What it is
An AI agent is a program that uses a language model to decide which steps to take, calls tools such as your CRM or document store, and hands off to a person when it should. We build agents for work that is repetitive but too varied for a simple rule: reading inbound requests, extracting data from documents, drafting replies, updating records and chasing missing information.
Not every problem needs an agent. Part of the job is telling you when a plain script, a form or a scheduled report would do the work more cheaply and reliably.
Who it’s for
- Operations, finance and support teams handling high volumes of similar requests.
- Companies with processes that depend on reading documents: invoices, contracts, applications, claims.
- Teams that tried a no-code automation and hit its limits on messy, real-world inputs.
How we deliver
- Audit the workflow. We trace one process end to end and mark each step as deterministic, judgement-based or exception handling. Only the middle category is a candidate for a model.
- Build an evaluation set first. Before writing the agent we collect real examples with correct answers. This is how we know whether the agent works, and how we catch regressions later.
- Start narrow. The first version handles one task with a human approving every action. Autonomy is increased step by step as accuracy holds up on the evaluation set.
- Design for failure. Every agent has timeouts, spending limits, a clear escalation path and a log of each decision and tool call.
- Operate and tune. We monitor accuracy, cost and latency for the first weeks in production and adjust prompts, tools and thresholds.
What you get
- Agents running in your infrastructure, using model providers on your accounts.
- An evaluation harness you can rerun whenever prompts or models change.
- A review interface where your team approves, corrects and audits agent actions.
- Cost and usage reporting per workflow.
- A runbook covering how to pause, adjust and extend each agent.
