Artificial intelligence · Artificial Intelligence

Internal search and knowledge base

Everything your company knows, scattered across folders, inboxes and systems, searchable in a single box and with sourced answers.

Sources: Documents, email, intranet and systems
Search: Semantic, not exact keyword
Duration: 5 to 10 weeks
Responses: Always with its source cited

The problem

The knowledge exists, but it is split between a shared folder, the inbox of someone who no longer works here and the heads of three people. Searching by exact keyword does not find it.

What it includes

Multi-source indexing

Documents, email, intranet, manuals and internal systems, in a single up-to-date index.

Search by meaning

It finds what you meant even if you do not use the words of the original document.

Sourced answers

Every answer points to which document and which paragraph it came from, so it can be verified.

Permissions respected

Each person sees only what they were already entitled to see: the search engine does not break existing security.

Continuous updating

The index refreshes only when documents change, without reprocessing everything each time.

How we work

01
Inventory
Where the knowledge lives and who can see what.
02
Ingestion
Initial indexing and definition of the update cycle.
03
Tuning
Calibration with the team's real questions.
04
Adoption
Training and measurement of use.

Deliverables

Document	Length
Search engine in production Web or embedded in your intranet.	included
Gap report What they ask for and is not documented.	included

Note

The gap report tends to be the most valuable part. Knowing what the team asks for and cannot find reveals exactly which documentation is missing.

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All practice areas

Custom development Cybersecurity Consulting