom-built for your zone topology and your plant safety logic.

LiDAR und Kamera erkennen, wenn jemand eine Gefahrenzone betritt — ATEX-Zone, Kran-Schwenkbereich, Reißleinen-Zone eines Förderbands, automatisierte Zelle — und speisen Verlangsamung oder Notabschaltung in die Sicherheits-SPS, bevor der Mitarbeiter in Gefahr ist. Arbeitet in Staub, Nebel und schlechtem Licht. Jedes Ereignis wird auditfähig für die Sicherheits-Beauftragten protokolliert. Nach Maß gebaut für Ihre Zonen-Topologie und Ihre Anlagen-Sicherheitslogik.

A LiDAR + camera pair detects when a worker enters a hazardous area — ATEX zone, crane swing radius, conveyor pull-cord zone, automated cell — and feeds slow-down or hard-stop signals into the safety PLC before the worker is at risk. Works in dust, fog and low light. Every event is logged for the safety officer's audit trail. Custom-built for your zone topology and your plant safety logic.

A LiDAR + camera pair detects when a worker enters a hazardous area — ATEX zone, crane swing radius, conveyor pull-cord zone, automated cell — and feeds slow-down or hard-stop signals into the safety PLC before the worker is at risk. Works in dust, fog and low light. Every event is logged for the safety officer's audit trail. Custom-built for your zone topology and your plant safety logic.

A LiDAR + camera pair detects when a worker enters a hazardous area — ATEX zone, crane swing radius, conveyor pull-cord zone, automated cell — and feeds slow-down or hard-stop signals into the safety PLC before the worker is at risk. Works in dust, fog and low light. Every event is logged for the safety officer's audit trail. Custom-built for your zone topology and your plant safety logic.

A LiDAR + camera pair detects when a worker enters a hazardous area — ATEX zone, crane swing radius, conveyor pull-cord zone, automated cell — and feeds slow-down or hard-stop signals into the safety PLC before the worker is at risk. Works in dust, fog and low light. Every event is logged for the safety officer's audit trail. Custom-built for your zone topology and your plant safety logic.

5–25 m typical detection rangetypische Erfassungsreichweitetypical detection rangetypical detection rangetypical detection rangetypical detection range
< 200 ms typical reaction timetypische Reaktionszeittypical reaction timetypical reaction timetypical reaction timetypical reaction time
ATEX-aware sensor housings per zoneSensor-Gehäuse je Zonesensor housings per zonesensor housings per zonesensor housings per zonesensor housings per zone
Auditable event log for the safety officerEreignis-Log für Sicherheits-Beauftragteevent log for the safety officerevent log for the safety officerevent log for the safety officerevent log for the safety officer
USE CASEANWENDUNGSFALLUSE CASEUSE CASEUSE CASEUSE CASE  ·  ATEX worker safety AI · LiDAR + camera fusionPersonenerkennung ATEX · Fusion aus LiDAR und KameraATEX worker safety AI · LiDAR + camera fusionATEX worker safety AI · LiDAR + camera fusionATEX worker safety AI · LiDAR + camera fusionATEX worker safety AI · LiDAR + camera fusion

Person detection in hazard zones, before the worker is at risk. Personen in Gefahrenzonen erkennen, bevor der Mitarbeiter in Gefahr ist. Person detection in hazard zones, before the worker is at risk. Person detection in hazard zones, before the worker is at risk. Person detection in hazard zones, before the worker is at risk. Person detection in hazard zones, before the worker is at risk.

ATEX worker safety AI is a perception pipeline that detects people entering hazardous zones — ATEX areas, crane swing radius, conveyor pull-cord zones, automated-cell perimeters — and triggers PLC slow-down or hard-stop signals before the worker is at risk, with an auditable event log for the safety officer.Personenerkennung KI für ATEX-Zonen ist eine Wahrnehmungs-Pipeline, die Personen beim Betreten von Gefahrenbereichen — ATEX-Zonen, Kran-Schwenkbereich, Reißleinen-Zonen am Förderband, Perimeter automatisierter Zellen — detektiert und Verlangsamungs- oder Notabschalt-Signale in die Sicherheits-SPS speist, bevor der Mitarbeiter in Gefahr ist. Mit auditfähigem Ereignis-Log für die Sicherheits-Beauftragten.ATEX worker safety AI is a perception pipeline that detects people entering hazardous zones — ATEX areas, crane swing radius, conveyor pull-cord zones, automated-cell perimeters — and triggers PLC slow-down or hard-stop signals before the worker is at risk, with an auditable event log for the safety officer.ATEX worker safety AI is a perception pipeline that detects people entering hazardous zones — ATEX areas, crane swing radius, conveyor pull-cord zones, automated-cell perimeters — and triggers PLC slow-down or hard-stop signals before the worker is at risk, with an auditable event log for the safety officer.ATEX worker safety AI is a perception pipeline that detects people entering hazardous zones — ATEX areas, crane swing radius, conveyor pull-cord zones, automated-cell perimeters — and triggers PLC slow-down or hard-stop signals before the worker is at risk, with an auditable event log for the safety officer.ATEX worker safety AI is a perception pipeline that detects people entering hazardous zones — ATEX areas, crane swing radius, conveyor pull-cord zones, automated-cell perimeters — and triggers PLC slow-down or hard-stop signals before the worker is at risk, with an auditable event log for the safety officer.

The pain is structural in every dust- or gas-prone plant: existing ATEX safety relies on light-curtains, RFID badges and procedural lockout-tagout. Light curtains miss anyone who walks around them; RFID badges only protect the worker who actually wore one; lockout-tagout is bypassed under schedule pressure more often than safety departments care to admit. And when an incident does happen — a near-miss, a swing-radius excursion, a pull-cord trip — there is rarely a clean record of who was where, when, and why the protection failed. Dust, smoke and low light defeat camera-only systems exactly when you need them most.Der Schmerz ist strukturell in jeder staub- oder gasführenden Anlage: bestehende ATEX-Sicherheit stützt sich auf Lichtvorhänge, RFID-Marken und Lockout-Tagout-Verfahren. Lichtvorhänge übersehen jeden, der sie umgeht; RFID-Marken schützen nur den Mitarbeiter, der sie tatsächlich getragen hat; Lockout-Tagout wird unter Termindruck häufiger umgangen, als es den Arbeitssicherheits-Abteilungen lieb ist. Und wenn doch etwas passiert — Beinahe-Unfall, Schwenkbereichs-Überschreitung, Reißleinen-Auslösung — fehlt meist die saubere Aufzeichnung, wer wann wo war und warum der Schutz versagt hat. Staub, Rauch und schlechtes Licht setzen reine Kamera-Systeme genau dann außer Kraft, wenn man sie am dringendsten braucht.The pain is structural in every dust- or gas-prone plant: existing ATEX safety relies on light-curtains, RFID badges and procedural lockout-tagout. Light curtains miss anyone who walks around them; RFID badges only protect the worker who actually wore one; lockout-tagout is bypassed under schedule pressure more often than safety departments care to admit. And when an incident does happen — a near-miss, a swing-radius excursion, a pull-cord trip — there is rarely a clean record of who was where, when, and why the protection failed. Dust, smoke and low light defeat camera-only systems exactly when you need them most.The pain is structural in every dust- or gas-prone plant: existing ATEX safety relies on light-curtains, RFID badges and procedural lockout-tagout. Light curtains miss anyone who walks around them; RFID badges only protect the worker who actually wore one; lockout-tagout is bypassed under schedule pressure more often than safety departments care to admit. And when an incident does happen — a near-miss, a swing-radius excursion, a pull-cord trip — there is rarely a clean record of who was where, when, and why the protection failed. Dust, smoke and low light defeat camera-only systems exactly when you need them most.The pain is structural in every dust- or gas-prone plant: existing ATEX safety relies on light-curtains, RFID badges and procedural lockout-tagout. Light curtains miss anyone who walks around them; RFID badges only protect the worker who actually wore one; lockout-tagout is bypassed under schedule pressure more often than safety departments care to admit. And when an incident does happen — a near-miss, a swing-radius excursion, a pull-cord trip — there is rarely a clean record of who was where, when, and why the protection failed. Dust, smoke and low light defeat camera-only systems exactly when you need them most.The pain is structural in every dust- or gas-prone plant: existing ATEX safety relies on light-curtains, RFID badges and procedural lockout-tagout. Light curtains miss anyone who walks around them; RFID badges only protect the worker who actually wore one; lockout-tagout is bypassed under schedule pressure more often than safety departments care to admit. And when an incident does happen — a near-miss, a swing-radius excursion, a pull-cord trip — there is rarely a clean record of who was where, when, and why the protection failed. Dust, smoke and low light defeat camera-only systems exactly when you need them most.

