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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.

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
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
FluidStack logo
FluidStack
✓ verifiedPaid

Infrastructure company building large-scale GPU data centers and compute for AI, including Anthropic's compute buildout.

101K visits/mo
Gumloop logo
Gumloop
✓ verifiedFreemium

No-code platform for building and running AI agents that automate work across data, sales and support tasks.

701K visits/mo
Pricing

No public 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

Pro: $37/month (20k+ credits/month, unlimited seats)
Core features
  • 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
  • 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
  • Large-scale GPU and data-center infrastructure for AI
  • Power acquisition and data-center design/build
  • Fast deployment (gigawatts in ~6 months)
  • Operates both hardware and software stack
  • Visual canvas to orchestrate multi-agent workflows
  • Prebuilt specialized agents (data, support, CRM, sales)
  • Access to many AI models with no vendor lock-in
  • Slack, Teams and email agent interaction
  • Recurring/scheduled tasks and triggers
  • Enterprise security: RBAC, VPC, audit logs, spend controls
Use cases
  • Privately querying your own documents
  • Running local AI without the cloud
  • Building AI agents over your data
  • Using multiple LLM providers in one app
  • 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
  • Training and running large AI models at scale
  • Provisioning GPU compute for AI labs
  • Building dedicated AI data-center capacity
  • Automate data analysis and reporting
  • Triage support tickets and spot patterns
  • Keep a CRM updated and research prospects
  • Deploy AI agents across a team's tools
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