Custom AI agents built around how you work
When no ready-made agent fits, we build one that does. We map the workflow, connect your systems, and release in stages, so you see it working before you commit to the next step.
Your process is not a template
Some work does not look like anyone else’s: an intake process with your own rules, an approval chain across three systems, a knowledge base only your team understands. A generic agent will not fit, and bending your process around it costs more than it saves.
A custom agent starts from your workflow and ends with software that does that workflow, with your rules, in your systems.
- Your process has steps no ready-made agent covers
- The agent must work with internal systems or data
- You need specific approval and audit rules
- Several steps across several tools must run as one flow
Examples of custom agents
Each one starts as a written scope for a single workflow.
Document intake agent
Reads incoming forms and attachments, extracts the fields you need, checks them against rules and files them where they belong.
Order and returns agent
Looks up an order, answers status questions, starts a return and updates the record.
Internal knowledge agent
Answers staff questions from your policies, handbooks and past answers, and cites the source it used.
Scheduling and dispatch agent
Matches requests to available people and times, confirms with both sides and handles changes.
Research and briefing agent
Gathers information from the sources you specify and delivers a structured brief on a schedule.
Approval workflow agent
Routes requests to the right approver, chases replies and records the decision.
How a custom agent comes together
Map the workflow
We follow the task from trigger to finish, noting every decision, tool and exception.
Write the scope
You receive what the agent does alone, what needs approval, what it connects to and how it will be tested.
Build and test
We build against real examples from your business and run the written test set after every change.
Release in stages
The agent starts supervised. You expand its authority as the results earn it.
Connected to the systems you already run
Agents work inside your tools through supported interfaces, using accounts we can limit and revoke. We design each connection with the least access the job needs, and we agree in writing what data the agent can read and write.
Where a system has no suitable interface, we say so early and propose an alternative rather than building something fragile.
- Email, calendars, CRMs, helpdesks and spreadsheets
- Databases and internal systems, through approved interfaces
- Documents, forms and knowledge bases
- Messaging tools such as Slack and Teams
Which one do you need?
| Prebuilt agent | Custom agent | Enterprise | |
|---|---|---|---|
| Discovery call and fit assessment | |||
| Written scope and approval rules | |||
| Set up on your tools and knowledge | |||
| Starting design | Proven design for a common job | Built from your workflow | Built from your workflow and policies |
| Internal systems and databases | – | ||
| Testing before launch | Checked on your own examples | Written test set | Written test set with pass marks |
| Supervised, staged release | |||
| Activity log of every action | |||
| Exportable audit trail and named approvers | – | Optional | |
| Identity and access integration | – | Optional | |
| Documentation for your team | Plain-language guide | Full documentation | Documentation and runbooks |
| Ongoing improvement | Optional | Optional | Optional |
| Best for | Small business | A process unique to you | Large teams |
What you receive at the end
A custom engagement ends with something you can run, understand and change, not a black box.
- The working agent, deployed in your environment or ours as agreed
- Documentation of what it does, what it can access and how to change its rules
- The written test set with expected results
- Optional support and improvement after launch
Straight answers
What is a custom AI agent?
A custom AI agent is software that uses a language model to complete a defined task in your business, connected to your own data and tools and built to follow your rules.
How do you decide what to build first?
We choose the workflow with clear steps, repeated effort and a result a person can check. The discovery call is for exactly this decision.
How do you keep an agent from making costly mistakes?
We limit its permissions, add approval points to sensitive actions, and test it against a written set of real cases before it goes live.
Who owns the agent?
Ownership and licence terms are agreed in writing before work starts.
What do we receive at the end?
The working agent, documentation, the test set, and a clear way to change its rules. Ongoing support is optional.
How long does a custom build take?
It depends on the workflow and the systems involved. After discovery you receive a staged plan, so you can see the path and decide stage by stage.
Can you work with our internal systems?
Yes, through supported interfaces such as APIs, database access or file exchange. We confirm what is possible during scoping.
What if the first version is not right?
That is why we test against real cases and release in stages. Problems appear while the agent is supervised, and we fix them before it gains more authority.
Ready to talk it through?
Tell us the task and we will tell you whether an agent fits.
Request a demo Book a call