Our approach fuses two sensors per zone. A 3D-LiDAR scans the zone geometry — point clouds penetrate dust and smoke far better than RGB, so the system still sees a person when the camera does not. A high-resolution camera adds confirmation — rules out forklifts, animals and pallets that would otherwise trigger false stops. Per-zone safety distance is configured per area (a crane swing radius needs a larger margin than a robot-cell perimeter), and the redundant detection writes interlock signals into the safety PLC. Every event — detection, slow-down, stop, all-clear — goes into an audit log with timestamp, zone, person count, sensor confidence and evidence frames.Unser Ansatz fusioniert zwei Sensoren je Zone. Ein 3D-LiDAR scannt die Zonen-Geometrie — Punktwolken durchdringen Staub und Rauch deutlich besser als RGB, das System sieht die Person also auch dann, wenn die Kamera versagt. Eine hochauflösende Kamera bestätigt die Detektion — schließt Stapler, Tiere und Paletten aus, die sonst Fehlauslösungen wären. Der Sicherheitsabstand wird pro Schutzzone konfiguriert (ein Kran-Schwenkbereich braucht einen größeren Abstand als ein Roboter-Zell-Perimeter), und die redundante Detektion schreibt Verriegelungs-Signale in die Sicherheits-SPS. Jedes Ereignis — Detektion, Verlangsamung, Stopp, Freigabe — geht ins Audit-Log mit Zeitstempel, Zone, Personenanzahl, Sensor-Konfidenz und Beweis-Frames.Our approach fuses two sensors per zone. A 3D-LiDAR scans the zone geometry — point clouds penetrate dust and smoke far better than RGB, so the system still sees a person when the camera does not. A high-resolution camera adds confirmation — rules out forklifts, animals and pallets that would otherwise trigger false stops. Per-zone safety distance is configured per area (a crane swing radius needs a larger margin than a robot-cell perimeter), and the redundant detection writes interlock signals into the safety PLC. Every event — detection, slow-down, stop, all-clear — goes into an audit log with timestamp, zone, person count, sensor confidence and evidence frames.Our approach fuses two sensors per zone. A 3D-LiDAR scans the zone geometry — point clouds penetrate dust and smoke far better than RGB, so the system still sees a person when the camera does not. A high-resolution camera adds confirmation — rules out forklifts, animals and pallets that would otherwise trigger false stops. Per-zone safety distance is configured per area (a crane swing radius needs a larger margin than a robot-cell perimeter), and the redundant detection writes interlock signals into the safety PLC. Every event — detection, slow-down, stop, all-clear — goes into an audit log with timestamp, zone, person count, sensor confidence and evidence frames.Our approach fuses two sensors per zone. A 3D-LiDAR scans the zone geometry — point clouds penetrate dust and smoke far better than RGB, so the system still sees a person when the camera does not. A high-resolution camera adds confirmation — rules out forklifts, animals and pallets that would otherwise trigger false stops. Per-zone safety distance is configured per area (a crane swing radius needs a larger margin than a robot-cell perimeter), and the redundant detection writes interlock signals into the safety PLC. Every event — detection, slow-down, stop, all-clear — goes into an audit log with timestamp, zone, person count, sensor confidence and evidence frames.Our approach fuses two sensors per zone. A 3D-LiDAR scans the zone geometry — point clouds penetrate dust and smoke far better than RGB, so the system still sees a person when the camera does not. A high-resolution camera adds confirmation — rules out forklifts, animals and pallets that would otherwise trigger false stops. Per-zone safety distance is configured per area (a crane swing radius needs a larger margin than a robot-cell perimeter), and the redundant detection writes interlock signals into the safety PLC. Every event — detection, slow-down, stop, all-clear — goes into an audit log with timestamp, zone, person count, sensor confidence and evidence frames.

This is not an off-the-shelf safety appliance. ATEX zones, crane envelopes and plant safety logic differ per site. We treat every engagement as a discovery + fixed-scope build, descending from our hub service Industrial Perception AI. Typically four to twelve weeks from contract to live tool, with the code and the model handed over to you at the end.Das ist kein Sicherheits-Gerät von der Stange. ATEX-Zonen, Kran-Hüllen und Anlagen-Sicherheitslogik unterscheiden sich pro Standort. Wir behandeln jedes Projekt als Discovery + Festscope-Build, abgeleitet aus unserem Hub-Service Industrielle Objekterkennung. Typisch vier bis zwölf Wochen vom Vertrag bis zum produktiven Tool — Code und Modell gehören Ihnen.This is not an off-the-shelf safety appliance. ATEX zones, crane envelopes and plant safety logic differ per site. We treat every engagement as a discovery + fixed-scope build, descending from our hub service Industrial Perception AI. Typically four to twelve weeks from contract to live tool, with the code and the model handed over to you at the end.This is not an off-the-shelf safety appliance. ATEX zones, crane envelopes and plant safety logic differ per site. We treat every engagement as a discovery + fixed-scope build, descending from our hub service Industrial Perception AI. Typically four to twelve weeks from contract to live tool, with the code and the model handed over to you at the end.This is not an off-the-shelf safety appliance. ATEX zones, crane envelopes and plant safety logic differ per site. We treat every engagement as a discovery + fixed-scope build, descending from our hub service Industrial Perception AI. Typically four to twelve weeks from contract to live tool, with the code and the model handed over to you at the end.This is not an off-the-shelf safety appliance. ATEX zones, crane envelopes and plant safety logic differ per site. We treat every engagement as a discovery + fixed-scope build, descending from our hub service Industrial Perception AI. Typically four to twelve weeks from contract to live tool, with the code and the model handed over to you at the end.

„A near-miss that nobody recorded is a near-miss that will happen again." „Ein Beinahe-Unfall, den niemand protokolliert hat, ist ein Beinahe-Unfall, der wiederkommt." „A near-miss that nobody recorded is a near-miss that will happen again." „A near-miss that nobody recorded is a near-miss that will happen again." „A near-miss that nobody recorded is a near-miss that will happen again." „A near-miss that nobody recorded is a near-miss that will happen again."

Built by the same team that delivers our LiDAR wagon-detection pipeline — six lid centroids, sub-5 cm error, two-second response. Gebaut von dem Team, das auch unsere LiDAR-Waggon-Erkennung liefert — sechs Deckel-Mittelpunkte, Fehler unter 5 cm, Antwort in zwei Sekunden. Built by the same team that delivers our LiDAR wagon-detection pipeline — six lid centroids, sub-5 cm error, two-second response. Built by the same team that delivers our LiDAR wagon-detection pipeline — six lid centroids, sub-5 cm error, two-second response. Built by the same team that delivers our LiDAR wagon-detection pipeline — six lid centroids, sub-5 cm error, two-second response. Built by the same team that delivers our LiDAR wagon-detection pipeline — six lid centroids, sub-5 cm error, two-second response.

Three stagesDrei StufenThree stagesThree stagesThree stagesThree stages

From sensor to safety PLC — three stages of the pipeline. Vom Sensor zur Sicherheits-SPS — drei Stufen der Pipeline. From sensor to safety PLC — three stages of the pipeline. From sensor to safety PLC — three stages of the pipeline. From sensor to safety PLC — three stages of the pipeline. From sensor to safety PLC — three stages of the pipeline.

1 · Sensor coverage of the zone1 · Sensor-Abdeckung der Zone1 · Sensor coverage of the zone1 · Sensor coverage of the zone1 · Sensor coverage of the zone1 · Sensor coverage of the zone

One or more LiDAR + camera pairs cover the hazardous zone with redundant overlap, so no single sensor failure leaves a blind spot. ATEX-aware sensor housings where the zone classification requires it (dust zone 22, gas zone 2, fertiliser silos, refinery process areas). Dust-tolerant optics, runs in fog, smoke and night light — the geometry channel keeps working when the visual channel struggles. Ein oder mehrere LiDAR-Kamera-Paare decken die Gefahrenzone mit redundanter Überlappung ab, damit kein einzelner Sensor-Ausfall einen toten Winkel hinterlässt. ATEX-taugliche Sensor-Gehäuse, wo die Zonen-Einstufung es verlangt (Staubzone 22, Gaszone 2, Düngemittel-Silos, Prozessbereiche in Raffinerien). Staubtolerante Optik, läuft in Nebel, Rauch und Nachtlicht — der Geometrie-Kanal arbeitet weiter, wenn der visuelle Kanal schwächelt. One or more LiDAR + camera pairs cover the hazardous zone with redundant overlap, so no single sensor failure leaves a blind spot. ATEX-aware sensor housings where the zone classification requires it (dust zone 22, gas zone 2, fertiliser silos, refinery process areas). Dust-tolerant optics, runs in fog, smoke and night light — the geometry channel keeps working when the visual channel struggles. One or more LiDAR + camera pairs cover the hazardous zone with redundant overlap, so no single sensor failure leaves a blind spot. ATEX-aware sensor housings where the zone classification requires it (dust zone 22, gas zone 2, fertiliser silos, refinery process areas). Dust-tolerant optics, runs in fog, smoke and night light — the geometry channel keeps working when the visual channel struggles. One or more LiDAR + camera pairs cover the hazardous zone with redundant overlap, so no single sensor failure leaves a blind spot. ATEX-aware sensor housings where the zone classification requires it (dust zone 22, gas zone 2, fertiliser silos, refinery process areas). Dust-tolerant optics, runs in fog, smoke and night light — the geometry channel keeps working when the visual channel struggles. One or more LiDAR + camera pairs cover the hazardous zone with redundant overlap, so no single sensor failure leaves a blind spot. ATEX-aware sensor housings where the zone classification requires it (dust zone 22, gas zone 2, fertiliser silos, refinery process areas). Dust-tolerant optics, runs in fog, smoke and night light — the geometry channel keeps working when the visual channel struggles.

