We start in your process, not your codebase. Map it, find the bottleneck, fix it with custom software — sometimes that means large language models, computer vision, and AI agents, sometimes it means a boring well-engineered backend. We pick the tool after we understand the problem.
Every engagement starts with the same thing — mapping the actual process. Where it's slow, where it's manual, where it's invisible. Technology comes second, selected to fit the problem. This works where no-code and off-the-shelf tools fall short — when the task needs custom code, trained models, or non-trivial integrations.
GPU-accelerated inspection pipelines, real-time computer vision, and engineering-grade desktop applications for industrial workflows.
Multi-tenant clinical platforms, lab data interpretation, and AI-driven medical reporting with strict reliability and privacy requirements.
Multi-agent architectures, MCP servers, and integration of large language models into existing enterprise tools and processes.
Systems software we build for ourselves — available to integrate into client infrastructure.
Across client projects, the same adjacent problems kept resurfacing — and no off-the-shelf solution fit them well. We built our own, and now offer to integrate them into our clients' infrastructure.
Early versions · expanding feature set · preparing for client pilots.
Used in-house · active development · public release planned.
Used in-house · active development · public release planned.
More projects coming.
Process first, code second. We sit down with the people who actually run the workflow — operators, engineers, managers — and write a process map. The software comes after that conversation, scoped to the problem.
Not every project needs full-cycle delivery. We also take focused engineering work: integrating LLMs into existing pipelines, building MCP servers, designing multi-agent systems for specific workflows, or unblocking stalled codebases.
Engagement formats: fixed-scope delivery, time & materials, embedded engineering team.
Sessions with the team that runs the workflow. We map the steps, find manual work and data gaps. The result is a written process map the customer agrees with.
We select technology to fit the problem, not the other way around. Architecture, risk and cost mapping, delivered as a spec the team can build against.
Iterative delivery with code review, CI, and incremental integration. Demo-driven milestones over hidden roadmaps.
Production rollout with observability — on-prem, cloud, GPU stacks, air-gapped setups when needed. Long-term support, model retraining, feature evolution.
Free first call. NDA up front.
Discuss a project →