A knowledge base built on your data
The agent looks up your catalogue, prices, policies and documentation instead of improvising. Retrieval over real sources, not the model's memory.
Service
An agent decides; a chatbot only answers.
A chatbot follows the branches someone programmed. An AI agent reasons about the goal, looks up the information it needs, chooses which tool to use and carries out the action. It's the difference between answering a question and resolving the matter.
- 3–6 weeks
- Implementation
- Custom project
- Scope
- Your own data
- Knowledge
Why it matters
Most enquiries don't fit a decision tree. "Do you have something similar but cheaper and available this week?" means checking catalogue, stock and calendar at once. Programming every combination is impossible; reasoning over them isn't.
Scope
What's included
Connected tools
It can check availability, create records, book or escalate, depending on what the conversation needs.
Limits and safeguards
We define what it can do on its own and what needs human confirmation. An agent without limits is a risk, not an advantage.
Traceability
Every decision and action is logged, so you can review what the agent did and why.
Ongoing evaluation
We measure hits and misses on real cases, and adjust instructions and sources with that data.
Process
How we do it
- 01
Define the scope
What the agent must be able to resolve, with what information, and how far it can act without supervision.
- 02
Prepare the sources
We structure your information so the agent can look it up reliably, not approximately.
- 03
Build and connect
We build the agent, give it its tools and put the safeguards in place.
- 04
Evaluate before launch
We test it against real cases and measure its accuracy before putting it in front of customers.
Stack
What we build it with
Models chosen per case: not every problem needs the most expensive model, and some don't need a model at all.
- OpenAI
- Claude (Anthropic)
- n8n
- Supabase
- PostgreSQL
- Vectorize
- LangGraph
FAQ
Before you hire us
How is it different from a chatbot?
A chatbot follows a script: if the user says A, it answers B. An agent reasons about the goal, decides which tool to use and takes actions (checking the calendar, writing to the CRM, confirming an appointment) without every branch being programmed in advance.
What if the agent makes things up?
That's why it answers from your sources and not from the model's memory. When it can't find the information, it says so and hands over instead of filling the gap. Sensitive actions require human confirmation, and everything is logged for review.
When do I need an agent, and when is a bot enough?
If your enquiries repeat and fit a handful of paths, a well-built bot is cheaper and more predictable. An agent is worth it when questions span several sources or require choosing between options that can't be listed in advance.
Related
Often combined with
Is this what you need?
Tell us about your case in four questions. We'll tell you honestly whether this service solves it, whether another one fits better, or whether we're not right for you.