2 · Person detection + confirmation2 · Personen-Detektion + Bestätigung2 · Person detection + confirmation2 · Person detection + confirmation2 · Person detection + confirmation2 · Person detection + confirmation

LiDAR clusters persons by geometry — height, gait, motion signature — so the system separates a worker from a forklift or a pile of pallets. The camera confirms the detection visually, ruling out animals, vegetation and yard equipment that would otherwise trigger false stops. Per-zone safety distance is configured: crane envelopes need larger margins than a robot-cell perimeter. Der LiDAR clustert Personen über die Geometrie — Höhe, Gangbild, Bewegungs-Signatur — und trennt so den Mitarbeiter von einem Stapler oder einem Paletten-Stapel. Die Kamera bestätigt die Detektion visuell und schließt Tiere, Pflanzen und Hofgerät aus, die sonst Fehlauslösungen wären. Der Sicherheitsabstand wird pro Schutzzone konfiguriert: Kran-Hüllen brauchen größere Margen als ein Roboter-Zell-Perimeter. LiDAR clusters persons by geometry — height, gait, motion signature — so the system separates a worker from a forklift or a pile of pallets. The camera confirms the detection visually, ruling out animals, vegetation and yard equipment that would otherwise trigger false stops. Per-zone safety distance is configured: crane envelopes need larger margins than a robot-cell perimeter. LiDAR clusters persons by geometry — height, gait, motion signature — so the system separates a worker from a forklift or a pile of pallets. The camera confirms the detection visually, ruling out animals, vegetation and yard equipment that would otherwise trigger false stops. Per-zone safety distance is configured: crane envelopes need larger margins than a robot-cell perimeter. LiDAR clusters persons by geometry — height, gait, motion signature — so the system separates a worker from a forklift or a pile of pallets. The camera confirms the detection visually, ruling out animals, vegetation and yard equipment that would otherwise trigger false stops. Per-zone safety distance is configured: crane envelopes need larger margins than a robot-cell perimeter. LiDAR clusters persons by geometry — height, gait, motion signature — so the system separates a worker from a forklift or a pile of pallets. The camera confirms the detection visually, ruling out animals, vegetation and yard equipment that would otherwise trigger false stops. Per-zone safety distance is configured: crane envelopes need larger margins than a robot-cell perimeter.

3 · PLC interlock + audit log3 · SPS-Verriegelung + Audit-Log3 · PLC interlock + audit log3 · PLC interlock + audit log3 · PLC interlock + audit log3 · PLC interlock + audit log

Confirmed detections feed into the plant safety PLC as slow-down or hard-stop signals over the existing safety bus. Every event — detection, slow-down, stop, all-clear — writes into the historian or safety database with timestamp, zone, person count, sensor confidence and evidence frames. The safety officer gets an auditable trail without manual paperwork. Bestätigte Detektionen speisen die Sicherheits-SPS als Verlangsamungs- oder Notabschalt-Signale über den bestehenden Sicherheits-Bus. Jedes Ereignis — Detektion, Verlangsamung, Stopp, Freigabe — schreibt in den Historian oder die Sicherheits-Datenbank mit Zeitstempel, Zone, Personenanzahl, Sensor-Konfidenz und Beweis-Frames. Die Sicherheits-Beauftragten bekommen einen auditfähigen Trail ohne Papierkram. Confirmed detections feed into the plant safety PLC as slow-down or hard-stop signals over the existing safety bus. Every event — detection, slow-down, stop, all-clear — writes into the historian or safety database with timestamp, zone, person count, sensor confidence and evidence frames. The safety officer gets an auditable trail without manual paperwork. Confirmed detections feed into the plant safety PLC as slow-down or hard-stop signals over the existing safety bus. Every event — detection, slow-down, stop, all-clear — writes into the historian or safety database with timestamp, zone, person count, sensor confidence and evidence frames. The safety officer gets an auditable trail without manual paperwork. Confirmed detections feed into the plant safety PLC as slow-down or hard-stop signals over the existing safety bus. Every event — detection, slow-down, stop, all-clear — writes into the historian or safety database with timestamp, zone, person count, sensor confidence and evidence frames. The safety officer gets an auditable trail without manual paperwork. Confirmed detections feed into the plant safety PLC as slow-down or hard-stop signals over the existing safety bus. Every event — detection, slow-down, stop, all-clear — writes into the historian or safety database with timestamp, zone, person count, sensor confidence and evidence frames. The safety officer gets an auditable trail without manual paperwork.

Pipeline architecture · #how-it-worksPipeline-Architektur · #how-it-worksPipeline architecture · #how-it-worksPipeline architecture · #how-it-worksPipeline architecture · #how-it-worksPipeline architecture · #how-it-works

How the pipeline works — concretely. Wie die Pipeline arbeitet — konkret. How the pipeline works — concretely. How the pipeline works — concretely. How the pipeline works — concretely. How the pipeline works — concretely.

We keep the architecture boring on purpose. Three loosely coupled stages, each one independently testable, each one swappable when the sensor stack changes. Built on the same stack we use across all our perception work: PCL, Open3D, OpenCV, PyTorch. Wir halten die Architektur absichtlich langweilig. Drei lose gekoppelte Stufen, jede einzeln testbar, jede einzeln tauschbar, wenn sich der Sensor-Stack ändert. Gebaut auf demselben Stack, den wir für unsere gesamte Wahrnehmungs-Arbeit nutzen: PCL, Open3D, OpenCV, PyTorch. We keep the architecture boring on purpose. Three loosely coupled stages, each one independently testable, each one swappable when the sensor stack changes. Built on the same stack we use across all our perception work: PCL, Open3D, OpenCV, PyTorch. We keep the architecture boring on purpose. Three loosely coupled stages, each one independently testable, each one swappable when the sensor stack changes. Built on the same stack we use across all our perception work: PCL, Open3D, OpenCV, PyTorch. We keep the architecture boring on purpose. Three loosely coupled stages, each one independently testable, each one swappable when the sensor stack changes. Built on the same stack we use across all our perception work: PCL, Open3D, OpenCV, PyTorch. We keep the architecture boring on purpose. Three loosely coupled stages, each one independently testable, each one swappable when the sensor stack changes. Built on the same stack we use across all our perception work: PCL, Open3D, OpenCV, PyTorch.

01

Multi-sensor capture in dust + smokeMulti-Sensor-Aufnahme in Staub und RauchMulti-sensor capture in dust + smokeMulti-sensor capture in dust + smokeMulti-sensor capture in dust + smokeMulti-sensor capture in dust + smoke

Each LiDAR delivers a 3D point cloud of the zone — typically several hundred thousand points per scan, multiple times per second. Cameras add synchronised colour frames, lens-calibrated and time-stamped. Raw data writes to local storage with a per-event UUID for audit trail and re-labelling. The LiDAR channel is the resilience layer: it keeps reporting geometry when dust, fog or low light blind the camera. Jeder LiDAR liefert eine 3D-Punktwolke der Zone — typisch mehrere hunderttausend Punkte pro Scan, mehrmals pro Sekunde. Kameras ergänzen synchronisierte Farb-Frames, objektiv-kalibriert und zeit-gestempelt. Rohdaten schreiben auf lokalen Speicher mit Ereignis-UUID für Audit-Trail und Re-Labelling. Der LiDAR-Kanal ist die Resilienz-Schicht: er meldet weiter Geometrie, wenn Staub, Nebel oder schlechtes Licht die Kamera blind machen. Each LiDAR delivers a 3D point cloud of the zone — typically several hundred thousand points per scan, multiple times per second. Cameras add synchronised colour frames, lens-calibrated and time-stamped. Raw data writes to local storage with a per-event UUID for audit trail and re-labelling. The LiDAR channel is the resilience layer: it keeps reporting geometry when dust, fog or low light blind the camera. Each LiDAR delivers a 3D point cloud of the zone — typically several hundred thousand points per scan, multiple times per second. Cameras add synchronised colour frames, lens-calibrated and time-stamped. Raw data writes to local storage with a per-event UUID for audit trail and re-labelling. The LiDAR channel is the resilience layer: it keeps reporting geometry when dust, fog or low light blind the camera. Each LiDAR delivers a 3D point cloud of the zone — typically several hundred thousand points per scan, multiple times per second. Cameras add synchronised colour frames, lens-calibrated and time-stamped. Raw data writes to local storage with a per-event UUID for audit trail and re-labelling. The LiDAR channel is the resilience layer: it keeps reporting geometry when dust, fog or low light blind the camera. Each LiDAR delivers a 3D point cloud of the zone — typically several hundred thousand points per scan, multiple times per second. Cameras add synchronised colour frames, lens-calibrated and time-stamped. Raw data writes to local storage with a per-event UUID for audit trail and re-labelling. The LiDAR channel is the resilience layer: it keeps reporting geometry when dust, fog or low light blind the camera.

02

Person classification + safety-distance calculationPersonen-Klassifikation + SicherheitsabstandPerson classification + safety-distance calculationPerson classification + safety-distance calculationPerson classification + safety-distance calculationPerson classification + safety-distance calculation

The point cloud goes through ground removal, voxel down-sampling and a person classifier trained on real plant data — workers in PPE, helmets, high-vis vests, not the office benchmark. The camera image goes through a second classifier on the same target. Both heads fuse into a confirmed person track with a measured distance to the configured zone boundary. False-positive rate is tuned per zone; the safety distance is configurable per area. Die Punktwolke läuft durch Boden-Entfernung, Voxel-Downsampling und einen Personen-Klassifikator, trainiert auf echten Anlagendaten — Mitarbeiter in PSA, Helm und Warnweste, nicht der Büro-Benchmark. Das Kamerabild läuft durch einen zweiten Klassifikator auf dasselbe Ziel. Beide Köpfe fusionieren zu einer bestätigten Personen-Spur mit gemessenem Abstand zur konfigurierten Zonen-Grenze. Die Fehlauslösungs-Rate wird pro Zone abgestimmt; der Sicherheitsabstand ist pro Bereich konfigurierbar. The point cloud goes through ground removal, voxel down-sampling and a person classifier trained on real plant data — workers in PPE, helmets, high-vis vests, not the office benchmark. The camera image goes through a second classifier on the same target. Both heads fuse into a confirmed person track with a measured distance to the configured zone boundary. False-positive rate is tuned per zone; the safety distance is configurable per area. The point cloud goes through ground removal, voxel down-sampling and a person classifier trained on real plant data — workers in PPE, helmets, high-vis vests, not the office benchmark. The camera image goes through a second classifier on the same target. Both heads fuse into a confirmed person track with a measured distance to the configured zone boundary. False-positive rate is tuned per zone; the safety distance is configurable per area. The point cloud goes through ground removal, voxel down-sampling and a person classifier trained on real plant data — workers in PPE, helmets, high-vis vests, not the office benchmark. The camera image goes through a second classifier on the same target. Both heads fuse into a confirmed person track with a measured distance to the configured zone boundary. False-positive rate is tuned per zone; the safety distance is configurable per area. The point cloud goes through ground removal, voxel down-sampling and a person classifier trained on real plant data — workers in PPE, helmets, high-vis vests, not the office benchmark. The camera image goes through a second classifier on the same target. Both heads fuse into a confirmed person track with a measured distance to the configured zone boundary. False-positive rate is tuned per zone; the safety distance is configurable per area.

