AI Agent Development
We build autonomous agents that plan, use tools and complete real workflows. Architecture, evaluation, red-teaming and operation, engineered so they are safe to run in production.
Agents that do real work
An AI agent is a system that plans, calls tools and takes multi-step actions toward a goal. The value is real, and so is the risk: an agent that acts on your systems needs guardrails, not just a good prompt.
We design the agent architecture, build the tool integrations, put an evaluation harness and red-team pass in place, and operate the result so it stays reliable as your tools and data change.
- Multi-step, tool-using agents scoped to a real workflow.
- Evaluation and red-teaming before anything touches production.
- Human approval gates and audit trails where they matter.
How we build agents
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Architecture and tools
We design the planning loop, the tools the agent can call and the boundaries it must respect, matched to your systems.
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Evaluation and red-team
An evaluation harness against real tasks plus adversarial testing, so failure modes are found before users are.
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Guardrails and operation
Approval gates, audit trails and monitoring so an agent can act with the right level of autonomy and oversight.
Frequently asked questions
Are agents safe to let loose on our systems?
With the right design, yes. We scope what an agent can do, add human approval gates for sensitive actions, and log every step for audit.
How do you stop an agent going wrong?
We red-team it against adversarial inputs and edge cases, and we constrain its tools and permissions so the blast radius of any mistake stays small.
What frameworks do you use?
We choose per project across the mainstream agent frameworks and build directly on model APIs where that gives more control over reliability and cost.
Put an agent on the repetitive work
Tell us the workflow you want an agent to own. We will scope an architecture that is reliable and safe to operate.