Services/Build
AI Agent Development
Agents that plan, call tools, and act inside your systems, with a human in the loop where it matters.
- 8 to 16 weeks
- Fixed scope, or an ongoing team
- Architect plus agent and backend engineers
- Multi-step work that currently needs a person to coordinate it
What we do
We design and build agents that take a goal, break it into steps, use your tools and data, and complete the work. Each agent ships with evaluation, guardrails, and the oversight controls an operations team needs before it runs in production.
What the work includes
Multi-agent architectures
Specialised agents that hand work to each other: research, analysis, drafting, and execution, coordinated by a planner and bounded by explicit rules.
Tool use grounded in your systems
Agents act through your APIs, databases, and internal tools rather than through generic web access, so every action is traceable to a system of record.
Evaluation before rollout
We build the test set from your real cases first, then measure each change against it. An agent goes live when the numbers say it should.
Oversight built in
Human approval gates, escalation paths, and a full audit trail of what the agent saw, decided, and did.
In production
Six supply-chain agents for a Fortune 500 pilot
Supplier risk, tariff analysis, BOM optimisation, sanctions screening, part shortage, and executive insight agents, delivered on a 15-subsystem platform.
See our enterprise experienceHow an engagement runs
Scope, build, evaluate, operate.
The same four stages on every engagement, each with a defined output.
Scope
A short discovery with the people who own the problem. Output: a written scope, acceptance criteria, and a fixed estimate.
Build
A named lead and a team sized to the scope. Working software from the first weeks, demonstrated on a fixed cadence.
Evaluate
Every AI component is measured against real cases before rollout. The numbers decide when it goes live.
Operate
Deployment, monitoring, and a support window. Then a handover, or an ongoing team if you want one.
Typical stack
Tools we commonly use for this work. The final choice follows your requirements, region, and existing platform.
- Python
- LangGraph
- LangChain
- OpenAI
- Anthropic
- PostgreSQL
- Neo4j
- Weaviate
- Docker
Agents in production
Agents that finish the work
Agent projects often stall between the demo and the first real user. We build the evaluation, guardrails, and integrations needed to get past that point.