03

PLC interlock + event-log write-backSPS-Verriegelung + Ereignis-Log-RückschreibungPLC interlock + event-log write-backPLC interlock + event-log write-backPLC interlock + event-log write-backPLC interlock + event-log write-back

Confirmed track crossing a zone boundary triggers a slow-down or hard-stop signal into the safety PLC over the existing safety bus — Profisafe, CIP Safety, or hard-wired safety outputs per project. Simultaneously the event writes into the historian or safety database: timestamp, zone, person count, confidence, evidence frames. The control-room operator sees the live overlay on the HUD; the safety officer queries the database for the audit trail. Eine bestätigte Spur, die eine Zonen-Grenze überschreitet, löst ein Verlangsamungs- oder Notabschalt-Signal in die Sicherheits-SPS aus — über den bestehenden Sicherheits-Bus, Profisafe, CIP Safety oder fest verdrahtete Sicherheits-Ausgänge je Projekt. Parallel schreibt das Ereignis in den Historian oder die Sicherheits-Datenbank: Zeitstempel, Zone, Personenanzahl, Konfidenz, Beweis-Frames. Der Leitstand-Operator sieht das Live-Overlay im HUD; die Sicherheits-Beauftragten fragen die Datenbank für den Audit-Trail ab. Confirmed track crossing a zone boundary triggers a slow-down or hard-stop signal into the safety PLC over the existing safety bus — Profisafe, CIP Safety, or hard-wired safety outputs per project. Simultaneously the event writes into the historian or safety database: timestamp, zone, person count, confidence, evidence frames. The control-room operator sees the live overlay on the HUD; the safety officer queries the database for the audit trail. Confirmed track crossing a zone boundary triggers a slow-down or hard-stop signal into the safety PLC over the existing safety bus — Profisafe, CIP Safety, or hard-wired safety outputs per project. Simultaneously the event writes into the historian or safety database: timestamp, zone, person count, confidence, evidence frames. The control-room operator sees the live overlay on the HUD; the safety officer queries the database for the audit trail. Confirmed track crossing a zone boundary triggers a slow-down or hard-stop signal into the safety PLC over the existing safety bus — Profisafe, CIP Safety, or hard-wired safety outputs per project. Simultaneously the event writes into the historian or safety database: timestamp, zone, person count, confidence, evidence frames. The control-room operator sees the live overlay on the HUD; the safety officer queries the database for the audit trail. Confirmed track crossing a zone boundary triggers a slow-down or hard-stop signal into the safety PLC over the existing safety bus — Profisafe, CIP Safety, or hard-wired safety outputs per project. Simultaneously the event writes into the historian or safety database: timestamp, zone, person count, confidence, evidence frames. The control-room operator sees the live overlay on the HUD; the safety officer queries the database for the audit trail.

All three stages run on an industrial PC at the zone cabinet. No cloud dependency, no external API, no licence dial-home. The code is yours at handover. Alle drei Stufen laufen auf einem Industrie-PC im Zonen-Schaltschrank. Keine Cloud-Abhängigkeit, keine externe API, kein Lizenz-Heimruf. Der Code gehört Ihnen bei der Übergabe. All three stages run on an industrial PC at the zone cabinet. No cloud dependency, no external API, no licence dial-home. The code is yours at handover. All three stages run on an industrial PC at the zone cabinet. No cloud dependency, no external API, no licence dial-home. The code is yours at handover. All three stages run on an industrial PC at the zone cabinet. No cloud dependency, no external API, no licence dial-home. The code is yours at handover. All three stages run on an industrial PC at the zone cabinet. No cloud dependency, no external API, no licence dial-home. The code is yours at handover.

What you getWas Sie bekommenWhat you getWhat you getWhat you getWhat you get

Three deliverables — from the same pipeline. Drei Liefer-Ergebnisse — aus derselben Pipeline. Three deliverables — from the same pipeline. Three deliverables — from the same pipeline. Three deliverables — from the same pipeline. Three deliverables — from the same pipeline.

Real-time safety interlockEchtzeit-Sicherheits-VerriegelungReal-time safety interlockReal-time safety interlockReal-time safety interlockReal-time safety interlock

Slow-down and hard-stop signals into the plant safety PLC, over the safety bus or hard-wired safety outputs. The safety logic stays under your existing functional-safety regime — we feed the inputs; your safety PLC owns the decision and the certification scope. Verlangsamungs- und Notabschalt-Signale in die Sicherheits-SPS, über den Sicherheits-Bus oder fest verdrahtete Sicherheits-Ausgänge. Die Sicherheits-Logik bleibt in Ihrem bestehenden funktionalen Sicherheits-Regime — wir speisen die Eingänge; Ihre Sicherheits-SPS besitzt die Entscheidung und den Zertifizierungs-Scope. Slow-down and hard-stop signals into the plant safety PLC, over the safety bus or hard-wired safety outputs. The safety logic stays under your existing functional-safety regime — we feed the inputs; your safety PLC owns the decision and the certification scope. Slow-down and hard-stop signals into the plant safety PLC, over the safety bus or hard-wired safety outputs. The safety logic stays under your existing functional-safety regime — we feed the inputs; your safety PLC owns the decision and the certification scope. Slow-down and hard-stop signals into the plant safety PLC, over the safety bus or hard-wired safety outputs. The safety logic stays under your existing functional-safety regime — we feed the inputs; your safety PLC owns the decision and the certification scope. Slow-down and hard-stop signals into the plant safety PLC, over the safety bus or hard-wired safety outputs. The safety logic stays under your existing functional-safety regime — we feed the inputs; your safety PLC owns the decision and the certification scope.

Audit-grade event logAuditfähiges Ereignis-LogAudit-grade event logAudit-grade event logAudit-grade event logAudit-grade event log

Every detection logged with timestamp, person count, zone, sensor confidence and evidence frames. Feeds your safety database, your historian, your incident-investigation workflow — the same temporal model we use on stockpile monitoring, applied to safety events instead of material piles. Jede Detektion protokolliert mit Zeitstempel, Personenanzahl, Zone, Sensor-Konfidenz und Beweis-Frames. Speist Ihre Sicherheits-Datenbank, Ihren Historian, Ihren Vorfalls-Untersuchungs-Workflow — dasselbe zeitliche Modell, das wir auf Halden-Monitoring einsetzen, übertragen auf Sicherheits-Ereignisse statt Materialhalden. Every detection logged with timestamp, person count, zone, sensor confidence and evidence frames. Feeds your safety database, your historian, your incident-investigation workflow — the same temporal model we use on stockpile monitoring, applied to safety events instead of material piles. Every detection logged with timestamp, person count, zone, sensor confidence and evidence frames. Feeds your safety database, your historian, your incident-investigation workflow — the same temporal model we use on stockpile monitoring, applied to safety events instead of material piles. Every detection logged with timestamp, person count, zone, sensor confidence and evidence frames. Feeds your safety database, your historian, your incident-investigation workflow — the same temporal model we use on stockpile monitoring, applied to safety events instead of material piles. Every detection logged with timestamp, person count, zone, sensor confidence and evidence frames. Feeds your safety database, your historian, your incident-investigation workflow — the same temporal model we use on stockpile monitoring, applied to safety events instead of material piles.

Operator HUDOperator-HUDOperator HUDOperator HUDOperator HUDOperator HUD

A live overlay so the control-room operator sees who is where in real time — zone outlines, active detections, current safety state per area. Same dashboard surfaces the recent event history for shift handover and supervisor reviews. Ein Live-Overlay, damit der Leitstand-Operator in Echtzeit sieht, wer wo ist — Zonen-Umrisse, aktive Detektionen, aktueller Sicherheits-Status je Bereich. Dasselbe Dashboard zeigt die jüngste Ereignis-Historie für Schichtübergabe und Vorgesetzten-Reviews. A live overlay so the control-room operator sees who is where in real time — zone outlines, active detections, current safety state per area. Same dashboard surfaces the recent event history for shift handover and supervisor reviews. A live overlay so the control-room operator sees who is where in real time — zone outlines, active detections, current safety state per area. Same dashboard surfaces the recent event history for shift handover and supervisor reviews. A live overlay so the control-room operator sees who is where in real time — zone outlines, active detections, current safety state per area. Same dashboard surfaces the recent event history for shift handover and supervisor reviews. A live overlay so the control-room operator sees who is where in real time — zone outlines, active detections, current safety state per area. Same dashboard surfaces the recent event history for shift handover and supervisor reviews.

Why customWarum CustomWhy customWhy customWhy customWhy custom

Why a custom build — not an off-the-shelf product. Warum nach Maß — und nicht von der Stange. Why a custom build — not an off-the-shelf product. Why a custom build — not an off-the-shelf product. Why a custom build — not an off-the-shelf product. Why a custom build — not an off-the-shelf product.

