Everything an agent needs to be trusted in production.

Before we build anything, we map your workflows and grade each one for agent fit: how repetitive it is, how tolerant of error, how well the required knowledge is written down, and what a good outcome actually looks like. You leave with a ranked shortlist, a rough cost and risk profile for each candidate, and a clear recommendation — including the workflows we think you should not automate yet. Strategy is where we save clients the most money, because a well-chosen first project builds the trust that funds the next.

We build agents around your domain, not a generic template. That means designing the planning loop, the set of tools the agent can call, how it remembers context across a task, and how it decomposes a goal into steps it can actually execute. We write real software: typed interfaces, version control, code review and tests. The result is an agent you own outright, that a competent engineer can read, extend and reason about — never a black box glued together from prompts.

An agent is only as good as what it knows. We design retrieval systems that turn your documents, tickets, wikis and databases into a source of grounded, citeable answers. That covers the unglamorous but decisive work: chunking and indexing strategy, hybrid keyword-and-vector search, reranking, permission-aware retrieval so people only see what they should, and freshness pipelines that keep the index current. Every answer can be traced back to the passage that produced it.

Most business value hides in multi-step processes that cross several systems: read an email, check a record, update a ledger, notify a person. We build agents that carry these workflows end to end, handing off to humans at exactly the points where judgement is needed. We are careful about idempotency and retries, so a half-finished task never corrupts your data, and we design every automation to fail loudly and safely rather than quietly do the wrong thing.

This is the discipline that separates a demo from a system. We build graded test sets from your real cases, run them on every change, and track quality the way an engineering team tracks a regression suite. On top of that sits a guardrail layer: input and output validation, policy checks, rate and cost limits, and clear rules for when the agent must defer to a human. You get dashboards and traces, so when something goes wrong you can see exactly which step failed and why.

An agent that only runs on a laptop is a science project. We deploy into your environment — cloud or on-premise — with the plumbing production demands: authentication, secrets management, logging, monitoring, alerting and cost controls. We integrate with the tools your team already uses through their APIs, ship behind feature flags so you can roll out gradually, and hand over runbooks so your engineers are never dependent on us to keep the lights on.