AI systems that understand a goal, use your tools, execute the workflow, and know when to hand back to a human.
They work on a clean prompt and fail on the fourth edge case. The gap between a convincing demo and a system your operations team relies on is engineering — tool contracts, memory, failure handling, evaluation and observability.
An agent is not a chat window. It is a system that holds a goal, selects tools, reads authorized data, takes action inside your business systems, and escalates when a decision exceeds its mandate. We engineer that system — and the evaluation and observability that make it trustworthy in production.
The last column is what separates a demo from a system you can operate.
Anatomy of a production agent
A goal and its policy enter at the top. The runtime reasons over authorized context, plans, and acts through typed tool calls. Anything the risk model flags passes a human approval gate before it reaches your systems of record. Governance, observability and audit span every layer — which is the part that decides whether the thing can be operated rather than merely demonstrated.
Engagements draw on a subset of these, scoped to the outcome you are buying.
Custom agents built around one business-specific workflow, not a general assistant bolted onto a department.
Specialized agents that collaborate on a task chain — research, analysis, decision, execution — with a human approval gate where the stakes require one.
Typed, permissioned tool contracts connecting agents to CRMs, ERPs, databases, APIs, email, calendars, cloud platforms and internal applications.
An agent scoped to a defined, repeatable business function — an AI research analyst, recruitment coordinator, or operations coordinator — with an owner and a performance baseline.
We redesign the workflow around what an agent is genuinely good at, rather than inserting a chatbot into a process that was designed for humans.
Autonomy tiered by risk: act freely on low-risk steps, draft-and-request-approval on sensitive ones, hard-stop on anything that moves money or commits the business.
Where a system has no API and replacing it is not on the table, agents can operate the interface directly — used deliberately, and only where it is the right trade-off.
Retrieval and memory designed for the task: what the agent should recall across a session, across a case, and across the organization — and what it must never retain.
A test suite for behaviour: accuracy, tool selection, hallucination rate, task completion, policy adherence and deliberate failure scenarios — run on every change.
Every action, tool call, latency figure, token cost, failure and human intervention traced and queryable, so the system can be operated rather than trusted blindly.
These are illustrative constructions, not client case studies. We do not publish customer names, savings figures or results we have not verified.
The problem
Inbound enquiries arrive by web form and email. Response times drift, enrichment is manual, and the CRM record is incomplete before a rep ever sees it.
What we would build
An agent that reads the enquiry, enriches the company from authorized sources, scores it against the ICP, writes a structured CRM record, and drafts a first response for rep approval.
How it works
Potential business impact
Faster and more consistent first response, a cleaner pipeline, and reps spending their time on qualified conversations rather than triage.
The problem
Responding to an RFP means one team reading hundreds of pages, hunting for prior answers across shared drives, and assembling a document under deadline.
What we would build
A chain of specialized agents: a requirements agent that decomposes the tender, a retrieval agent that finds prior approved answers, a drafting agent that assembles a response, and a compliance agent that checks it against the tender’s own mandatory criteria.
How it works
Potential business impact
A first draft in hours rather than days, with every claim traceable to an approved source, and the bid team reviewing instead of assembling.
Where we set out the reasoning, in more detail than a capability list allows.
