Knowledge base
Answers from policies, guides, product docs, and internal materials with cited context.
Artificial intelligence Teams with large internal material libraries and recurring information requests
An AI assistant answers from your knowledge base with sources
The assistant gets only allowed context, shows the answer source, never runs critical actions unchecked, and knows when to escalate.
01Question
02Search
03Source
04Answer
OutputAnswer + source link
Low confidence leads to clarification or a human.
Practical outcome
The assistant finds a relevant fragment, answers with a source, and escalates doubtful requests
Problem
Answers take long to find, knowledge is scattered, and a plain AI chat may answer without grounding
Primary route
question → knowledge search → sourced answer → review or escalation
A good fit for
Where an assistant is useful and safe
Teams with large internal material libraries and recurring information requests
Employee helper
Drafts, information search, and allowed actions in work tools.
First line
Handling typical requests and escalating when data is thin or error risk is high.
Fit / boundaries
What must not go unchecked
AI does not make critical decisions and never sees data outside the user's rights
01AI must not be the sole path for critical decisions
02Quality is limited by source completeness and freshness
03Private data requires access filters and audit
Working scenarios
Answers, actions, and AI boundaries
Demonstration routes, not client results. Exact logic depends on your rules, data, and systems.
Scenario / 01
Answer with sources
The query becomes a search; matching fragments are filtered and used for a sourced reply.
1Question2Search3Context4Answer
Scenario / 02
API action
The assistant clarifies parameters, shows the action plan, and calls an allowed function after confirm.
1Intent2Params3Confirm4API
Scenario / 03
Escalate to expert
On low confidence it builds a short summary, attaches context, and opens a ticket.
1Question2Score3Summary4Expert
Engagement trigger
When knowledge search slows work
You need fast search and answers from allowed sources with clear escalation
- 01Information is scattered across many documents
- 02People keep asking experts the same questions
- 03Ordinary search fails on user phrasing
- 04Public AI cannot safely touch internal data
Solution scope
Context, access, and control
- Scenario and risk map
- Prepared knowledge loop
- AI assistant and interface
- Validation question set
- Logging and documentation
Data and systems in the loopLLM APITelegramREST APIDocumentsKnowledge basesVector search
How we launch
From a real process to a working loop
Tools are chosen after we verify inputs, exceptions, and the success criterion.
- 01
We set boundaries
Allowed questions, actions, audience, and mandatory escalation cases.
- 02
We prepare knowledge
Documents, structure, freshness, rights, and owners.
- 03
We design retrieval
Chunking, indexing, access filters, and context selection rules.
- 04
We add control
Function limits, answer format checks, and source logging.
- 05
We score quality
A test question set, completeness metrics, and error review before launch.
Will the assistant train on our data?+
Most often we use retrieval over a private knowledge base without model fine-tuning. Approach depends on volume, quality, and hosting needs.
How do you reduce hallucinated answers?+
Limit question scope, ground answers in found sources, score confidence, and escalate when confirmed context is missing.
Can document access be restricted?+
Yes. User rights apply before context search so the model never sees forbidden fragments.
Can it trigger actions in tools?+
Yes, via strictly described API functions, parameter checks, and confirmation for significant operations.
How is quality measured?+
On real questions: correctness, source presence, completeness, escalation rate, and error patterns.
First step
Discuss an AI assistant
We'll map inputs, exceptions, and constraints. You leave with a priority scenario and a next step — no obligation to start a project.
Discuss an AI assistantService: AI assistants