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Cognee vs Alexein

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Cognee compared with Alexein
Detail CogneeAlexein logo Alexein
What it doesOpen-source memory platform for AI agents Memory for AI agents and the people using them
StageNot given Not given
FoundedNot given Not given
Based inDE Not given
Pricing modelNot given Freemium
PricingFree: $0/month with 1M tokens and 1 workspace (no card required). Standard: $1.00 per 1M tokens plus $5 per additional workspace. Enterprise: contact for pricing with bring-your-own-cloud deployment. Open-source engine available free to self-host. Free: 10,000 events and 1,000 retrievals per month. Starter: $13/month for 50,000 events and 5,000 retrievals. Pro: $100/month for 500,000 events and 50,000 retrievals. Scale: $399/month for 2,500,000 events and 250,000 retrievals. Enterprise: Custom pricing.
Key features
  • Unified vector search, knowledge graphs, and relational storage
  • Automatic knowledge graph generation from data sources
  • Multi-tenant support with isolated workspaces
  • Data source integrations (Slack, Notion, Google Drive, GitHub, etc.)
  • Self-improving memory that learns from use
  • Multiple deployment options (cloud, self-hosted, air-gapped)
  • Agent framework integrations (LangGraph, CrewAI, OpenAI SDK, MCP)
  • Support for multiple vector and graph databases
  • GDPR compliance and encryption at rest and in transit
  • Built-in graph visualization of company brain
  • Search memory with dates and sources
  • Memory history and item versions
  • Data erasure with receipt
  • Correct and edit facts
  • Works with Claude, ChatGPT, Cursor and GitHub Copilot
  • Integrates with LangGraph, CrewAI and OpenAI Agents SDK
  • Connect to Slack, Notion, Linear, Jira and GitHub
  • Hosted MCP server
  • Item expiry
What makes it different
  • Combines vectors with graph relationships and generated data models for connected context retrieval
  • State of the art performance on BEAM benchmark (79% vs 73.4% at 100k tokens)
  • Keeps memory costs flat as data grows compared to baseline LLM approaches
  • Fully open-source with no database lock-in
  • Updates memory as source data changes, not just static snapshots
  • Reduces token usage while improving context accuracy
  • Privacy and data control built in, not bolted on
  • Nothing is dropped when limits are reached
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)70 no change since last check10 +7 (up) since last check
Trust Flow (Majestic)140
Citation Flow (Majestic)4312
Referring domains (Majestic)10893

4 details filled in for both companies.

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