Knowledge & data
Ask your company’s documents a question. Get an answer with the source.
A private assistant that searches your policies, contracts, manuals and past work, answers in plain language, and shows exactly which file it used.
At a glance
Company knowledge assistant
- Every answer cites its source document
- Respects who is allowed to see what
- Updates as your files change
- Cloud or fully on-premise
Delivered from New Baneshwor, Kathmandu, on-site across the valley and remotely across Nepal.
In short
What is a company knowledge assistant?
A company knowledge assistant is a private chat tool that answers staff questions using your organization’s own documents: policies, contracts, manuals, past proposals and records. It works through a technique called retrieval-augmented generation (RAG): it first finds the relevant passages in your files, then writes an answer from them and shows which documents it used. Bit Microsystems builds these assistants on cloud or fully local infrastructure for organizations in Nepal.
What is included
Everything needed to make it work in practice
One team covers the full job, so there are no gaps between suppliers.
Content audit
We review what you have, where it lives and how current it is, and flag contradictory or outdated material before it is indexed.
Connectors
Links to Google Drive, SharePoint and OneDrive, shared folders or a NAS, your website and internal databases.
Permission-aware indexing
People only get answers from documents they are already allowed to open.
Answers with citations
Each answer links to the file and passage it came from, so staff can verify it in one click.
A simple chat interface
A web chat for the office, with the option to add it to the tools your team already uses.
Evaluation and tuning
We build a test set from real staff questions and measure answer quality before launch and after every change.
Where it is used
Who this helps, and how
Typical situations we design for in Kathmandu and across Nepal.
Onboarding new staff
New joiners ask the assistant how things are done instead of interrupting colleagues or searching old email.
Policy and circular lookup
Banks, cooperatives and institutions get instant, sourced answers from hundreds of internal policies and notices.
Law and consulting firms
Find the relevant clause, precedent or past opinion across years of files, kept entirely in-house.
NGOs and project teams
Reuse past proposals, reports and evaluations instead of rewriting them from memory.
Compare
A public AI chatbot vs a company knowledge assistant
A general assistant such as ChatGPT is excellent for general questions. It simply does not know your organization, and that is the gap a knowledge assistant fills.
| Company knowledge assistant | Public AI chatbot | |
|---|---|---|
| What it knows | Your internal documents, updated as files change. | General public information. |
| Sources | Cites the exact document and passage. | Often none, or public web pages. |
| Access control | Each person only sees what they are permitted to. | Not applicable. |
| Where data lives | Your choice, including fully on your own server. | The provider’s cloud. |
| Best for | Questions about your policies, clients, projects and procedures. | General knowledge, drafting and brainstorming. |
How we work
From first conversation to a system your team uses
- 01
Audit the sources
We agree which document collections are in scope and who should have access to each.
- 02
Build and test
We index the content and test the assistant against real questions from your staff.
- 03
Pilot with one team
A small group uses it daily and reports where answers fall short.
- 04
Roll out and maintain
Wider access, automatic re-indexing as files change, and periodic quality reviews.
Is it right for you?
An honest fit check
We would rather tell you now than after you have paid for the wrong thing.
A good fit if
- Staff regularly ask “where is that written?” or “how did we do this last time?”.
- Knowledge is spread across drives, email attachments and old folders.
- Onboarding takes a long time because so much is undocumented habit.
- The documents are confidential and cannot go into a public chatbot.
Probably not the right choice if
- You have only a few documents that everyone already knows.
- Most of your knowledge is in people’s heads. It has to be written down first, and we can help plan that.
- The documents contradict each other or are badly out of date. The assistant will faithfully repeat whatever it is given.
Tools and technology we work with
Questions
Frequently asked
Straight answers to what people ask us most about this service.
What is RAG (retrieval-augmented generation)?
RAG is a method that lets an AI model answer from a specific set of documents. When someone asks a question, the system first retrieves the most relevant passages from your files, then gives those passages to the model to write the answer. Because the answer is built from retrieved text, it can cite its sources and stays up to date as the documents change.
Does a knowledge assistant still make mistakes?
Far fewer than a general chatbot, because it answers from your documents and shows the source. It can still misread a passage or miss a relevant file. That is why every answer includes citations, and why we measure quality against a set of real questions before launch.
Can it respect document permissions?
Yes. We carry over the access rules from the source system, so a staff member only receives answers drawn from documents they could already open themselves.
Does it work with Nepali documents?
Yes, for documents that contain real text. Scanned Nepali documents need OCR first, which we include where required. Search and answer quality in Nepali is somewhat below English, so we test it on your own files and show you the results.
How is it kept up to date?
The index refreshes automatically on a schedule, so new and edited files are picked up without anyone having to upload them manually.
Should we fine-tune a model on our documents instead?
Usually not. RAG is the right tool for knowledge, because it cites sources and updates the moment a file changes. Fine-tuning is better suited to teaching a model a style or a narrow skill, and it cannot tell you where an answer came from.
Related
Often combined with
Start a conversation
Thinking about company knowledge assistant?
Tell us what you want to achieve and what you have today. We will reply with a clear plan, a realistic timeline and an estimate.