Knowledge Unification

Bringing all your knowledge into one searchable system

The Core Challenge

Your knowledge lives in silos:

• Twitter bookmarks you can't search effectively

• Apple Notes buried in folders

• Browser bookmarks with broken links

• Notion databases you forgot existed

• ChatGPT conversations that vanished

ATLAS unifies everything into a single, searchable knowledge graph.

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Supported Data Sources

Currently Available

Source	What's Captured
Twitter/X Bookmarks	Tweets, threads, linked articles, images
Apple Notes	Full note content, attachments, folders
GitHub Stars	Repository metadata, READMEs, topics
LLM Conversations	ChatGPT, Claude exports with full context
Voice Memos	Transcribed audio with AI extraction
Readwise	Highlights, annotations, and notes
Obsidian Vaults	Markdown notes with full link structure

Coming Soon

• Kindle Highlights

• Pocket/Instapaper

• Notion Exports

• YouTube Watch Later

• Podcast Notes

• Telegram Groups (Alpha agent integration)

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The 5-Stage Pipeline

Every data source goes through ATLAS's standardized ingestion pipeline:

Stage 1: Acquire

Fetch raw data from the source

Connect to APIs, import files, or process exports. ATLAS handles authentication, rate limiting, and data retrieval automatically.

Stage 2: Prepare

Normalize into consistent format

Different sources have different structures. A tweet looks nothing like an Apple Note. This stage standardizes everything into a common schema.

Stage 3: Process

Extract intelligence with AI

This is where the magic happens. LLMs analyze each piece of content to extract:

• Key concepts

• Actionable insights

• Important quotes

• Mental frameworks

• Importance scores

Stage 4: Parse

Structure into graph nodes

Extracted intelligence becomes nodes in your knowledge graph. Concepts link to content, insights link to concepts, everything connects.

Stage 5: Render

Ready for search and visualization

Final processing for full-text search indexing, graph visualization, and API exposure.

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What Gets Unified

Content Items

The original sources — tweets, notes, documents, conversations.

Concepts

Key ideas extracted from your content. Each concept has:

• Name and description

• Importance score (0.0 - 1.0)

• Source references

• Related concepts

• Associated insights

Insights

Actionable learnings and observations. Things you should remember and act upon.

Actions

Tasks, research threads, ideas to explore. Your knowledge becomes a to-do list.

Relationships

Connections between everything. Concept A relates to Concept B. Content X contains Concept Y.

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The Unified Experience

Before ATLAS

"I know I read something about this..."
→ Search Twitter (nothing)
→ Search Notes (nothing)
→ Search bookmarks (nothing)
→ Google it again
→ Start from scratch

After ATLAS

"I know I read something about this..."
→ Search ATLAS
→ Find original content + extracted concepts + related insights
→ See connections to other things you've saved
→ Build on existing knowledge

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Key Benefits

🔍 Universal Search

One search box. Everything you've ever saved. Full-text search with semantic understanding.

🧠 Automatic Organization

No manual tagging or filing. ATLAS understands your content and organizes it automatically.

🔗 Connection Discovery

See relationships between ideas from different sources. Your Twitter bookmark connects to your Apple Note connects to your ChatGPT conversation.

📈 Growing Intelligence

Every new piece of content enriches existing knowledge. Your graph gets smarter over time.

💾 Data Ownership

Your unified knowledge lives in a SQLite database you control. Export anytime. No vendor lock-in.

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Technical Foundation

ATLAS uses a hybrid storage architecture:

• SQLite — Portable, reliable, local-first database

• FTS5 — Full-text search with relevance ranking

• Graph Schema — Nodes and edges for relationship traversal

• Vector Embeddings — Semantic similarity (coming soon)

All running locally. All under your control.