Every plant has its own ATEX zone topology, its own crane envelopes, its own safety PLC and its own lockout-tagout culture. A generic safety appliance solves the generic case; your case is not the generic case. Jede Anlage hat eigene ATEX-Zonen-Topologie, eigene Kran-Hüllen, eigene Sicherheits-SPS und eigene Lockout-Tagout-Kultur. Ein generisches Sicherheits-Gerät löst den generischen Fall; Ihr Fall ist nicht der generische Fall. Every plant has its own ATEX zone topology, its own crane envelopes, its own safety PLC and its own lockout-tagout culture. A generic safety appliance solves the generic case; your case is not the generic case. Every plant has its own ATEX zone topology, its own crane envelopes, its own safety PLC and its own lockout-tagout culture. A generic safety appliance solves the generic case; your case is not the generic case. Every plant has its own ATEX zone topology, its own crane envelopes, its own safety PLC and its own lockout-tagout culture. A generic safety appliance solves the generic case; your case is not the generic case. Every plant has its own ATEX zone topology, its own crane envelopes, its own safety PLC and its own lockout-tagout culture. A generic safety appliance solves the generic case; your case is not the generic case.

Zone-specific safety distance configurationZonen-spezifische Sicherheitsabstand-KonfigurationZone-specific safety distance configurationZone-specific safety distance configurationZone-specific safety distance configurationZone-specific safety distance configuration

A crane swing radius needs a larger margin than a robot-cell perimeter; a fertiliser silo with explosive-dust risk needs a different reaction profile than a wood-pellet conveyor. We configure the safety distance, the reaction curve and the false-positive tuning per zone — not one global threshold for everything. Ein Kran-Schwenkbereich braucht einen größeren Abstand als ein Roboter-Zell-Perimeter; ein Düngemittel-Silo mit Staubexplosions-Risiko braucht eine andere Reaktionskurve als ein Holzpellet-Förderband. Wir konfigurieren Sicherheitsabstand, Reaktionskurve und Fehlauslösungs-Abstimmung pro Schutzzone — nicht eine globale Schwelle für alles. A crane swing radius needs a larger margin than a robot-cell perimeter; a fertiliser silo with explosive-dust risk needs a different reaction profile than a wood-pellet conveyor. We configure the safety distance, the reaction curve and the false-positive tuning per zone — not one global threshold for everything. A crane swing radius needs a larger margin than a robot-cell perimeter; a fertiliser silo with explosive-dust risk needs a different reaction profile than a wood-pellet conveyor. We configure the safety distance, the reaction curve and the false-positive tuning per zone — not one global threshold for everything. A crane swing radius needs a larger margin than a robot-cell perimeter; a fertiliser silo with explosive-dust risk needs a different reaction profile than a wood-pellet conveyor. We configure the safety distance, the reaction curve and the false-positive tuning per zone — not one global threshold for everything. A crane swing radius needs a larger margin than a robot-cell perimeter; a fertiliser silo with explosive-dust risk needs a different reaction profile than a wood-pellet conveyor. We configure the safety distance, the reaction curve and the false-positive tuning per zone — not one global threshold for everything.

Sensor + housing selection for the actual environmentSensor- und Gehäuse-Auswahl für die echte UmgebungSensor + housing selection for the actual environmentSensor + housing selection for the actual environmentSensor + housing selection for the actual environmentSensor + housing selection for the actual environment

ATEX-aware sensor housings where the zone classification requires it — dust zone 22 in grain and pellet handling, gas zone 2 in refinery and chemical, dust-and-gas hybrids in fertiliser, IP66+ wash-down in foundry. We pick the housing per zone, not one catalogue option for the whole plant. ATEX-taugliche Sensor-Gehäuse, wo die Zonen-Einstufung es verlangt — Staubzone 22 in Getreide- und Pellet-Handling, Gaszone 2 in Raffinerie und Chemie, Staub-Gas-Mischformen in Düngemittel-Anlagen, IP66+ Wash-Down in der Gießerei. Wir wählen das Gehäuse pro Zone, nicht eine Katalog-Option für die ganze Anlage. ATEX-aware sensor housings where the zone classification requires it — dust zone 22 in grain and pellet handling, gas zone 2 in refinery and chemical, dust-and-gas hybrids in fertiliser, IP66+ wash-down in foundry. We pick the housing per zone, not one catalogue option for the whole plant. ATEX-aware sensor housings where the zone classification requires it — dust zone 22 in grain and pellet handling, gas zone 2 in refinery and chemical, dust-and-gas hybrids in fertiliser, IP66+ wash-down in foundry. We pick the housing per zone, not one catalogue option for the whole plant. ATEX-aware sensor housings where the zone classification requires it — dust zone 22 in grain and pellet handling, gas zone 2 in refinery and chemical, dust-and-gas hybrids in fertiliser, IP66+ wash-down in foundry. We pick the housing per zone, not one catalogue option for the whole plant. ATEX-aware sensor housings where the zone classification requires it — dust zone 22 in grain and pellet handling, gas zone 2 in refinery and chemical, dust-and-gas hybrids in fertiliser, IP66+ wash-down in foundry. We pick the housing per zone, not one catalogue option for the whole plant.

Integration with existing safety PLC + lockout-tagoutAnbindung an bestehende Sicherheits-SPS + Lockout-TagoutIntegration with existing safety PLC + lockout-tagoutIntegration with existing safety PLC + lockout-tagoutIntegration with existing safety PLC + lockout-tagoutIntegration with existing safety PLC + lockout-tagout

Most plants already have a safety PLC, light curtains, RFID badges and a lockout-tagout procedure. We feed our detections into what's already there as additional inputs — we do not replace your functional-safety regime. Profisafe, CIP Safety, hard-wired safety outputs and OPC UA for the non-safety audit channel all supported. Die meisten Anlagen haben bereits eine Sicherheits-SPS, Lichtvorhänge, RFID-Marken und ein Lockout-Tagout-Verfahren. Wir speisen unsere Detektionen als zusätzliche Eingänge in das, was schon da ist — wir ersetzen Ihr funktionales Sicherheits-Regime nicht. Profisafe, CIP Safety, fest verdrahtete Sicherheits-Ausgänge und OPC UA für den nicht-sicherheits-relevanten Audit-Kanal — alles unterstützt. Most plants already have a safety PLC, light curtains, RFID badges and a lockout-tagout procedure. We feed our detections into what's already there as additional inputs — we do not replace your functional-safety regime. Profisafe, CIP Safety, hard-wired safety outputs and OPC UA for the non-safety audit channel all supported. Most plants already have a safety PLC, light curtains, RFID badges and a lockout-tagout procedure. We feed our detections into what's already there as additional inputs — we do not replace your functional-safety regime. Profisafe, CIP Safety, hard-wired safety outputs and OPC UA for the non-safety audit channel all supported. Most plants already have a safety PLC, light curtains, RFID badges and a lockout-tagout procedure. We feed our detections into what's already there as additional inputs — we do not replace your functional-safety regime. Profisafe, CIP Safety, hard-wired safety outputs and OPC UA for the non-safety audit channel all supported. Most plants already have a safety PLC, light curtains, RFID badges and a lockout-tagout procedure. We feed our detections into what's already there as additional inputs — we do not replace your functional-safety regime. Profisafe, CIP Safety, hard-wired safety outputs and OPC UA for the non-safety audit channel all supported.

IP ownership + audit-log ownershipIP-Eigentum + Audit-Log-EigentumIP ownership + audit-log ownershipIP ownership + audit-log ownershipIP ownership + audit-log ownershipIP ownership + audit-log ownership

You own the source code, the model weights, the labelled dataset and the audit log at handover. The audit log lives in your historian, not on a vendor cloud. We document the system, train your team, and walk away clean. No black box, no monthly per-zone licence, no service contract you can't exit. See our FAQs on IP and engagement model for the standard terms. Sie besitzen Quellcode, Modell-Gewichte, gelabelten Datensatz und Audit-Log nach der Übergabe. Das Audit-Log lebt in Ihrem Historian, nicht in einer Anbieter-Cloud. Wir dokumentieren das System, schulen Ihr Team und gehen sauber raus. Keine Black Box, keine monatliche Pro-Zonen-Lizenz, kein Servicevertrag, aus dem Sie nicht rauskommen. Standard-Bedingungen siehe unsere FAQs zu IP und Zusammenarbeits-Modell. You own the source code, the model weights, the labelled dataset and the audit log at handover. The audit log lives in your historian, not on a vendor cloud. We document the system, train your team, and walk away clean. No black box, no monthly per-zone licence, no service contract you can't exit. See our FAQs on IP and engagement model for the standard terms. You own the source code, the model weights, the labelled dataset and the audit log at handover. The audit log lives in your historian, not on a vendor cloud. We document the system, train your team, and walk away clean. No black box, no monthly per-zone licence, no service contract you can't exit. See our FAQs on IP and engagement model for the standard terms. You own the source code, the model weights, the labelled dataset and the audit log at handover. The audit log lives in your historian, not on a vendor cloud. We document the system, train your team, and walk away clean. No black box, no monthly per-zone licence, no service contract you can't exit. See our FAQs on IP and engagement model for the standard terms. You own the source code, the model weights, the labelled dataset and the audit log at handover. The audit log lives in your historian, not on a vendor cloud. We document the system, train your team, and walk away clean. No black box, no monthly per-zone licence, no service contract you can't exit. See our FAQs on IP and engagement model for the standard terms.

