AI agents and knowledge systems
Give AI context.
Give people control.
Custom AI agents and knowledge systems designed for a defined job inside your business.
A good fit when…
I build assistants that can work with approved information, maintain useful context, and take clearly scoped actions through your tools.
- Your team needs answers from its own information
- Policies, records, and process knowledge are scattered. You want an assistant that can find relevant context and make its sources clear.
- Conversations need continuity
- An assistant needs to understand what has already happened, which facts apply, and when a person has taken ownership.
- AI needs to do more than respond
- You want to connect reasoning to useful actions, with permissions and review steps that match the consequences.
What we can build.
- Business knowledge systems
- Organize source material, design retrieval, and keep changing facts separate from general instructions.
- Stateful assistants
- Maintain conversation context alongside operational state, including ownership, next actions, and escalation.
- Controlled tool use
- Connect approved actions to APIs and applications, with validation and human review where the workflow needs it.
- Prompt design and evaluation
- Define response contracts, supported facts, representative scenarios, and checks for uncertainty or incorrect behavior.
How the work takes shape.
- 01Define the job and its limits
We decide what the assistant should answer, what it may do, and when it must ask a person.
- 02Connect context and tools
We identify trustworthy sources, model the state that must persist, and connect only the actions needed for the task.
- 03Evaluate before expanding
We test realistic questions, incomplete information, and failure cases. The first useful version has a bounded scope.
A useful starting point.
A strong brief includes the intended users, a few real tasks, the source information available, and examples of answers or actions that would be unacceptable.
Scope depends on source preparation, retrieval requirements, integrations, access boundaries, and the evaluation needed. Model and infrastructure usage are discussed as part of the design.
I have built stateful conversational systems, structured response contracts, knowledge workflows, and applications with scoped agent tools. The right architecture depends on the job rather than a preferred model or framework.
Calculations, access checks, and exact document fields should use dependable application logic. AI can interpret and propose while those controls remain explicit.
Before we begin.
Does every AI assistant need a custom trained model?
No. The useful first step is usually understanding the task, improving the source information, and evaluating a suitable model with the right context and tools.
Can the assistant use our existing documents and records?
We assess the sources, their quality, permissions, and update process. Access is designed around the task rather than treating every document as available to every user.
Can a person review actions before they happen?
Yes. We can define approval steps for particular actions, keep the proposed change visible, and record the decision in the application.
What would a better
way of working look like?
Tell me about the task, the process, or the idea.
contact@younesnadif.com