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Cognee vs Axtary

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 Axtary
Detail CogneeAxtary logo Axtary
What it doesOpen-source memory platform for AI agents Content authorization for AI agents
StageNot given Not given
FoundedNot given Not given
Based inDE Not given
Pricing modelNot given Not given
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. Local: free with CLI, SDK, local proxy, and MCP wrapper. Founding Team: $499 per month after a 30-day pilot, including guided setup, hosted approvals, team dashboard, verified ledger sync, and direct support.
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
  • Exact payload binding and hash verification
  • Policy engine with Cedar and Rego support
  • Local enforcement proxy and CLI
  • Hosted approvals dashboard and team coordination
  • Verifiable action ledger with audit trail
  • Model Context Protocol wrapper
  • Support for GitHub, Slack, Linear, Jira and cloud platforms
  • Runtime integration with Anthropic, OpenAI and Cursor
  • Credential-free playground and examples
  • ActionPass signed authorization artifact
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
  • Payload approval bound to exact hash, not summary—changes after approval are automatically rejected
  • Local enforcement with credential-free operation before team coordination layer
  • 30-day pilot model with no long-term commitment required
  • Open-source ActionPass artifact and verifier for transparency
  • Adapter-side verification prevents tool execution after payload tampering
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 check1 no change since last check
Trust Flow (Majestic)140
Citation Flow (Majestic)4328
Referring domains (Majestic)108961

4 details filled in for both companies.

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