AI agents for business, built around the decisions people keep.
An agent is useful when it prepares the work and a person decides. We design agents with limits, a route to a human, and a record of everything they did.
An AI agent is software that uses a language model to carry out a task with several steps: read the request, look things up in your systems, apply your rules and prepare a result. That makes agents good at work that was too varied for ordinary automation and too routine for skilled people.
They are a poor fit where the rules are simple enough for plain software, or where nobody can say what a good result looks like. Most operations need a mix: software for the fixed steps, agents for the preparation, and people for the exceptions.
In the illustrative deal desk on our home page, agents and software prepare each non-standard deal against the price book, the approval rules and the contract playbook. People decide the exceptions, and the rep still checks and sends.
What makes an agent safe to rely on.
A definition of acceptable
Before an agent takes a task, we write down what a good result is and how it will be checked. Without that, nobody can tell whether it is working.
A route to a person
When a case falls outside the rules, the agent stops and hands it to someone with the context attached. People decide the exceptions.
A record of what it did
Every step is logged: what the agent read, what it produced and who approved it. That record is how the system gets audited and improved.
Where agents earn their place.
Preparing a decision
Gathering the facts and checking them against your rules, so the person deciding starts with a finished file.
Reading what arrives
Requests, documents and emails that come in different shapes and need sorting, checking and routing.
Working across systems
Tasks that today mean copying between the CRM, a spreadsheet and an inbox.
Drafting to a playbook
First versions of quotes, replies or contract terms, written against your own standards and reviewed by a person.
Questions.
What happens when an agent gets it wrong?
It will, sometimes, so the system is designed for it. Checks catch what can be checked automatically, uncertain cases go to a person, and each mistake is recorded so the system can be corrected.
Which AI model do you use?
Whichever suits the task. We keep the model as a replaceable part, so the system does not depend on one provider and can change as models improve.
Do agents replace people?
The aim is capacity and speed. Agents take the preparation and the waiting out of the work. Judgement and accountability stay with people.
Where do the agents run?
Inside your infrastructure, with access only to the systems and data the task needs.
Where is your business losing time?
Tell us what’s slow, expensive or difficult to scale. We’ll explore where AI could make a meaningful difference.
Book a conversation30 minutes. No preparation needed.