OnyxAI Studio
AI Operations Review
Intelligence database / knowledge graph / daily discovery

QAtlas

A structured quantum industry intelligence platform built to organize companies, funding records, research, technologies, and market developments into a connected knowledge graph.

QAtlas visual system diagram

Proof depth

What this case study proves operationally.

The strongest proof is the workflow shape: what the visitor or staff member gives the system, what the business receives, and what follow-up becomes possible.

Intelligence database architecture

QAtlas separates organizations, funding records, research items, Intel posts, sources, topic pages, evergreen pages, and relationship signals into structured records instead of treating the market as a flat blog archive.

Knowledge graph structure

Company, funding, research, and Intel records link through source IDs and relationship helpers, so readers can move from a company profile to related capital events, research signals, ecosystem categories, and dated market analysis.

Daily discovery and publishing workflow

The CLI discovery workflow scans trusted sources, filters duplicates and junk pages, creates analyst prompt packets when needed, imports reviewed decisions, updates evergreen pages, and can publish source-backed Intel records when confidence and attribution gates are satisfied.

Structured SEO and market briefs

Public entity pages, topic guides, evergreen pages, schema, `llms.txt`, AI context JSON, and weekly market briefs turn the database into crawlable and answer-ready intelligence rather than a private spreadsheet.

Graph

Entity model

Daily

Workflow

Briefs

Publishing

The Challenge

Quantum industry information is fragmented across company pages, research publications, grant notices, press releases, funding announcements, and policy sources, which makes it hard to compare ecosystem signals without losing source context.

The Solution

QAtlas uses an intelligence database architecture with typed entity records, source attribution, relationship signals, daily discovery, evergreen topic pages, structured SEO, and market brief publishing workflows.

The Result

The platform gives Onyx a live proof asset for knowledge graph structure, source-backed publishing, entity pages, daily discovery operations, and market intelligence workflows that stay useful to readers and AI answer systems.

Stack and service links

The useful details stay connected.

Case studies should feed service pages, and service pages should point back to relevant proof.

Next step

Have a similar operation that needs structure?

Request an AI Operations Review