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Company knowledge for AI

Answers from your company knowledge.
One update. Every answer current.

Every assistant and automation works from the same current knowledge: handbooks, policies, product documentation and websites. Each answer links to the passage it came from, so your team can check it in one click. Nobody keeps a stale copy in a private prompt.

Company knowledge · RAG · Semantic search · Source citations · OCR · Web crawl · Live sync

See knowledge in use
Animated demo · sample data
Procurement Assistant

Ask for a purchase in the ERP

Grounding

Assistants follow your rules.

Before drafting an order, answering a ticket or choosing a supplier, the assistant reads the same policies, processes and wiki pages your team would open.

Company policies and how-tos
The process rules your team already wrote
The same rules for every assistant and automation
Source citations

Check any answer in one click.

Every answer points to the document, page or ticket it came from, so nobody has to take it on faith.

Source citations
Every answer links back to where it came from
Live sync

No stale copies.

Update the source document, and every assistant and automation uses the new version. No old copy survives in a forgotten prompt.

One update, current for every assistant
No private copies in prompts
Knowledge + business data

The policy and the case in one answer.

A policy explains the process. A record describes the specific case. The assistant uses both, for example the refund policy together with this customer's order history.

Refund policy from the handbook
Order history from the ERP
An answer that applies both
How it works

From a pile of documents to reliable answers

You supply the material. Taibles handles everything between a raw file and an answer with sources.

01
Sources

Bring in what your team already wrote.

Upload documents and spreadsheets in bulk, let Taibles follow the links of a website, or import your HubSpot pages. Scanned paperwork is read too, so the old PDFs on the shared drive count.

Upload files in bulk
Scan a website by following its links
Import HubSpot pages
Text recognition for scans and images
02
Document preparation

Tables stay tables. Headings stay with their sections.

Each file is read with its layout, not flattened into plain text. Documents are split along their real sections, so every passage still makes sense when it comes back in an answer.

Layout understood, not flattened
Tables kept as tables
Split at headings and sections
Each passage gets a title, summary and tags
03
Retrieval / RAG

Ask in your own words.

Questions are matched by meaning, so people ask the way they would ask a colleague. Test a few questions before rollout, then give the collection to an assistant or use it in any automation step.

Finds the passage even when the wording differsSemantic search
Narrow by tag, section or sourceFilters
Test questions before rolloutBuilt in