Take repeatable tasks off your team's hands, with control over what the AI can do.
We build AI agents that carry out tasks across your business systems. Start with one workflow, agree which actions need approval, and test the agent on real examples before giving it access to live work. You can see what it did, where it failed, and what each task cost.
- Tasks passed between tools
- Progress checked by hand
- An agent follows the workflow
- Approvals and actions recorded
- Fewer manual handoffs
- Visibility into each action
- Control over task costs
Best for: Teams automating repeatable tasks or improving an existing agent
What you get
- Working agent and business-system integrations
- Tool permissions and human approval steps
- Test suite with baseline results and failure cases
- Activity and cost reporting, operating instructions, and team training
Scope & integrations
- Connections to business systems through APIs and MCP, with permissions for each tool
- Tests for task completion, mistakes, and changes in behavior
- Activity records, cost tracking, and human approval for agreed actions
When this helps
- Your team repeats the same steps across several systems, and you want to know which parts an agent could handle.
- You have an agent prototype, but need to check its accuracy and permissions before people rely on it.
- You cannot tell why an agent made a mistake or how much its work is costing.
How the work happens
01Choose the task and its limits
We map the workflow, the systems involved, and what happens if the agent gets something wrong. Together we set the permissions and decide when a person must approve an action.
02Agree how to test it
We use representative tasks and known failure cases to check whether the agent completes the work correctly. The same tests run after changes so we can compare results.
03Connect it to your systems
We build the integrations and enforce permissions in the tools and systems the agent uses. Approval steps cover the actions you have agreed need a person to check them.
04Check live behavior and hand it over
Activity records and cost tracking help your team investigate problems. You get the code, tests, operating instructions, and training to manage the agent.
Common questions
Can we start with one task?
Yes. A single workflow lets us agree what success looks like and test whether an agent is useful before you expand its responsibilities.
What happens when the agent gets something wrong?
We agree approval and escalation steps before building. Activity records help trace failures, and known incidents become test cases. These checks reduce risk; they do not make an agent error-free.
Can you improve an agent we already have?
Yes. We test the current agent first, keep what meets the agreed requirements, and show you which parts need to change.
Which models and frameworks do you use?
We can work with Claude, OpenAI, and open-weight models. The choice depends on your tasks, data requirements, and budget. We keep tests with the system so future model changes can be checked against the same work.