Production-grade AI,
engineered to ship

Four pillar services — Generative AI Development (LLM apps, RAG, fine-tuning), AI Agent Development (autonomous agents with tool use and guardrails), AI Integration Services (adding AI to existing systems), and AI Readiness Assessment (a 2–4 week audit and rollout roadmap). Every engagement is led by a senior engineer.

We work with frontier models (Anthropic Claude, OpenAI GPT) and open-source LLMs (Llama, Mistral), with retrieval on Pinecone, Weaviate, or pgvector. Agents use tool calling and MCP, and every build ships with evaluation harnesses, tracing, and LLM observability.

We practice eval-driven development — evaluation sets and regression gates before launch — plus guardrails for PII and hallucination control, human-in-the-loop for high-risk actions, and observability to monitor accuracy, cost, and latency in production.

Yes. AI Integration Services adds LLM features, workflow automation, and RAG over your internal data to an existing stack via APIs and incremental rollout, so you ship AI capability without a rewrite.

Start with an AI Readiness Assessment — a 2–4 week audit of your data, systems, and processes that scores use cases by ROI and feasibility and delivers a phased delivery roadmap before any build commitment.