An AI assistant that resolves queries end-to-end

The client's team was spending hours on repetitive user queries that always followed the same shape: look something up, cross-check it against account state, reply with the right next step.

Classic chatbots failed here. The job needed an assistant that could act, meaning query systems and file tickets, not just answer from documents.

We designed a tool-using agent: retrieval over the client's knowledge base for grounding, a set of typed tools for the actions it was allowed to take, and an explicit confidence policy for when to hand off to a human.

Before writing the agent loop we wrote its evals: a suite of real historical queries with expected resolutions, so every prompt or model change was measured instead of vibes-tested.

Retrieval-augmented generation over a vector index of the client's docs and FAQs, with citations surfaced in every answer.

A constrained tool layer where each tool is schema-validated, permission-scoped and logged. The agent can only touch what it was given.

Guardrails on both ends: input classification for prompt injection and abuse, output checks for policy compliance, plus full conversation observability.

Shipped to production with human handoff and monitoring in place.