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WHAT WE DO

Industrial AI that performs
under real conditions.

Three focused service areas, all built custom. No templates, no retrofitted demos — systems designed around your environment and your failure modes.

01   CUSTOM VISION SYSTEMS

If it can be seen, it can be automated.

We build AI vision models trained on your specific defects, in your specific environment, against your specific tolerances. Not ImageNet. Not a pre-trained classifier with fine-tuning bolted on. A system designed from the ground up to catch what matters in your process.

The gap between lab performance and field performance is where most vision systems fail. We close that gap by developing and validating in conditions that reflect real operating states — lighting variation, surface contamination, speed, vibration.

Camera and hardware selection, edge or cloud inference, integration with your existing line controls — we handle the full stack.

QUALITY INSPECTIONAutomated detection of surface defects, dimensional deviations, assembly errors, and contamination at production speed.
PROCESS MONITORINGContinuous vision-based monitoring of process states, material flow, and operator activity.
SAFETY & COMPLIANCEPPE detection, zone intrusion alerts, and automated compliance logging.

TECHNICAL APPROACH

  • Custom training data — collected from your environment, labeled to your defect taxonomy
  • Model architecture selected for your inference constraints (edge hardware, latency, power)
  • Multi-camera support with synchronised capture and per-zone inference
  • Continuous learning pipeline — production false positives fed back as training signal
  • PLC / SCADA integration for real-time line control based on vision output
  • Explainability overlays — operators see what the model is attending to, not just a pass/fail

02   INDUSTRIAL ANALYTICS

Data your team can actually act on.

Most industrial operations are already generating data. The problem isn't collection — it's turning raw sensor streams, vision outputs, and process logs into decisions at the speed the operation demands.

We build real-time analytics pipelines that fuse vision data with your existing sensor network, surfacing anomalies and trends through dashboards your team will actually use.

Every dashboard is designed around a decision, not a metric. If a number on screen doesn't change how your team acts, it doesn't belong there.

REAL-TIME DASHBOARDSOperator-facing and management-facing views built around decisions, not data dumps.
ANOMALY DETECTIONStatistical and ML-based detection of process deviations before they become defects or failures.
MULTI-SENSOR FUSIONCombining vision outputs with temperature, pressure, vibration, and other sensor data for richer context.

TECHNICAL APPROACH

  • Edge-to-cloud pipelines — stream or batch, depending on your latency and connectivity requirements
  • Protocol integration: OPC-UA, MQTT, Modbus, and proprietary historian formats
  • Time-series anomaly detection with configurable alert thresholds and runbook integration
  • Historian compatibility — works alongside existing SCADA data stores
  • Role-based dashboard layers — operator, engineer, and management views from the same data
  • Audit trail — all detections and alerts logged with timestamps and context for compliance

03   PREDICTIVE MAINTENANCE

Detect wear before it becomes downtime.

Reactive maintenance is expensive. Scheduled maintenance wastes capacity. Predictive maintenance — done properly — lets you intervene at exactly the right moment, before failure, after maximum useful life.

We build models that learn the visual and data signatures of equipment degradation: bearing wear, belt fatigue, seal degradation, thermal drift. When the signature appears, your team gets an alert — not an incident.

We work with your maintenance engineers to define what "degradation" looks like, then build a system that detects it reliably and early.

VISUAL WEAR DETECTIONCamera-based monitoring of components for surface wear, cracking, misalignment, and contamination.
VIBRATION & THERMAL ANALYSISSensor-driven anomaly detection for rotating equipment, drives, and heat-critical components.
REMAINING USEFUL LIFE ESTIMATIONProbabilistic forecasting to plan maintenance windows with confidence — not guesswork.

TECHNICAL APPROACH

  • Baseline profiling — we establish healthy-state signatures before training degradation detection
  • Combined modalities: vision, vibration, temperature, current draw — fused for higher accuracy
  • CMMS integration — alerts pushed directly to your maintenance management system
  • Confidence scoring — every alert carries an uncertainty estimate, not just a binary flag
  • Model drift monitoring — detects when production conditions have shifted enough to require retraining
  • Failure mode library — built from your specific asset types and historical incident data

HOW AN ENGAGEMENT WORKS

From first conversation to live system.

01

Discovery

We start by understanding your problem — not your budget. A frank conversation about what's happening, what you've tried, and what a successful outcome looks like.

02

Site Assessment

We come to your facility. We look at the environment, the hardware, the data flows. We don't spec a system from a description — we spec it from what we see.

03

Build & Validate

Development happens in close collaboration with your team. We validate at every stage against real production conditions — not held-out test sets.

04

Deploy & Sustain

We don't hand over a model and disappear. We support deployment, monitor performance, and handle retraining as your process evolves.

READY TO TALK

Have a problem we should know about?

Tell us what you're trying to solve. We'll tell you honestly whether we can help — and what that would look like.

GET IN TOUCH