AI agents
AI agents for real operational workflows
We build assistants that retrieve information, draft responses and perform approved actions with human oversight.
Discuss your project →Use cases
An agent can work with internal documents, knowledge bases, CRM, ERP or service systems. Action boundaries, roles and sources are defined before launch.
- Document search and grounded answers
- Draft emails and reports
- Request and document classification
- In-workflow guidance for employees
Control and verification
We design source references, logging, access levels and confirmation for critical operations. Where human judgement is required, the agent does not act autonomously.
From prototype to integration
We start with one measurable scenario using approved data. After quality validation, we integrate it into operational systems, document it and transfer knowledge to your team.
Fit before scope
Is this the right starting point?
Use these criteria for an initial orientation. The final recommendation follows a review of your context, data and constraints.
A good fit when
- There is repeatable work with documents, knowledge or systems
- Permitted sources and users are defined
- A person can review critical answers and actions
Resolve this first when
- The agent is expected to make critical or legally significant decisions independently
- Uncontrolled changes to production systems are required
- There are no representative queries or evaluation method
A verifiable first stage
What you can use to make the next decision
The exact scope is agreed before work begins. These are typical decision artefacts, not promised business results.
Agent architecture
Knowledge sources, tools, roles, permitted actions and human approval points.
Working prototype
A bounded scenario using approved data with response and error logging.
Evaluation set
Test queries, quality criteria, risks and a decision for the next iteration.
Five questions · no datasets or credentials
Frequently asked questions
Frequently asked questions
How is an AI agent different from a chatbot?
A chatbot mainly holds a conversation. An agent can use tools and data to perform a defined process within approved boundaries.
Can the model see every document?
No. Access is designed around user roles and your organisation's policies.
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