Most AI projects die between the notebook and production. We build the systems that survive the crossing, models that run against messy real-world data, on real hardware, with the monitoring to prove they still work next quarter.
Applied machine learning for organizations with real data problems, not demo datasets.
Object detection, segmentation and tracking on imagery from drones, fixed cameras and inspection rigs. Our Côté Gold blast-analysis system took first place against 29 teams.
Inference that runs on-device where bandwidth is scarce or latency matters, rather than shipping every frame to a cloud that may not be reachable.
Forecasting and anomaly detection over telemetry and operational history, built so the output lands in the tools your team already uses.
Extraction, classification and summarization over the documents and free text your operation generates, with human review where accuracy is non-negotiable.
A focused build that answers whether the hard part is achievable at all, before anyone commits to a full programme. Typically weeks, not quarters.
Monitoring, drift detection, retraining pipelines and fallbacks, the work that separates a model that demos from a model that operates.
Vision and AI systems we have taken from problem statement to working deployment.
Won 1st place analyzing open-pit mining blasts from drone footage, beating 29 teams from across Ontario.
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AI-powered fall detection without wearables, running vision inference at the edge.
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Real-time AI processing and analysis of complex aviation operations data.
Read MoreWe choose tools to fit the problem and your team's ability to maintain them, not the other way round.
No long discovery invoices before anyone writes code. We aim to have you looking at working software early.
Thirty minutes. You describe the problem, we ask hard questions and tell you how we would approach it, including if we are not the right team.
We define the smallest version that proves the hard part, agree the technical approach, and give you a fixed plan with milestones.
Working software in front of you on a regular cadence, so direction changes stay cheap and surprises surface early.
Deployment, monitoring and ongoing support. We build systems we expect to still be maintaining in three years.
“Their understanding of complex healthcare requirements and ability to translate them into engaging gamified experiences was outstanding. We wouldn't be where we are today without them.”
UKE Hamburg · COGITO
Not always. We often begin by assessing what data you already have and whether a smaller labelled set, transfer learning or synthetic augmentation can carry a first version. Part of the discovery call is working out whether your data can support the result you want.
Yes. Edge deployment is a core part of our work, running inference on-device for environments where connectivity is intermittent or absent, which is the normal case in mining and industrial settings.
We scope a proof of concept against your data with agreed success criteria defined up front. If it does not clear the bar, you have an inexpensive and definitive answer rather than a half-finished programme.
You do. Ownership of the code and trained models transfers to you, and we document them so another team could pick them up.
Tell us what you're trying to build. We'll spend 30 minutes understanding the problem and tell you how we'd approach it.
Book a 30-Minute Discovery Call