AI for industrial systems, monitored assets
and engineering-heavy operations.
We build production AI where physical systems, sensor data and engineering constraints all matter — and where a model has to work in the field, not just in a notebook.
Why teams like this come to us.
You have sensor or operational data but no reliable way to turn it into useful signals.
Predictive maintenance, anomaly detection or condition monitoring matters, but the path to production is unclear.
Your software team does not have the signal-processing or ML depth needed for the problem.
The solution has to work under real deployment conditions, not just in a lab demo.
Reliability, cost and operational fit matter as much as model accuracy.
How our services show up in industrial operations.
Clarify the highest-value use cases, data readiness, deployment constraints and commercial priorities — before any engineering spend.
Deliver monitoring, prediction or signal-intelligence capability into the systems your team already uses — built for the real deployment environment, not a demo.
Build operational dashboards and decision-support tools for engineering, maintenance and field teams — surfaces the right signal at the right time.
Automate downstream reporting, triage and follow-up where it makes operational sense — so alerts lead to action, not just more noise.
What we build for industrial and asset-heavy teams.
Monitoring and diagnostic systems built on sensor or operational data
Systems that continuously read, process and interpret sensor streams — detecting degradation, anomalies and failure signatures before they become incidents.
Predictive and anomaly-detection capabilities for engineering workflows
ML models trained on your operating data to predict maintenance needs, flag unusual behaviour and reduce unplanned downtime.
Decision-support tools for maintenance and operations teams
Interfaces and dashboards that surface the right information to the right person at the right time — without burying teams in raw data.
Operational workflows that connect AI outputs to real action
Automated routing, triage and reporting that turns an AI output into a work order, an alert, or a documented decision — not just a number on a screen.
Relevant proof.
Production-grade signal and ML systems, deployed under real engineering constraints and built for reliability rather than demo theatre.
HV Circuit Breaker Monitoring
Full-stack signal capture, wavelet analysis and AI diagnostics for high-voltage circuit breakers in the field. A monitoring product that became a product differentiator and went to mass production.
Read case studyExtremeReach Visual Intelligence
Four CV capabilities running at broadcast scale. Built around a hard cost constraint and cost-engineered to 10× below off-the-shelf vector DB solutions — proof that scalable ML systems can be engineered for real cost and performance requirements.
Read case studyNeed AI that works
under real conditions?
Start with Lean AI Strategy or book a discovery call.