Solution
AI search over your manuals, policies and files that answers staff with a link to the source, only from documents they are allowed to open.
Overview
The answer is in a shared drive somewhere, or an old email, or page forty of a PDF manual. New staff ask the same questions every week, and the person who knows is busy. Keyword search fails because nobody remembers what the document was called.
Retrieval-augmented generation, usually shortened to RAG, means the AI first finds the right passages in your documents, then answers only from those. Every answer quotes and links the passages it came from, so staff can check them.
If your documents already sit in one place, check what that place offers first. Notion AI, Microsoft Copilot over SharePoint, Gemini in Google Workspace and Glean search and answer over their own content and respect its permissions. Build custom when your knowledge is spread across systems those tools do not reach, when answers need to appear inside your own app or in front of customers, or when you need control over which model runs and where the data goes.
Teams whose answers are buried in manuals, policies, drives and old email threads, and who repeat the same questions to the same few people.
Retrieve first, answer second. Index documents with their permissions, find the relevant passages for each question and let the model answer only from those, with links back to the source. A question the documents do not cover returns a plain statement that nothing was found.
In practice
Illustrative examples. Each one is built from the modules below.
Law firm, 20 people
An associate types “what did we tell the Northfield client about the oven?” and gets the answer in seconds, with a link to the call notes it came from. The index and the AI model can run on a machine in the firm’s own office, so client files never go to an outside AI company.
What goes in
Heating and plumbing contractor, 12 vans
A technician on a no heat call asks which part fails most on that furnace model and whether the warranty covers it. The answer comes from the manufacturer’s manual and the company’s own job history, with both sources linked.
What goes in
Membership association
“When did the board last change the late fee, and why?” returns the minutes with the vote. Staff stop interrupting the one person who remembers, and new staff get the same answers as the old hands.
What goes in
Modules
Pull documents from where they live and keep them in step when files change, re-indexing only what changed and dropping deleted files so an old policy stops appearing.
Text from PDFs, Word files, slides and scanned pages, with the original file kept as the source of record.
Matching by meaning as well as keyword, so “refund rules” finds the returns policy.
Answers that quote and link the passages they came from, so staff can check them.
Access rules come from the source, so people only get answers from documents they are allowed to open.
When your documents do not cover the question, the system says so instead of guessing.
Feedback buttons and a log of what people ask, showing which documents are missing.
Architecture
A typical implementation flow, with explicit responsibilities at each boundary.
Connect sources, extract text and keep the index in step with changes and deletions.
Find passages by meaning and keyword, filtered to what the asking person may open.
Generate a cited answer from those passages, log the question and collect feedback.
Security and controls
Carry source permissions into retrieval and test them with restricted documents. Treat document text as untrusted input to the model. Confirm the provider’s data-use terms, or run the model in an account you control.
We select the final stack after reviewing your existing systems and operating requirements.
Security and IP practicesFit
FAQ
It is built to answer only from passages it found, and to show them. When nothing relevant comes back, it says so. No system gets this perfect, so we test it against real questions from your team before launch and keep the question log running after.
On the business API plans of the major AI providers, your data is not used for training by default. We check the current terms of the provider you pick, and the model can also run in a cloud account of your own.
The connectors look for new and changed files on a schedule and re-index only what changed. Deleted files drop out too, so an old policy stops turning up in answers.
Yes. Permissions are carried over from the source system and enforced when passages are retrieved, so a person never receives an answer built from a document they could not open.
Tell us where the current process breaks down. We can map the workflow, examine the integration requirements and define a practical scope for the build.