Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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ChaptersAI
Paid
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supermemory™
✓ verifiedFreemium
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
174K visits/mo
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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
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CopilotKit
✓ verifiedFreemium
Open-source React/Angular SDK and platform for embedding agentic, generative-UI copilots into apps, Slack and Teams.
170K visits/mo
Pricing
Subscription: $9/mo
ChaptersAI: $49/year
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
Developer: $0 (1 seat, free forever, 200 threads)
Pro: $39/developer/mo (up to 5 seats, 5,000 threads)
Team: $500/mo (5 seats, 25,000 threads)
Core features
- ✦Branching chat windows for detailed analysis
- ✦Version control for branched chats
- ✦Local storage for privacy and security
- ✦System Message editing
- ✦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
- ✦React and Angular frontend SDKs
- ✦Agent-rendered generative UI
- ✦AG-UI agent-user interaction protocol
- ✦Connectors for LangChain and other frameworks
- ✦Pre-built customizable chat/sidebar components
- ✦Slack and Teams integrations
- ✦Thread and state persistence
Use cases
- →Building large projects with GPT
- →Drilling down into component parts of a project
- →Experimenting with different versions of a chat
- →Writing stories with reader data insights
- →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
- →Adding an AI assistant to a SaaS product
- →Building agents that render interactive UI
- →Deploying copilots across Slack and Teams
- →Connecting existing agents to a frontend
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