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Cognee vs Lanes

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 Lanes
Detail CogneeLanes logo Lanes
What it doesOpen-source memory platform for AI agents Run your agentic fleet at scale
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: $0 per month for 1 user. Pro: $19/month for up to 10 members. 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
  • Run multiple coding agents in parallel on separate git worktrees and branches
  • Task board with live terminals for each agent session
  • Access Profiles to control permissions for each agent
  • Integration with 100+ providers
  • Audit logs of all agent actions and refusals
  • Self-hostable access layer
  • On-demand GPU compute by the second
  • Local-first execution keeping source code and output on user's machine
  • Support for Claude Code, Codex, and other agentic clients
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
  • Open-source access layer under Apache-2.0 so you can read the security model
  • Enforce access permissions at the system level, not through prompts
  • Centralized access control across all agents and platforms simultaneously
  • Keep data portable with plain files on your own disk, no vendor lock-in
  • Complete audit visibility of what every agent accessed and was denied
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 check7 no change since last check
Trust Flow (Majestic)146
Citation Flow (Majestic)4339
Referring domains (Majestic)1089192

4 details filled in for both companies.

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