AI agents in business: from prototype to production
An AI agent that impresses in a demo is not yet a useful agent. It becomes one when it works on your real data, inside your tools, with rules your teams understand. That is the step we prepare with you.
What an AI agent can take on
- Sorting, summarising and routing requests, emails or documents.
- Drafting replies, reminders or reports that your teams approve.
- Finding information in your documents and tools, and returning it with its source.
- Chaining repetitive tasks across several applications.
What gets an agent into production
- Accessible, up-to-date data, with defined access rights.
- Human approval for anything that commits the company.
- Logging: who asked for what, and what the agent did.
- Hosting defined at scoping, to fit your constraints.
- A simple measure, agreed before launch.
How we work
We start from a specific process. We find the right tool (a partner platform, a tool you already use, or a new partner we identify) and remain your point of contact. Depending on your need, we also strengthen your team with data experts, or advise you.
Frequently asked questions
Do we need an AI platform to start?
Not necessarily. The right starting point is a process and your data. The tool comes next, sometimes among those you already use.
Can an AI agent act on its own?
It can chain tasks, but anything that commits the company goes through human approval. These rules are set during scoping.
Where is our data hosted?
Wherever your constraints require. Hosting is defined at scoping, before anything goes into production.
Where do you work?
Worldwide, on site or remotely.