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Lobsterland vs Cognee

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

Lobsterland compared with Cognee
DetailLobsterland logo Lobsterland Cognee
What it doesHosted AI agents that do real work Open-source memory platform for AI agents
StageNot given Not given
FoundedNot given Not given
Based inNot given DE
Pricing modelPaid Not given
PricingLight $6.90/month, Medium $14.90/month, Large $29.90/month. Managed Paperclip workspace $4.90/month add-on. Managed Setup Launch service $199 one-time. All plans include 7-day free trial. Free: $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.
Key features
  • Browser chat and dashboard interface
  • Telegram, Slack, and WhatsApp integration
  • Hosted browser with persistent cookies and login state
  • Cron job scheduling and automation
  • Per-model cost tracking and usage analytics
  • Workspace editor for file and workflow management
  • Skills management from ClawHub
  • Multiple agents with separate workspaces
  • Chrome Extension support for browser control
  • 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
What makes it different
  • No servers to run or maintain
  • Full root-level capability inside isolated environment
  • Setup in about 2 minutes
  • 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
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)4 no change since last check70 no change since last check
Trust Flow (Majestic)114
Citation Flow (Majestic)3043
Referring domains (Majestic)841089

4 details filled in for both companies.

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