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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

supermemory™ logo
supermemory™
✓ verifiedFreemium

Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.

174K visits/mo
AnythingLLM logo
AnythingLLM
✓ verifiedFree

Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.

682K visits/mo
248K visits/mo4.8K saves
Autonoma logo
Autonoma
✓ verifiedFreemium

Open-source testing platform where AI agents drive your app end-to-end to catch regressions on every PR, no test code needed.

72K visits/mo9.3K saves
Pricing
Free: $0/mo (~$5/mo of usage included)
Pro: $19/mo (~$20/mo of usage, unlimited storage, 2 teammates)
Max: $100/mo (~$130/mo of usage, 6x Pro headroom)
Scale: $399/mo (~$600/mo of usage, up to 10 teammates)

No public pricing

No public pricing

Free & pay-as-you-go: $0 to start (100K credits free, then $100 per 150K credits)
Self-hosted: $0 (free forever, unlimited)
Core features
  • Persistent, structured memory built as a knowledge graph
  • Sub-300ms hybrid retrieval (RAG) with reranking
  • Native filesystem mount for agent memory access
  • Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
  • Automatic extraction from PDFs, images, and audio
  • User profile and behavior tracking across sessions
  • Chat with your documents (RAG)
  • Runs locally and offline for privacy
  • Supports any LLM (local or cloud)
  • Built-in AI agents
  • Handles PDFs, Word, CSV, codebases
  • No-code setup
  • Lifelike voice AI agents
  • 24/7 availability
  • Customer-led conversational platform
  • Integration with enterprise systems
  • AI agents navigate your app in real browsers
  • One-command setup that maps flows and drafts tests
  • SDK to seed and tear down real data
  • Runs on every PR against preview deploys
  • No test code required
  • Open-source with a self-hosted option
  • Integrates with GitHub, Vercel and Linear
Use cases
  • Developers adding long-term memory to AI agents
  • Teams building agents that need to sync with existing tools
  • Individuals wanting one memory layer shared across multiple AI assistants
  • Privately querying your own documents
  • Running local AI without the cloud
  • Building AI agents over your data
  • Using multiple LLM providers in one app
  • Answering customer service calls
  • Providing information and support
  • Resolving customer issues
  • Automating call center operations
  • Catching regressions before merging PRs
  • End-to-end testing without writing scripts
  • QA for fast-shipping product teams
  • Self-hosted testing on your own infrastructure
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