Deliverables tailored to ai consulting—designed for production, not prototypes that stall after launch.
Where AI helps, where it hurts, and what must be true for production—not slide-deck hype.
Data flows, model strategy, evaluation, cost model, and a phased rollout with clear decision points.
Threat modeling for AI features, data handling, logging, and sensible controls for regulated contexts.
Playbooks, code patterns, and review checkpoints so your engineers can ship safely after engagement.
OpenAI, Anthropic, Gemini, open-weight models where appropriate
RAG, tool use, structured outputs, caching, routing, guardrails
Vector search, ETL, labeling strategies, offline evaluation
AWS/GCP/Azure AI services, Bedrock, Vertex, enterprise SSO patterns
We map goals, constraints, and define scope with a senior architect.
Senior architect designs the system—no junior guesswork on foundations.
Agile sprints with live demos every Friday and a shared project board.
Production deployment, documentation, and full codebase ownership.
Explore outcomes from similar builds—filter by product type on the portfolio index.
We commonly pair strategy with implementation. If you only need a roadmap, we’ll keep deliverables explicitly advisory.
Typical architecture engagements are 2–6 weeks depending on depth, stakeholders, and existing systems.
Yes—model fit, lock-in risk, data processing terms, and realistic cost curves are part of the work.
Yes. We translate tradeoffs into decisions you can own, with clear milestones and success metrics.
Written architecture, backlog-ready epic breakdown, risk register, and an execution plan with estimates.