FAQ

Questions about ATEX worker safety AI. Fragen zur Personenerkennung in ATEX-Zonen. Questions about ATEX worker safety AI. Questions about ATEX worker safety AI. Questions about ATEX worker safety AI. Questions about ATEX worker safety AI.

The engagement-model questions we hear from every plant safety officer considering a custom perception build. Need something more specific to your zone? Ask us. Die Fragen zum Zusammenarbeits-Modell, die wir von jedem Sicherheits-Beauftragten hören, der einen Custom-Perception-Build erwägt. Brauchen Sie etwas Spezifischeres zu Ihrer Zone? Sprechen Sie uns an. The engagement-model questions we hear from every plant safety officer considering a custom perception build. Need something more specific to your zone? Ask us. The engagement-model questions we hear from every plant safety officer considering a custom perception build. Need something more specific to your zone? Ask us. The engagement-model questions we hear from every plant safety officer considering a custom perception build. Need something more specific to your zone? Ask us. The engagement-model questions we hear from every plant safety officer considering a custom perception build. Need something more specific to your zone? Ask us.

Industrial Perception AIIndustrielle ObjekterkennungIndustrial Perception AIIndustrial Perception AIIndustrial Perception AIIndustrial Perception AI

What does custom perception AI software cost?Was kostet maßgeschneiderte Wahrnehmungs-Software?What does custom perception AI software cost?What does custom perception AI software cost?What does custom perception AI software cost?What does custom perception AI software cost?
We don't publish list prices because every project is scoped against your data and your decision logic — but we work to three predictable tiers. Discovery & Assessment — a 1–3 day workshop, on-site or remote, fixed price in the low-four-figure range. You receive a written feasibility note, a recommended next step and (if applicable) a fixed-price quote for the follow-on project. Useful even if you don't then go ahead — many customers use the note to evaluate two or three vendors. Custom Pipeline / Tool — a 4–12 week project delivering a working perception pipeline (parser + algorithm + dashboard or OPC UA integration). Fixed scope, fixed price, you own the code at handover. Typical project size is in the mid-five to low-six-figure range depending on data volume, sensor count and integration depth. Long-term Partnership — a monthly retainer for ongoing development and on-call support. Sized to the team capacity you need (typically 0.5–2 FTE equivalent). Quarterly road-mapping included. All three tiers include source code, written documentation and a clean handover — no licence dependence on us. See our Industrial Perception AI service for the full engagement model. Wir veröffentlichen keine Listenpreise, weil jedes Projekt auf Ihre Daten und Ihre Entscheidungs-Logik zugeschnitten wird — aber wir arbeiten in drei berechenbaren Tiers. Discovery & Assessment — ein 1–3-tägiger Workshop, vor Ort oder remote, Festpreis im unteren vierstelligen Bereich. Sie erhalten eine schriftliche Machbarkeits-Note, einen empfohlenen nächsten Schritt und ggf. ein Festpreis-Angebot für das Folge-Projekt. Lohnt sich auch ohne Folge-Auftrag — viele Kunden nutzen die Note, um zwei oder drei Anbieter zu vergleichen. Custom Pipeline / Tool — ein 4–12-Wochen-Projekt, das eine fertige Wahrnehmungs-Pipeline liefert (Parser + Algorithmus + Dashboard oder OPC-UA-Anbindung). Fester Scope, Festpreis, Code-Übergabe am Ende. Übliche Projektgröße liegt im mittleren fünf- bis unteren sechsstelligen Bereich, je nach Datenvolumen, Sensor-Anzahl und Integrations-Tiefe. Langfristige Partnerschaft — monatlicher Retainer für laufende Entwicklung und On-Call-Support. Dimensioniert nach benötigter Team-Kapazität (typisch 0,5–2 FTE-Äquivalente). Quartalsweise Roadmap inklusive. Alle drei Tiers enthalten Quellcode, schriftliche Dokumentation und saubere Übergabe — keine Lizenz-Abhängigkeit von uns. Vollständiges Zusammenarbeits-Modell siehe unsere Industrielle Objekterkennung. We don't publish list prices because every project is scoped against your data and your decision logic — but we work to three predictable tiers. Discovery & Assessment — a 1–3 day workshop, on-site or remote, fixed price in the low-four-figure range. You receive a written feasibility note, a recommended next step and (if applicable) a fixed-price quote for the follow-on project. Useful even if you don't then go ahead — many customers use the note to evaluate two or three vendors. Custom Pipeline / Tool — a 4–12 week project delivering a working perception pipeline (parser + algorithm + dashboard or OPC UA integration). Fixed scope, fixed price, you own the code at handover. Typical project size is in the mid-five to low-six-figure range depending on data volume, sensor count and integration depth. Long-term Partnership — a monthly retainer for ongoing development and on-call support. Sized to the team capacity you need (typically 0.5–2 FTE equivalent). Quarterly road-mapping included. All three tiers include source code, written documentation and a clean handover — no licence dependence on us. See our Industrial Perception AI service for the full engagement model. We don't publish list prices because every project is scoped against your data and your decision logic — but we work to three predictable tiers. Discovery & Assessment — a 1–3 day workshop, on-site or remote, fixed price in the low-four-figure range. You receive a written feasibility note, a recommended next step and (if applicable) a fixed-price quote for the follow-on project. Useful even if you don't then go ahead — many customers use the note to evaluate two or three vendors. Custom Pipeline / Tool — a 4–12 week project delivering a working perception pipeline (parser + algorithm + dashboard or OPC UA integration). Fixed scope, fixed price, you own the code at handover. Typical project size is in the mid-five to low-six-figure range depending on data volume, sensor count and integration depth. Long-term Partnership — a monthly retainer for ongoing development and on-call support. Sized to the team capacity you need (typically 0.5–2 FTE equivalent). Quarterly road-mapping included. All three tiers include source code, written documentation and a clean handover — no licence dependence on us. See our Industrial Perception AI service for the full engagement model. We don't publish list prices because every project is scoped against your data and your decision logic — but we work to three predictable tiers. Discovery & Assessment — a 1–3 day workshop, on-site or remote, fixed price in the low-four-figure range. You receive a written feasibility note, a recommended next step and (if applicable) a fixed-price quote for the follow-on project. Useful even if you don't then go ahead — many customers use the note to evaluate two or three vendors. Custom Pipeline / Tool — a 4–12 week project delivering a working perception pipeline (parser + algorithm + dashboard or OPC UA integration). Fixed scope, fixed price, you own the code at handover. Typical project size is in the mid-five to low-six-figure range depending on data volume, sensor count and integration depth. Long-term Partnership — a monthly retainer for ongoing development and on-call support. Sized to the team capacity you need (typically 0.5–2 FTE equivalent). Quarterly road-mapping included. All three tiers include source code, written documentation and a clean handover — no licence dependence on us. See our Industrial Perception AI service for the full engagement model. We don't publish list prices because every project is scoped against your data and your decision logic — but we work to three predictable tiers. Discovery & Assessment — a 1–3 day workshop, on-site or remote, fixed price in the low-four-figure range. You receive a written feasibility note, a recommended next step and (if applicable) a fixed-price quote for the follow-on project. Useful even if you don't then go ahead — many customers use the note to evaluate two or three vendors. Custom Pipeline / Tool — a 4–12 week project delivering a working perception pipeline (parser + algorithm + dashboard or OPC UA integration). Fixed scope, fixed price, you own the code at handover. Typical project size is in the mid-five to low-six-figure range depending on data volume, sensor count and integration depth. Long-term Partnership — a monthly retainer for ongoing development and on-call support. Sized to the team capacity you need (typically 0.5–2 FTE equivalent). Quarterly road-mapping included. All three tiers include source code, written documentation and a clean handover — no licence dependence on us. See our Industrial Perception AI service for the full engagement model.
How long does it take to build a custom perception pipeline?Wie lange dauert eine maßgeschneiderte Wahrnehmungs-Pipeline?How long does it take to build a custom perception pipeline?How long does it take to build a custom perception pipeline?How long does it take to build a custom perception pipeline?How long does it take to build a custom perception pipeline?
From signed contract to a working tool in production, expect 4–12 weeks for a standard custom-pipeline engagement. The spread is driven by three factors. Data readiness. If you already have labelled data or representative recordings, we start training in week 1. If we need to set up data collection, add a sensor, or label from scratch, the front end adds 1–3 weeks. Integration depth. A standalone dashboard with REST output is the fastest path — typically 4–6 weeks. OPC UA integration into a running control system, with interlocks, factory-acceptance tests and a customer change-management process, is closer to 8–12 weeks. Sensor count and site complexity. One LiDAR + one camera in a clean indoor environment is faster than a six-sensor outdoor portal with dust, snow and dynamic lighting. We scope the difference up-front in the Discovery workshop. For a faster first signal we recommend the Discovery & Assessment tier — 1–3 days, fixed price, written feasibility note within a week. See Industrial Perception AI for the full model. Vom unterzeichneten Vertrag bis zum produktiven Tool rechnen Sie mit 4–12 Wochen für ein Standard-Custom-Pipeline-Projekt. Die Spanne wird von drei Faktoren bestimmt. Datenlage. Wenn Sie bereits gelabelte Daten oder repräsentative Aufnahmen haben, starten wir in Woche 1 mit dem Training. Müssen wir Datenerfassung aufsetzen, einen Sensor ergänzen oder von Null labeln, kommt vorne 1–3 Wochen dazu. Integrations-Tiefe. Ein eigenständiges Dashboard mit REST-Schnittstelle ist der schnellste Weg — typisch 4–6 Wochen. OPC-UA-Anbindung in eine laufende Leittechnik, mit Verriegelungen, Werks-Abnahme und kundenseitigem Change-Management, eher 8–12 Wochen. Sensor-Anzahl und Anlagen-Komplexität. Ein LiDAR + eine Kamera in einer sauberen Innen-Umgebung geht schneller als ein 6-Sensor-Portal im Freien mit Staub, Schnee und wechselndem Licht. Den Unterschied schneiden wir vorab im Discovery-Workshop sauber zu. Für ein schnelleres erstes Signal empfehlen wir das Discovery & Assessment-Tier — 1–3 Tage, Festpreis, schriftliche Machbarkeits-Note innerhalb einer Woche. Vollständiges Modell siehe Industrielle Objekterkennung. From signed contract to a working tool in production, expect 4–12 weeks for a standard custom-pipeline engagement. The spread is driven by three factors. Data readiness. If you already have labelled data or representative recordings, we start training in week 1. If we need to set up data collection, add a sensor, or label from scratch, the front end adds 1–3 weeks. Integration depth. A standalone dashboard with REST output is the fastest path — typically 4–6 weeks. OPC UA integration into a running control system, with interlocks, factory-acceptance tests and a customer change-management process, is closer to 8–12 weeks. Sensor count and site complexity. One LiDAR + one camera in a clean indoor environment is faster than a six-sensor outdoor portal with dust, snow and dynamic lighting. We scope the difference up-front in the Discovery workshop. For a faster first signal we recommend the Discovery & Assessment tier — 1–3 days, fixed price, written feasibility note within a week. See Industrial Perception AI for the full model. From signed contract to a working tool in production, expect 4–12 weeks for a standard custom-pipeline engagement. The spread is driven by three factors. Data readiness. If you already have labelled data or representative recordings, we start training in week 1. If we need to set up data collection, add a sensor, or label from scratch, the front end adds 1–3 weeks. Integration depth. A standalone dashboard with REST output is the fastest path — typically 4–6 weeks. OPC UA integration into a running control system, with interlocks, factory-acceptance tests and a customer change-management process, is closer to 8–12 weeks. Sensor count and site complexity. One LiDAR + one camera in a clean indoor environment is faster than a six-sensor outdoor portal with dust, snow and dynamic lighting. We scope the difference up-front in the Discovery workshop. For a faster first signal we recommend the Discovery & Assessment tier — 1–3 days, fixed price, written feasibility note within a week. See Industrial Perception AI for the full model. From signed contract to a working tool in production, expect 4–12 weeks for a standard custom-pipeline engagement. The spread is driven by three factors. Data readiness. If you already have labelled data or representative recordings, we start training in week 1. If we need to set up data collection, add a sensor, or label from scratch, the front end adds 1–3 weeks. Integration depth. A standalone dashboard with REST output is the fastest path — typically 4–6 weeks. OPC UA integration into a running control system, with interlocks, factory-acceptance tests and a customer change-management process, is closer to 8–12 weeks. Sensor count and site complexity. One LiDAR + one camera in a clean indoor environment is faster than a six-sensor outdoor portal with dust, snow and dynamic lighting. We scope the difference up-front in the Discovery workshop. For a faster first signal we recommend the Discovery & Assessment tier — 1–3 days, fixed price, written feasibility note within a week. See Industrial Perception AI for the full model. From signed contract to a working tool in production, expect 4–12 weeks for a standard custom-pipeline engagement. The spread is driven by three factors. Data readiness. If you already have labelled data or representative recordings, we start training in week 1. If we need to set up data collection, add a sensor, or label from scratch, the front end adds 1–3 weeks. Integration depth. A standalone dashboard with REST output is the fastest path — typically 4–6 weeks. OPC UA integration into a running control system, with interlocks, factory-acceptance tests and a customer change-management process, is closer to 8–12 weeks. Sensor count and site complexity. One LiDAR + one camera in a clean indoor environment is faster than a six-sensor outdoor portal with dust, snow and dynamic lighting. We scope the difference up-front in the Discovery workshop. For a faster first signal we recommend the Discovery & Assessment tier — 1–3 days, fixed price, written feasibility note within a week. See Industrial Perception AI for the full model.
