Tool-using agents
Agents that call your APIs, query databases and update records with scoped permissions.
AI Agent Development
AI agents that do the work, not just talk about it.
Agents that use your tools, follow your rules and actually finish the job.
Overview
What we deliver
A useful agent is not a chatbot with a bigger prompt. It needs access to the right tools, grounded knowledge, clear guardrails and a way to hand over to a human when confidence is low. We design, build and evaluate agents that run inside your real systems, from customer support to back-office operations, with the observability you need to trust them in production.
- Agent design: goals, tools, policies and escalation paths
- Production agent integrated with your systems
- Evaluation suite with regression benchmarks
- Observability dashboard for traces, cost and quality
- Guardrail and data-privacy configuration
- Runbook for operating and improving the agent
Capabilities
How we can help
Retrieval (RAG)
Answers grounded in your documents, with citations and freshness controls.
Multi-agent orchestration
Specialist agents that plan, delegate and verify each other's work on complex tasks.
Voice & chat agents
Natural conversations on web, WhatsApp, Slack or phone, connected to real actions.
Human-in-the-loop
Approval steps, confidence thresholds and clean escalation to your team.
Evaluation & guardrails
Test suites, red-teaming and runtime policies so quality is measured, not assumed.
Process
How an engagement runs
- 1
Task mapping
We pick a workflow with measurable value and define what 'done' looks like.
- 2
Prototype & eval
A working agent against real examples within weeks, scored by an evaluation suite.
- 3
Harden
Permissions, guardrails, fallbacks and human approval where it matters.
- 4
Operate
Monitoring, feedback loops and monthly quality reviews after launch.
Use cases
Where this makes a difference
Use case 01
Support resolution
Resolve routine tickets end to end: look up orders, issue refunds within policy, escalate the rest.
Use case 02
Sales operations
Research leads, enrich CRM records and draft personalised outreach for review.
Use case 03
Document processing
Read invoices and contracts, extract fields, check rules and file the results.
Typical technology
- Python
- TypeScript
- Claude
- OpenAI
- LangGraph
- LlamaIndex
- pgvector
- Pinecone
- MCP
- AWS Bedrock
Related work
See it in practice
FAQ
AI Agents: common questions
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