Now accepting early access applications

Your AI didn't fail.
Your knowledge structure did.

Diagnose why Copilot and internal AI can't deliver value — without reading your documents. We analyze structure & governance signals (metadata only) to produce an executive-ready report.

No content access
One-time diagnostic
72-hour auto deletion
Executive-ready PDF

Why AI rollouts stall in real companies

It's not the AI. It's the foundation it's built on.

Inconsistent answers

"RAG pulls the wrong source. Users stop trusting it."

Knowledge decay

"Critical SOPs are outdated or duplicated across teams."

Governance gaps

"No ownership, messy permissions, unclear lifecycle."

Simple Process

A diagnostic, not another tool to manage

Three steps to understand what's blocking your AI initiatives.

01

Export metadata

Export or generate metadata (CSV) from your knowledge systems (Notion / Confluence / Google Drive).

02

We analyze structure

We run a structure analysis (topology, ownership, lifecycle, permission risk).

03

Receive your report

You receive a report: AI Readiness Score + root causes + 90-day remediation plan.

Deliverables

Sample diagnostic preview

Excerpt from a full executive-ready diagnostic report.
The complete sample is available below.

AI Knowledge Readiness Score (0–100)

Top 3 structural blockers to AI adoption

Governance gaps (ownership & lifecycle)

Permission risk map (where AI should not access)

ROI estimate: time & cost leakage from knowledge chaos

A 90-day remediation checklist (works with your existing tools)

sample_report.pdf

📊 Sample Diagnostic Findings

Orphaned docs

43%

No clear owner

58%

Outdated SOP risk

High

External share risk

Medium

AI Readiness Score34/100

Is this right for you?

Atlas Diagnostic is designed for specific challenges. Here's how to know if it's a fit.

Perfect for

  • Teams already using Copilot/ChatGPT Enterprise/RAG and not seeing ROI
  • 30–500 employee companies with growing documentation sprawl
  • Ops / CTO / Knowledge owners who need a clear diagnosis

Not designed for

  • Personal "second brain" workflows
  • Teams just experimenting with AI casually
  • Companies unwilling to export metadata
Security First

Built for security-first teams

We understand that enterprise data is sensitive. That's why we designed Atlas Diagnostic from the ground up with security as a core principle—not an afterthought.

Zero document content access

Metadata only

We do not read or store document content. Metadata only.

Encrypted in transit

Data is encrypted in transit using industry-standard TLS.

Auto-delete

Uploaded files auto-delete within 72 hours.

No model training

We do not train models on your data. Ever.

Data Boundaries

Exactly what we access — and what we never do

Atlas Diagnostic is designed with strict data boundaries so security teams know precisely how information is handled.

What we analyze (metadata only)

We only access non-content metadata required to understand knowledge structure, including:

  • Document or page ID
  • Folder or workspace hierarchy
  • Parent–child relationships
  • File or page type (doc, page, PDF, etc.)
  • Creation and last-updated timestamps
  • Owner and last editor identifiers
  • Permission scope (private / team / organization / external)
  • Source system (Notion, Confluence, Google Drive, SharePoint)

✓ We do NOT access document text, paragraphs, comments, or attachments.

What we never access

Atlas Diagnostic will never:

  • Read document body content
  • Extract or store document text
  • Generate embeddings or vector indexes
  • Copy or back up customer documents
  • Monitor your workspace continuously
  • Sync data after the diagnostic completes
  • Train AI models using customer data
  • Retain data beyond the diagnostic window

How AI is used

AI is used only to summarize diagnostic findings generated by deterministic analysis.

  • AI does not process uploaded metadata directly
  • AI does not read customer files
  • AI never receives document content
  • AI is applied only to aggregated structural metrics

Data lifecycle

  • Metadata files are uploaded using encrypted transport (TLS)
  • Files are stored temporarily for diagnostic processing
  • All uploaded data is automatically deleted within 72 hours
  • No backups or replicas are retained
  • Data deletion is irreversible

Apply for early diagnostic access

Limited spots available. We'll review applications and reach out to qualified teams.

Basic information

Tell us a bit about your role and organization.

Your environment

Where is your team's knowledge primarily stored?

Current challenges

This helps us understand where AI adoption is breaking down.

Application information is stored securely for internal review and communication purposes only.

Diagnostic data (such as uploaded metadata files) is processed separately and is never stored in our internal systems. All diagnostic data is automatically deleted within 72 hours.

Frequently asked questions

Have another question? Reach out to us directly.