Who owns the code and IP we pay you to build?Wem gehören Code und IP, die wir bei Ihnen beauftragen?Who owns the code and IP we pay you to build?Who owns the code and IP we pay you to build?Who owns the code and IP we pay you to build?Who owns the code and IP we pay you to build?
You do. Our standard contract transfers full ownership of the project-specific code, model weights, training data (where the data is yours) and documentation to you on final acceptance. We don't keep a back-door licence and we don't lock you into a maintenance contract. What we retain is our pre-existing toolbox — reusable libraries, calibration utilities, generic data parsers, the OWL EYE® core — which we license to you, royalty-free, for use on the delivered tool. This is the same boundary that any reputable engineering firm draws: we bring the toolbox, you keep the deliverable. If you want a different IP arrangement — for example a joint patent on a novel algorithm, or a co-developed model that we both reuse with consent — we structure that explicitly in the project contract. Tell us up-front in the Discovery workshop. Full engagement details on our Industrial Perception AI page. Ihnen. Unser Standard-Vertrag überträgt das volle Eigentum am projektspezifischen Code, an den Modell-Gewichten, an Trainingsdaten (soweit die Daten Ihnen gehören) und an der Dokumentation bei der Abnahme an Sie. Wir behalten keine Hintertür-Lizenz und binden Sie nicht an einen Wartungsvertrag. Was bei uns bleibt, ist unser vorhandener Werkzeugkasten — wiederverwendbare Bibliotheken, Kalibrier-Utilities, generische Daten-Parser, der OWL EYE®-Kern — den wir Ihnen lizenzgebührenfrei für das gelieferte Tool lizenzieren. Das ist dieselbe Grenze, die jedes seriöse Ingenieurbüro zieht: Wir bringen den Werkzeugkasten, Sie behalten das Ergebnis. Wenn Sie eine andere IP-Vereinbarung wollen — etwa ein gemeinsames Patent auf einen neuartigen Algorithmus oder ein gemeinsam entwickeltes Modell, das wir beide mit Einwilligung wiederverwenden — regeln wir das explizit im Projektvertrag. Sagen Sie es vorab im Discovery-Workshop. Vollständige Details auf unserer Seite zur Industriellen Objekterkennung. You do. Our standard contract transfers full ownership of the project-specific code, model weights, training data (where the data is yours) and documentation to you on final acceptance. We don't keep a back-door licence and we don't lock you into a maintenance contract. What we retain is our pre-existing toolbox — reusable libraries, calibration utilities, generic data parsers, the OWL EYE® core — which we license to you, royalty-free, for use on the delivered tool. This is the same boundary that any reputable engineering firm draws: we bring the toolbox, you keep the deliverable. If you want a different IP arrangement — for example a joint patent on a novel algorithm, or a co-developed model that we both reuse with consent — we structure that explicitly in the project contract. Tell us up-front in the Discovery workshop. Full engagement details on our Industrial Perception AI page. You do. Our standard contract transfers full ownership of the project-specific code, model weights, training data (where the data is yours) and documentation to you on final acceptance. We don't keep a back-door licence and we don't lock you into a maintenance contract. What we retain is our pre-existing toolbox — reusable libraries, calibration utilities, generic data parsers, the OWL EYE® core — which we license to you, royalty-free, for use on the delivered tool. This is the same boundary that any reputable engineering firm draws: we bring the toolbox, you keep the deliverable. If you want a different IP arrangement — for example a joint patent on a novel algorithm, or a co-developed model that we both reuse with consent — we structure that explicitly in the project contract. Tell us up-front in the Discovery workshop. Full engagement details on our Industrial Perception AI page. You do. Our standard contract transfers full ownership of the project-specific code, model weights, training data (where the data is yours) and documentation to you on final acceptance. We don't keep a back-door licence and we don't lock you into a maintenance contract. What we retain is our pre-existing toolbox — reusable libraries, calibration utilities, generic data parsers, the OWL EYE® core — which we license to you, royalty-free, for use on the delivered tool. This is the same boundary that any reputable engineering firm draws: we bring the toolbox, you keep the deliverable. If you want a different IP arrangement — for example a joint patent on a novel algorithm, or a co-developed model that we both reuse with consent — we structure that explicitly in the project contract. Tell us up-front in the Discovery workshop. Full engagement details on our Industrial Perception AI page. You do. Our standard contract transfers full ownership of the project-specific code, model weights, training data (where the data is yours) and documentation to you on final acceptance. We don't keep a back-door licence and we don't lock you into a maintenance contract. What we retain is our pre-existing toolbox — reusable libraries, calibration utilities, generic data parsers, the OWL EYE® core — which we license to you, royalty-free, for use on the delivered tool. This is the same boundary that any reputable engineering firm draws: we bring the toolbox, you keep the deliverable. If you want a different IP arrangement — for example a joint patent on a novel algorithm, or a co-developed model that we both reuse with consent — we structure that explicitly in the project contract. Tell us up-front in the Discovery workshop. Full engagement details on our Industrial Perception AI page.
Can you use our existing cameras and LiDAR sensors?Können Sie unsere vorhandenen Kameras und LiDAR-Sensoren weiterverwenden?Can you use our existing cameras and LiDAR sensors?Can you use our existing cameras and LiDAR sensors?Can you use our existing cameras and LiDAR sensors?Can you use our existing cameras and LiDAR sensors?
Yes — in most cases. Our toolchain is sensor-agnostic on the data layer. If your sensors deliver a standard format (PCD, LAS, E57 for point clouds; RTSP, GigE Vision, USB3 Vision for cameras) we can ingest them in a day. We've worked with Riegl, Livox, Faro, Hesai, Velodyne, Ouster, Basler, FLIR, Allied Vision and IDS cameras. We'll tell you honestly when the existing hardware isn't the right tool. Common cases where we recommend a replacement: - The existing LiDAR is too narrow (FoV or range) to cover the area you want classified — usually solved by repositioning before buying anything new. - The camera is auto-exposing on a high-contrast scene (sun + shadow at a gate), which breaks classification reliability — solved by switching to a manual-exposure industrial camera with HDR sensor. - The existing sensor's vendor lock-in (proprietary stream format, no documented SDK) makes integration cost more than a Livox replacement. We don't earn a margin on reselling hardware to you. If you do want us to source new sensors, we do that through our normal Hardware & products channel at list price. See Industrial Perception AI for how we scope it. In den meisten Fällen ja. Unsere Toolchain ist auf der Datenebene sensor-agnostisch. Wenn Ihre Sensoren ein Standard-Format liefern (PCD, LAS, E57 für Punktwolken; RTSP, GigE Vision, USB3 Vision für Kameras), binden wir sie an einem Tag an. Wir haben mit Riegl, Livox, Faro, Hesai, Velodyne, Ouster, Basler, FLIR, Allied Vision und IDS gearbeitet. Wir sagen Ihnen ehrlich, wenn die vorhandene Hardware nicht das richtige Werkzeug ist. Übliche Fälle, in denen wir zum Tausch raten: - Der vorhandene LiDAR ist zu schmal (FoV oder Reichweite), um den gewünschten Bereich abzudecken — meist durch Repositionierung gelöst, bevor neu gekauft wird. - Die Kamera auto-belichtet auf einer Szene mit hohem Kontrast (Sonne + Schatten am Tor), das bricht die Klassifikations-Zuverlässigkeit — gelöst durch Wechsel auf eine manuell belichtbare Industrie-Kamera mit HDR-Sensor. - Vendor-Lock-in des vorhandenen Sensors (proprietärer Stream, kein dokumentiertes SDK) macht die Anbindung teurer als ein Livox-Ersatz. Wir verdienen nicht am Weiterverkauf von Hardware an Sie. Wenn Sie wollen, dass wir neue Sensoren beschaffen, läuft das über unseren regulären Kanal Handelsware & Produkte zum Listenpreis. Scoping-Modell siehe Industrielle Objekterkennung. Yes — in most cases. Our toolchain is sensor-agnostic on the data layer. If your sensors deliver a standard format (PCD, LAS, E57 for point clouds; RTSP, GigE Vision, USB3 Vision for cameras) we can ingest them in a day. We've worked with Riegl, Livox, Faro, Hesai, Velodyne, Ouster, Basler, FLIR, Allied Vision and IDS cameras. We'll tell you honestly when the existing hardware isn't the right tool. Common cases where we recommend a replacement: - The existing LiDAR is too narrow (FoV or range) to cover the area you want classified — usually solved by repositioning before buying anything new. - The camera is auto-exposing on a high-contrast scene (sun + shadow at a gate), which breaks classification reliability — solved by switching to a manual-exposure industrial camera with HDR sensor. - The existing sensor's vendor lock-in (proprietary stream format, no documented SDK) makes integration cost more than a Livox replacement. We don't earn a margin on reselling hardware to you. If you do want us to source new sensors, we do that through our normal Hardware & products channel at list price. See Industrial Perception AI for how we scope it. Yes — in most cases. Our toolchain is sensor-agnostic on the data layer. If your sensors deliver a standard format (PCD, LAS, E57 for point clouds; RTSP, GigE Vision, USB3 Vision for cameras) we can ingest them in a day. We've worked with Riegl, Livox, Faro, Hesai, Velodyne, Ouster, Basler, FLIR, Allied Vision and IDS cameras. We'll tell you honestly when the existing hardware isn't the right tool. Common cases where we recommend a replacement: - The existing LiDAR is too narrow (FoV or range) to cover the area you want classified — usually solved by repositioning before buying anything new. - The camera is auto-exposing on a high-contrast scene (sun + shadow at a gate), which breaks classification reliability — solved by switching to a manual-exposure industrial camera with HDR sensor. - The existing sensor's vendor lock-in (proprietary stream format, no documented SDK) makes integration cost more than a Livox replacement. We don't earn a margin on reselling hardware to you. If you do want us to source new sensors, we do that through our normal Hardware & products channel at list price. See Industrial Perception AI for how we scope it. Yes — in most cases. Our toolchain is sensor-agnostic on the data layer. If your sensors deliver a standard format (PCD, LAS, E57 for point clouds; RTSP, GigE Vision, USB3 Vision for cameras) we can ingest them in a day. We've worked with Riegl, Livox, Faro, Hesai, Velodyne, Ouster, Basler, FLIR, Allied Vision and IDS cameras. We'll tell you honestly when the existing hardware isn't the right tool. Common cases where we recommend a replacement: - The existing LiDAR is too narrow (FoV or range) to cover the area you want classified — usually solved by repositioning before buying anything new. - The camera is auto-exposing on a high-contrast scene (sun + shadow at a gate), which breaks classification reliability — solved by switching to a manual-exposure industrial camera with HDR sensor. - The existing sensor's vendor lock-in (proprietary stream format, no documented SDK) makes integration cost more than a Livox replacement. We don't earn a margin on reselling hardware to you. If you do want us to source new sensors, we do that through our normal Hardware & products channel at list price. See Industrial Perception AI for how we scope it. Yes — in most cases. Our toolchain is sensor-agnostic on the data layer. If your sensors deliver a standard format (PCD, LAS, E57 for point clouds; RTSP, GigE Vision, USB3 Vision for cameras) we can ingest them in a day. We've worked with Riegl, Livox, Faro, Hesai, Velodyne, Ouster, Basler, FLIR, Allied Vision and IDS cameras. We'll tell you honestly when the existing hardware isn't the right tool. Common cases where we recommend a replacement: - The existing LiDAR is too narrow (FoV or range) to cover the area you want classified — usually solved by repositioning before buying anything new. - The camera is auto-exposing on a high-contrast scene (sun + shadow at a gate), which breaks classification reliability — solved by switching to a manual-exposure industrial camera with HDR sensor. - The existing sensor's vendor lock-in (proprietary stream format, no documented SDK) makes integration cost more than a Livox replacement. We don't earn a margin on reselling hardware to you. If you do want us to source new sensors, we do that through our normal Hardware & products channel at list price. See Industrial Perception AI for how we scope it.

