Agents that work. A brain that governs them.
We design single-purpose AI agents and the orchestration layer, the “AI brain”, that coordinates them across your organisation. Human checkpoints, audit trails and continuous monitoring are built in from the first sprint.
Agents, brains and the difference.
Most organisations start with one helpful agent. Value compounds when agents can share context and hand work to each other safely. That needs a brain.
An agent
Software that takes a goal, uses tools and data, and completes a task: triaging requests, drafting reports, checking documents. Useful on its own, limited by its lane.
An AI brain
The orchestration layer that routes work between agents and systems, keeps shared memory, applies policy and decides when a human must sign off.
The guardrails
Boundaries, permissions, escalation paths and monitoring that make the whole system safe to trust with real decisions.
Watch a request move through the brain.
Pick a request. The log shows which agents act, where a human checkpoint pauses the flow, and what gets recorded. The scenarios are illustrative.
Guardrails are part of the build, not a review at the end.
New AI regulation across the UK and Europe is turning governance from a choice into an obligation. We design for it from day one.
Boundaries & permissions
Each agent gets only the data and actions it needs. Data-handling rules are agreed and documented before build work begins.
Human-in-the-loop
High-stakes actions pause for a named person to approve, with the reason recorded every time.
Monitoring & audit
Live oversight of agent behaviour, drift and errors, with a full decision trail for auditors and regulators.
From one agent to an organisation-wide brain.
Custom agent design
Agents shaped around your real workflows, not a generic template.
Orchestration layers
Connecting agents to each other and to your business systems.
Data pipeline integration
Secure, permissioned access to the data agents actually need.
Model selection & tuning
The right model for the job, evaluated against your own test cases.
Monitoring & evaluation
Quality, cost and behaviour tracked after launch, not just at sign-off.
Adoption & skills
Training and change support so teams trust and use what we build.
Example engagements.
Illustrative scenarios, not past clients.
Customer operations agent
A retailer wants routine service requests resolved automatically, with complex cases escalated to a person with full context attached.
Enterprise knowledge brain
Knowledge is scattered across dozens of systems. We build an orchestration layer that lets permitted agents find, cite and act on it securely.
Governance-first underwriting assist
Analysts get AI-prepared case files while every recommendation stays explainable and every decision stays human.
Administrative load reduction
Agents prepare referrals, letters and scheduling so clinical staff spend more time with patients, never on clinical judgement.
What could automation free up?
Estimate the time and money AI agents could release from one workflow. Change the numbers to match your team.
Indicative only, based on 46 working weeks and a 37.5-hour week. A diagnostic replaces these assumptions with your measured baseline.
Check these numbers with usAI, answered plainly.
Is our data used to train external models?
Not without your written agreement. Data-handling boundaries are agreed and documented during design, before any build work begins.
How do you stop errors in critical workflows?
Through scoped permissions, human checkpoints on high-stakes actions, evaluation against your own test cases, and monitoring after launch.
Will it work with the tools we already use?
Yes. Agents are built to connect to your existing systems rather than replace them wholesale.
Where should we start?
With one well-chosen workflow that is frequent, measurable and low-risk. A diagnostic identifies it and sets the baseline we measure against.
How is an AI engagement priced?
We start with a fixed-price diagnostic. Build work is priced per workflow, and monitoring is a monthly service so someone stays accountable after launch.
How long until the first agent is live?
Usually eight to twelve weeks for a first governed workflow, including evaluation against your own test cases and a period of supervised running.
What do you need from us?
A process owner, examples of real cases with known outcomes for testing, access to the systems the agent will use, and agreement on which actions need a person.