03 — Services
AI assistants & agents
AI where it genuinely helps, not where it merely looks impressive.
- Typical timeline
- Four to ten weeks
- Tools
- Claude API، RAG، Vector database، Tool calling، Automated evaluation
- Overview
- System design
The problem
A generic chatbot on a website solves nobody’s problem. What is worth building is an assistant that knows your real prices, your return policy and this customer’s history — and says so when it does not know.
We build assistants that work on your own knowledge and data: customer replies, summarising, classification, extracting information from documents, and drafting.
Our approach
- 01Start from one defined taskInstead of a do-everything assistant, we pick one frequent task that can actually be evaluated.
- 02Connect it to real knowledgeThe assistant answers from your documents, products and records, and cites the source it used.
- 03Draw a clear boundaryWe define what the assistant may not do, and where it must hand the work to a person.
- 04Evaluate before trustingWe measure against a set of real examples, and it stays out of the main path until quality is stable.
Deliverables
- An assistant connected to your knowledge and data
- An evaluation set and a quality report
- Escalation rules for handing over to a person
- A panel to review conversations and cost
Measurable outcomes
- Repetitive questions answered
- a meaningful share
- Time to a first draft
- materially shorter
- Answers logged and reviewable
- complete
complex cases still routed to a person
FAQ
What if the assistant answers something incorrectly?
That is why boundaries and evaluation exist. It declines in uncertain territory and passes the work to a person. No system is error-free, and we do not claim otherwise.
Where does our data go?
During design we decide where data is stored and what must never leave your organisation at all.
Next step
Is this what you were looking for?
Let us have a short call and see what it looks like for your situation specifically.