AI agents built for real work.
We design AI agents that can understand objectives, retrieve information, use tools, execute workflows, and verify their work within defined business rules.
AI that does more than answer questions — bounded by the parts of the system that are predictable.
- 01
Research agent
Gathers and reconciles source material
- 02
Decision engine
Applies business rules and thresholds
- 03
Tools / APIs
Executes against real systems
- 04
Action
Writes the outcome back
- 05
Verification
Checks the result before it counts
Every step is observable, every tool call is permissioned, and the verification stage decides whether a result is released or escalated.
How our agents are put together.
The intelligent part of the system sits in the middle. Everything around it exists to give that part the right context and to check what it produces.
Intelligence, knowledge, tools, guardrails.
An agent that is missing any one of these is either unreliable, uninformed, incapable of acting, or unsafe to deploy.
Intelligence
Language models and reasoning. The part that interprets an objective, plans a route through it, and explains what it did.
Knowledge
Business data, documents, APIs and context. Retrieval is scoped and cited, so an answer can be traced back to its source.
Tools
The software capabilities an agent is allowed to use — queries, integrations, calculations, writes — each with a typed contract.
Guardrails
Permissions, validation, monitoring and deterministic controls. What the agent may touch, what must be checked, and when a human decides.
Observe, reason, decide, act, learn.
The loop is deliberately boring. Predictable stages are what make an agent reviewable when its output matters.
- 01
Observe
Take in the triggering event, the objective, and the state of the systems around it.
- 02
Reason
Work out what is actually being asked, what information is missing, and which steps the task requires.
- 03
Decide
Choose a course of action — including deciding to stop and escalate to a person.
- 04
Act
Call tools, query systems, write records, and produce output through defined interfaces.
- 05
Learn from outcomes
Record what happened against what was intended, so the behaviour can be reviewed and corrected.
Where agents earn their place.
Six patterns we build most often. Each one replaces a specific, repetitive judgement task — not a person’s job description.
Research agents
Gather material across internal and external sources, reconcile what disagrees, and return a cited summary rather than an unattributed paragraph.
Business process agents
Carry a multi-step workflow across systems that were never designed to talk to each other, with a clear record of every step taken.
Financial intelligence agents
Read filings, releases and market events, and translate them into structured, reviewable positions — the pattern behind MEIA.
Customer operations agents
Resolve routine requests against real account data, and hand off cleanly — with full context — when a case needs a person.
Monitoring agents
Watch systems, data feeds or thresholds continuously, and escalate with the supporting evidence already assembled.
Data agents
Answer questions against warehouses and operational stores, returning the query alongside the answer so results can be checked.
What we will not ship.
Autonomy is a design decision with consequences. These are the positions we hold on every agent we build.
Scoped, not open-ended
An agent is given a defined job, a defined set of tools and a defined set of systems it may touch. It does not get general access to your business because it is convenient.
Checked, not trusted
Output passes deterministic validation before it counts. Where a check cannot be automated, the agent escalates instead of proceeding.
Observable, not opaque
Every step, tool call and decision is logged. When something goes wrong, the trace is there to read — this is a requirement, not a feature.
We do not claim that an agent can replace expert judgement, and we do not build systems whose failure modes we cannot describe. Where a task genuinely needs a person, the right design is an agent that prepares the work and hands it over.
Start with one repetitive decision.
The best first agent is narrow: one workflow, one clear success test, one system of record. Tell us which one is costing you the most time.