AI agents that do real work, safely
We design and build AI agents that handle multi-step work: triaging tickets, reconciling data, running cloud runbooks or answering customers. Every agent has clear permissions, audit logs and a human approval step where it matters.
What you get
Use-case discovery
Find the workflows where an agent saves real time, and the ones where it should not be used.
Agent design & tool use
Multi-step agents that call your APIs, databases and SaaS tools through well-defined tools and MCP servers.
Guardrails & human approval
Scoped permissions, approval steps, rate limits and full logs of every action an agent takes.
Evaluation & monitoring
Test suites for agent behaviour, cost tracking and dashboards once it is live.
Step by step
- 1
Pick the workflow
Map one process end to end and agree what success looks like.
- 2
Prototype
A working agent on real data within weeks, not months.
- 3
Harden
Guardrails, evaluations, security review and approvals.
- 4
Launch & improve
Roll out gradually, measure and tune.
What changes for you
- Hours of manual work automated
- Every agent action logged
- Humans approve what matters
Tools we use
Questions about ai agents & automation
Will an agent act without our approval?
Only where you decide it can. We usually start with agents that suggest actions, then add automatic steps once they have proven reliable.
Which models do you use?
Whatever fits the job and your data rules: models on Amazon Bedrock, Azure OpenAI, or open-source models hosted in your own cloud.
Tell us what you are building, or what is keeping you up at night.
A 30-minute call with an engineer, not a sales script. You will leave with practical next steps even if we never work together.