Your Company's Collective Intelligence.
Ground every assistant and automation in the same current company knowledge, not private prompts and stale copies. Connect documents, websites, and databases once so every workflow uses the exact same approved rules.
OCR 路 Semantic search 路 Live sync 路 Web crawl
Ground assistants in your rules
Before it drafts an order, answers a ticket, or chooses a supplier, Taibles can read the same policy rules, processes, and internal wiki your team would open.
Shows the source behind every answer
Every answer points back to the document, page, or ticket it came from, so you can check it in one click instead of taking it on faith.
Change the policy once. The next answer uses it.
Update the source document and every assistant or workflow immediately uses the new version, leaving no stale copy inside an old prompt.
From a pile of documents to answers
You supply the material. Taibles takes care of everything between a raw file and a reliable, sourced answer.
- 1Sources
Bring in what your team already wrote
Drop in documents and spreadsheets, point Taibles at a website and let it follow the links itself, or import your HubSpot blog and pages. Scanned paperwork is read too, so the old PDFs in the shared drive still count.
Upload files, in bulkScan a website, following its own linksImport your HubSpot blog and pagesText recognition for scans and images - 2Document preparation
The hard part of RAG, handled for you
This is where most in-house attempts quietly fail. Every file is read with its layout understood instead of scraped as flat text, so a table arrives as a table and each heading stays attached to the section under it. Taibles then splits documents along those real section boundaries rather than every few thousand characters, so a passage still makes sense on its own when it comes back.
Layout understood, not flattened to plain textTables kept as tablesSplit on headings and sections, never a blind character countEach passage gets its own title, summary and tags - 3Retrieval / RAG
Let people ask in their own words
Questions are matched by meaning, so people can ask the way they would ask a colleague rather than guessing the right keyword. Try a few queries yourself first, and when the answers hold up, hand the collection to an assistant or search it from any automation step.
Finds the passage even when the wording differsMatched by meaningNarrow by tag, section or sourceFiltersTry queries before you roll it outBuilt inUsed by assistants and automations alikeShared