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Enterprise AI Knowledge FoundationYour knowledge, AI-ready.

TensorLot turns scattered enterprise documents into a trustworthy foundation for AI — so retrieval, assistants and agents work faster, more precisely and up to 70% cheaper. On any model.

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See how it works ↓

the problemAI is only as good as what it reads.

Most enterprises sit on millions of documents: five versions of the same procedure, copies in forgotten sites, 2019 files that still rank first. Point an assistant or an agent at that and it answers with confidence — from the wrong file.

“Poor data quality is the #1 obstacle in GenAI projects.”

Gartner, 2025

Cleaning the data is not a side project. It is the foundation everything else stands on.

the winsFaster. More precise. Cheaper AI.

Clean data is not a nice-to-have. It is what makes every model, assistant and agent on top of it perform — measurably.

Cheaper

−70% fewer tokens per answer

Curated, deduplicated context instead of raw document dumps — fewer tokens, fewer retries, lower bills on any model.

Observed in TensorLot pilot deployments, 2026.
More precise

Cited every answer, every source

Answers point to the canonical version. Contradictions, duplicates and outdated copies are flagged before any model reads them.

Faster

10 s instead of a morning of searching

People ask Tensor Bot, agents call one MCP endpoint — and get the right document, not five versions of it. Connect an agent in minutes, not sprints.

how it worksFrom scattered files to AI-ready knowledge.

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Connect

Connect your sources

  • SharePoint, Confluence, Jira, GitHub
  • Read-only, permission-aware
  • Incremental sync — no migration
Analyse

Score every document

  • Quality score per document
  • Contradictions across sources
  • Outdated & duplicate detection
Clean

Fix what’s broken

  • Guided remediation
  • Canonical version marked
  • Rules per site, library or URL
Serve

Answer people and agents

  • Cited answers via Tensor Bot
  • One MCP endpoint for agents
  • Every call audit-logged
11governed tools · 1 endpoint

what you getOne foundation. Three outcomes.

01 · Foundation
A trustworthy foundation for AI

Deduplicated, contradiction-checked, quality-scored — the layer every assistant and agent should read from.

02 · Retrieval
Reliable, scalable retrieval

Cited answers with confidence, on any model. Knowledge management that finally works — because the data underneath is clean.

03 · Agents
Agents that act correctly

One MCP endpoint: scoped, governed, audit-logged. Copilot Studio, Claude or any framework — up to 70% fewer tokens per answer.

the productSee every problem. Fix it.

TensorLot Core reads your documents the way an auditor would — and shows you the verdict in one console.

TensorLot Console · Document Healthtenant / all site collections / dashboard
TensorLot console — Document Health dashboard: overall health score 82/100 with score history, and the document list with per-document health, findings and last scan

One health score for the whole tenant (82/100, +34 points since March) — and per document: format, site, library, health, open findings, last scan. Before any AI reads it.

what trust looks likeEvidence, not promises.

Cited answer

“Two approved suppliers are under contract for this component.”

  • supplier-contracts-2026.pdf · p. 4
  • vendor-list-q2.xlsx · row 18
2 sources
Quality score

onboarding-guide-v3.docx

  • Last updated 2023 · owner left the company
0.31 · outdated
Contradiction

Data-retention period

  • Policy v4: 7 years
  • QMS copy: 10 years
canonical: v4
Audit log

procurement-bot · ask

  • 09:41:07 · tenant acme-group
  • scope: supplier-docs · 3 tool calls
okdry-run

agnostic by designAny source. Any model. Any agent.

TensorLot is the layer in between — not another silo. Your sources stay where they are; your models and agent frameworks stay your choice.

/ SharePoint · Confluence · Jira · GitHub · Microsoft 365 · Azure  
/ Copilot Studio · Claude · OpenAI · Azure OpenAI · LangGraph · any MCP client  

next stepReady for a trustworthy foundation?

See your own SharePoint answered with citations — and what your agents would read — in a 30-minute demo.

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