RAG pilot on company data
A RAG pilot tests on a selected document set whether the system finds the right sources and answers at a quality level sufficient for a larger implementation.
fromPLN 12,000
A RAG pilot is a limited, measurable test of whether your documents can support useful answers that point back to their sources. It turns an assumption about “company knowledge in AI” into evidence before a larger investment.
When to start with a pilot
- You have documents, procedures, or tickets, but do not know whether they are complete enough for retrieval.
- Answer accuracy and traceability matter more than a polished chat interface.
- Different access levels or sensitive information need to be understood before full rollout.
- You need a decision document rather than a vendor promise.
How it works
Together we select a representative knowledge slice and a set of real questions with expected outcomes. We inspect formats and source quality, build ingestion and retrieval, design source-citing answers, and evaluate relevance, completeness, and correct evidence. We then tune the approach and compare results.
The pilot also identifies missing, contradictory, duplicate, or inaccessible content. It does not pretend that a good answer on a small collection automatically proves production quality for every company source.
What you receive
- a working pilot on the agreed document sample;
- a question set and transparent quality evaluation;
- answer examples with source references;
- a list of source-data problems and access requirements;
- a recommendation and technical direction for the next stage.
The pilot starts from 12,000 PLN. Pricing depends on the amount and condition of the source sample, formats, and required accuracy. A successful direction can grow into a second brain for companies; if the first decision is which process to improve, begin with an AI audit.
FAQ
Why a pilot rather than the whole system immediately?
Answer quality depends on the condition of your documents, which cannot be assessed from a presentation. A pilot limits the source set and investment while measuring results before a full decision.
What if we do not continue?
You retain the quality report, source-problem list, recommendation, and code within the contract scope. The material can support a later decision with another supplier as well.
How do you measure answer quality?
Using a question set agreed with you and expected answers: we test relevance, completeness, and whether the system points to the correct source. You see results before and after tuning, not merely a claim that it works.
Do our documents leave our environment?
That depends on the selected architecture and model. Before work, we agree what may reach an external API, what must stay in your environment, and what access and retention requirements apply.
Does a good pilot result guarantee quality across the whole knowledge base?
No. A pilot confirms results on an agreed sample and question set. More sources can introduce formats, contradictions, and access requirements that need separate validation.