Most engagements ship a working v1 in 8–10 weeks. We open with a strategy and mapping sprint to define high-ROI use cases and success metrics, then move through design, build, and evaluation in tight, measurable iterations.

A clear problem statement, success metrics, access to sample data, and a stakeholder who can make decisions. We’ll run a kickoff workshop to align scope and lock the KPIs we’ll measure against.

We’re model-agnostic and choose per use case—OpenAI, Anthropic Claude, Google Gemini, xAI, DeepSeek, and others—paired with vector search, orchestration, function-calling toolchains, and observability. We optimize for accuracy, latency, and cost.

Every build ships with guardrails, audit trails, and rigorous evaluation. We run usability testing with real users and track eval pass rates before launch, so features are accurate, secure, and trusted in production.

Model and API usage is billed separately at provider rates, since it scales with your usage. We design pipelines for cost control—caching, hybrid search, re-ranking, and right-sized models—and give you transparent forecasts up front.