Four practices, one team. Every engagement draws on whichever mix of software engineering, applied AI, and data infrastructure the problem actually needs.
We design and build production applications from scratch: web platforms, internal tools, customer portals, APIs. Every engagement starts with the same question — what does this system need to do in six months, not just at launch — and the architecture follows from the answer.
Applied machine learning, not research for its own sake. We scope the problem, select or fine-tune a model, and build the evaluation and monitoring that make it trustworthy in production — from classification and forecasting to retrieval and generation.
We design agentic systems that plan and execute real engineering work: multi-step coding agents, orchestration layers, and the guardrails that keep them accountable. Every agent ships with human review built into the loop, not bolted on after.
Pipelines and warehousing built for real query volume: ingestion, transformation, and modeling for data that has outgrown a single database. We build the layer your analytics and AI systems actually depend on.
Tell us what you're working on. We'll tell you honestly whether we're the right fit.