AI agents thatdo real work.
We build agents that handle support requests and internal tasks inside your existing tools, with limits on what they may do and a record of what they did.
01Who it is for
The problems we are usually called about.
Support, operations and service teams handling a high volume of repetitive requests, and the leaders who want that handled without losing control.
The same questions, all day
Skilled staff spend most of their time on requests that have a known answer.
Slow first response
Customers and colleagues wait hours for something a system could resolve in seconds.
A chatbot that frustrated everyone
The last attempt gave confident wrong answers and could not hand over to a person.
No visibility of what AI is doing
Leaders will not approve an agent they cannot audit.
02What we do
Useful inside your systems.
Support agents
Answering customers in your helpdesk or chat from your own knowledge, and handing over to a person when they should.
Operations agents
Looking things up, triaging tickets and preparing reports across your internal systems.
Guardrails and approvals
Clear limits on actions, with human approval for anything that matters.
Audit logs
Every answer and action recorded with its sources.
03How it runs
Step by step.
- 01
Scoping call
We pick one process where an agent would clearly help, and agree what it must never do.
- 02
Knowledge and tools
The agent is connected to the documents and systems it needs, with access limited to its job.
- 03
Test on real cases
It is measured against past requests with known answers before anyone outside the team sees it.
- 04
Controlled launch
It starts with a small group or a draft-only mode, with people approving its work.
- 05
Widen and monitor
Scope grows as the results justify it, with reporting on what it handles and where it hands over.
04What you get
Delivered, documented, yours.
An agent tested on your cases
Measured on real examples before it meets a customer.
Reporting on what it handles
Resolution, handover and error rates.
Control over its knowledge
Your team can update what it knows and what it may do.
Tools we work with
Your stack, not ours
From our work
Account reconciliation platform
A month-end reconciliation platform for a finance team moving off spreadsheets. AI proposes the transaction matches; people review and sign off.
Questions
What clients ask first.
How do you stop it giving wrong answers?
Answers are drawn from your own approved content and shown with their source. We test against known cases before launch and route anything uncertain to a person.
Can it take actions, or only answer?
Both, within limits you set. Reading and drafting are low risk. Actions such as refunds or account changes can require human approval.
What happens when it cannot help?
It hands over to a person with the conversation and what it has already found, so nobody starts again.
Will customers know they are talking to AI?
That is your decision, and we recommend being open about it. The agent can say so and offer a person at any point.
Is this a voice agent?
No. We build agents that work in text, inside helpdesks, chat and internal tools.
How do we know it is working?
You get reporting on volumes handled, handover rate, accuracy on sampled cases and cost per request.
Tell us what you run.
Thirty minutes with an engineer. You leave with a clear scope, a timeline and a recommended approach.