Send us a zone map and a sample scan.Schicken Sie uns einen Zonen-Plan und einen Beispiel-Scan.Send us a zone map and a sample scan.Send us a zone map and a sample scan.Send us a zone map and a sample scan.Send us a zone map and a sample scan.

A zone layout, a few sample point clouds, a description of your existing safety PLC and lockout-tagout procedure — we come back within two business days with a written feasibility note and a fixed-price scope for the discovery workshop. Part of our Industrial Perception AI service.Ein Zonen-Layout, ein paar Beispiel-Punktwolken, eine Beschreibung Ihrer bestehenden Sicherheits-SPS und Ihres Lockout-Tagout-Verfahrens — wir kommen innerhalb von zwei Werktagen mit einer schriftlichen Machbarkeits-Note und einem Festpreis-Angebot für den Discovery-Workshop zurück. Teil unseres Services Industrielle Objekterkennung.A zone layout, a few sample point clouds, a description of your existing safety PLC and lockout-tagout procedure — we come back within two business days with a written feasibility note and a fixed-price scope for the discovery workshop. Part of our Industrial Perception AI service.A zone layout, a few sample point clouds, a description of your existing safety PLC and lockout-tagout procedure — we come back within two business days with a written feasibility note and a fixed-price scope for the discovery workshop. Part of our Industrial Perception AI service.A zone layout, a few sample point clouds, a description of your existing safety PLC and lockout-tagout procedure — we come back within two business days with a written feasibility note and a fixed-price scope for the discovery workshop. Part of our Industrial Perception AI service.A zone layout, a few sample point clouds, a description of your existing safety PLC and lockout-tagout procedure — we come back within two business days with a written feasibility note and a fixed-price scope for the discovery workshop. Part of our Industrial Perception AI service.

info@sachtleben-technology.com +49 7831 969 22-190
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Tell us about your hazard zone. Erzählen Sie uns von Ihrer Gefahrenzone. Tell us about your hazard zone. Tell us about your hazard zone. Tell us about your hazard zone. Tell us about your hazard zone.

Zone classification, sensor setup, your safety PLC interface, your existing lockout-tagout procedure — anything you have. We come back within two business days with an honest first assessment and a fixed-price scope for the Discovery workshop. Zonen-Einstufung, Sensor-Setup, Ihre Sicherheits-SPS-Schnittstelle, Ihr bestehendes Lockout-Tagout-Verfahren — alles, was Sie haben. Wir kommen innerhalb von zwei Werktagen mit einer ehrlichen ersten Einschätzung und einem Festpreis-Angebot für den Discovery-Workshop zurück. Zone classification, sensor setup, your safety PLC interface, your existing lockout-tagout procedure — anything you have. We come back within two business days with an honest first assessment and a fixed-price scope for the Discovery workshop. Zone classification, sensor setup, your safety PLC interface, your existing lockout-tagout procedure — anything you have. We come back within two business days with an honest first assessment and a fixed-price scope for the Discovery workshop. Zone classification, sensor setup, your safety PLC interface, your existing lockout-tagout procedure — anything you have. We come back within two business days with an honest first assessment and a fixed-price scope for the Discovery workshop. Zone classification, sensor setup, your safety PLC interface, your existing lockout-tagout procedure — anything you have. We come back within two business days with an honest first assessment and a fixed-price scope for the Discovery workshop.

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