01
AI strategy & advisory
Clarify where AI can create durable value, what should be built, and what should stay simple. Best suited to teams moving from exploration to an executable technical roadmap.
Capabilities
Technical judgment before technical complexity.
Support for founders and technical leaders making consequential decisions about applied AI. Engagement shape and scope are defined around the actual constraint, not a fixed package.
02
Computer vision & inference
Architecture for camera-based systems across edge and cloud, with attention to latency, reliability, model constraints, and the economics of inference.
03
AI infrastructure
Practical systems for deploying and operating machine learning workloads, from data and training decisions to production inference and observability.
04
Technical diligence & workshops
Focused reviews for founders and technical leaders evaluating AI roadmaps, architectures, technical risk, or a build-versus-buy decision.
Useful starting questions
Bring the hard decision.
- 01Where can AI create real leverage in this system?
- 02What architecture fits the latency, cost, and reliability constraints?
- 03What should run at the edge, in the cloud, or not exist at all?
- 04How do we move from a promising model to an operating product?
Have a specific system in mind?
Share the operating context and the decision you are facing. Relevance comes before format.