STEP 01
The question reaches the appropriate sources
Search takes into account the user's role, topic, and current document versions. Access scope is verified before passing material to the model.
AI PRODUCT / COMPANY KNOWLEDGE
Knowledge, unlocked.
Your team's knowledge, one question away.
WHO THIS SCENARIO IS FOR
Your team's knowledge, one question away.
For organizations where answers are scattered across documents, and a few experienced people constantly explain the same procedures.
STEP 02
The answer shows its basis
The assistant presents a concise result and links to document fragments. In case of contradiction or missing data, it indicates the problem or asks for clarification.
STEP 03
Knowledge grows with the process
The user reports an inaccurate answer with context. The content owner corrects the source, and a representative case is added to tests. Document updates also include the search index.
01 / CHALLENGE
Important information is scattered across documents. The team searches for answers or keeps asking the same people.
02 / SOLUTION
An assistant searches approved sources, cites them and respects each user's document permissions.
03 / HOW TO MEASURE VALUE
Time to find an answer, citation accuracy and questions escalated to an expert.
DESIGN DECISIONS
A scope you can test.
The initial scope would cover an approved collection of documents and one type of questions. We would not connect the entire company drive without verifying permissions and currency. The ability to cite sources and correctly report a lack of answer would be as important as providing an accurate answer.
How would we plan a pilot?
The acceptance test set would include typical, ambiguous, and unanswerable questions. We would separately evaluate search accuracy and source utilization. The time to find a useful answer would be compared with previous work and the number of questions directed to an expert.
SAMPLE ACCEPTANCE CRITERIA
What needs to work?
- The answer has a source that actually confirms the provided information.
- Content outside the user's access does not enter the model's context.
- A withdrawn document does not reappear via the index or shared buffer.
- If information is missing, the system suggests a possible next step.
EXPLORE OUR APPROACH
From scenario to informed decision.
01 AI Technology / 4 min
RAG in the enterprise: how to build an assistant that leverages your knowledge
Connecting a file catalog is just the beginning. A useful RAG system requires order in documents, accurate retrieval, updates, and access control for every source.
Read article
02 Quality and security / 4 min
Permissions in the AI assistant: who can see which response?
A corporate assistant should not become a shortcut to data outside the user's role. Plan access in search, memory, history, and operations.
Read article
03 Quality and security / 4 min
Evals: How to test AI quality before changing the model or prompt
Manually checking a few responses will not reveal what broke elsewhere. Build an evaluation set that corresponds to the tasks and the consequences of errors.
Read articleLET'S TAKE THE FIRST STEP
Let's discuss
your project.
You don't need a finished specification. Tell us what you want to improve, and we'll find the right place to start together.
- We'll find where technology can bring you the most value.
- We'll discuss scope, budget and a practical plan.
- We'll agree on a clear next step, with no obligation.