AI Agents & Automation
An agent is a system that decides what to do next. That power needs boundaries. We build agents with explicit tool contracts, step limits, approval gates on consequential actions and complete audit trails.
What this includes
Tool-using agents
Agents that query databases, call internal APIs and operate your existing systems through typed, validated interfaces.
Multi-step reasoning
Graph-based orchestration where each step is inspectable and recoverable rather than a black box.
Human-in-the-loop
Approval checkpoints before any irreversible or outward-facing action.
Workflow automation
Triage, routing, enrichment and back-office processes that previously needed a person reading a screen.
Failure handling
Retries, fallbacks, timeouts and escalation paths designed in from the start.
Audit logging
Every decision, tool call and input recorded for review and compliance.
What you end up with
- Measurable reduction in manual handling time
- Actions bounded by explicit permissions
- Full traceability of every agent decision
- Graceful degradation instead of silent failure
Tools we reach for
Frequently asked
What stops an agent doing something destructive?
Tool design. Destructive capabilities are either not exposed or gated behind explicit human approval. Agents get the narrowest tool surface that does the job.
How many steps should an agent take?
Fewer than you would think. Most production agents work best at two to five steps with a hard ceiling and a clean escalation path.
Other work in this practice
RAG & Knowledge Systems
Turn scattered documents into a knowledge layer your AI can answer from — accurately, with sources.
Read moreLLM Integration
Add language model capability to an existing product without destabilising it.
Read moreComputer Vision
Extract structure and meaning from images, documents and video streams.
Read moreLet's talk about what you're building
Tell us the problem. We'll tell you honestly whether AI is the right tool, and what it would take.