From a useful answer to a useful action.
Custom AI agents that work with your business systems. Build useful assistants with defined permissions, human approval and realistic evaluation.
For operations teams juggling requests across systems.
Let’s talk ai agentsGive good work a capable assistant.
An agent becomes useful when it can work with the right context and tools. We design that connection carefully, with a clear boundary between what it can suggest and what it can do.
- Task-specific agents connected to your tools
- Defined permissions and approval points
- Evaluation against real working scenarios
What we work through.
Define the boundaries
Set the tasks, allowed data, available tools and actions that always require a person. Keep the initial scope narrow enough to evaluate.
Connect the context
Bring together approved knowledge and system APIs. Design for incomplete information, missing permissions and unavailable services.
Test the behaviour
Evaluate normal requests, ambiguous instructions and failure scenarios. Establish monitoring, feedback and a responsible owner.
AI that works across your business.
Some tasks need several capabilities working together: understanding a request, finding relevant information and preparing an action. We design workflows that bring those steps together, with clear checks and human approval where it matters.
Give each capability a clear job
An assistant becomes easier to assess when its purpose and boundaries are clear. We define what information it receives, which tools it can use and what a useful result contains. When several capabilities are needed, we design the handoffs between them and keep responsibility for the overall task visible.
Combine judgement with dependable steps
AI can interpret a request or work with variable information, while conventional software checks required details and applies agreed rules. We decide which parts need flexibility and which should follow a predictable path. Adding more agents is a design choice that needs to earn its place.
Make authority explicit
Reading information, preparing a draft and changing a business record are different permissions. We design access and approval checks into the software that performs the action. A reviewer should see the proposed change and relevant context, with a clear choice to approve, correct or decline it.
Handle uncertainty and stopping points
An agent needs a useful response when it cannot finish. We plan for missing context, unavailable tools and requests outside its scope. Limits on attempts and execution time help contain failed runs, while a clear handoff lets a person continue with the information already gathered.
Good questions.
Clear answers.
How is an AI agent different from a chatbot?
A chatbot primarily holds a conversation. An agent may also use tools or take steps to complete a task. The important question is which capabilities your workflow actually needs.
Can people approve important actions?
Yes. We can design approval steps for changes such as updating a record or sending a message, and limit an agent to read-only access where appropriate.
Do we need several AI agents?
Only when separate capabilities or responsibilities make the work easier to deliver and assess. A focused agent or a conventional workflow may be enough. We consider coordination effort, latency and running cost before recommending a more complex design.
Can an agent work without a chat window?
Yes. An agreed business event or scheduled process can trigger a workflow. The right interface depends on who needs to supply information, review the result or approve an action. A conversational interface is one option.
How can we tell what an agent actually did?
We design an appropriate activity record showing relevant steps, tool outcomes and approval decisions. What is retained and who can view it are agreed during design. Logs should help investigation without unnecessarily collecting sensitive content.
What could work
better for you?
Bring us the bottleneck, the big idea,
or the question you keep coming back to.