A clear problem statement, success metrics, access to sample data, and a stakeholder who can make decisions help us move quickly. We run a kickoff workshop first so scope, risks, and milestones are aligned.

We need your target workflow, business goals, sample data if available, and access to the systems the AI solution should connect with. From there we define the first usable release.

We choose the model and stack around your privacy, latency, accuracy, and budget needs. We commonly work with leading LLMs, RAG systems, vector databases, workflow automation, and cloud deployment platforms.

Model and API costs are usually estimated separately because they depend on traffic, usage patterns, and hosting choices. We include clear projections before development starts.