AI agents for business
Custom AI agents that work inside your CRM, documents, email and internal tools, with your data and your rules. Designed, integrated and deployed to production.
What is an AI agent for business?
An AI agent takes a request, gathers the context it needs, then acts: it looks up a customer record, drafts a document, updates the CRM or hands a case to the right person. That is agentic AI: a language model that doesn’t just answer, but carries out steps in your systems.
In a business, the hard part isn’t the model. It’s the integration: access, permissions, human approvals and error handling. That is the part this work focuses on.
Examples
Agents that take repetitive, multi-step work off your team, with people kept in the loop.
Inbound requests and customer service
The agent reads emails or form submissions, pulls up the customer’s history, drafts a reply and routes complex cases to your team.
Documents and admin
Invoices, contracts, purchase orders: the agent extracts the data, checks it and enters it in your software, with human approval where needed.
Sales and CRM
Drafting a proposal, summarising an account before a meeting, updating opportunities: the agent works from your CRM and documents.
How it works
Integration through your existing APIs, the Model Context Protocol (MCP) or custom connectors. Each agent has defined permissions and approval steps, and its actions are logged and reversible. You own the code.
Already have a prototype? See the AI audit- 01
Pick the first use case
One specific workflow, the tools and data it touches, the decisions that stay with people, and how success is measured.
- 02
Build and integrate
Develop the agent, connect it to your systems and test it with your team on real cases, including errors and exceptions.
- 03
Deploy and hand over
Production release with monitoring, then handover: code, tests and operating documentation. Ongoing support a few days a month is available for the next agents.
Questions
Custom AI agent or off-the-shelf tool?
If an existing tool covers your need, you’ll hear that first. A custom agent makes sense when the workflow spans several systems, needs rules specific to your business or handles sensitive data.
How long does it take to set up an AI agent?
It depends on how many systems need connecting and which approvals are required. Scope and timeline are agreed before development starts.
Does our data stay confidential?
The agent only accesses the data its task needs. The choice of model and hosting follows your constraints, including GDPR.
Do we need an in-house technical team?
No. You get a documented agent and a walkthrough so your team can use it. If you have developers, they get the code and tests to extend it.
Discuss a project
Describe the task, the software involved and what you need to change.
Request a 30-minute call