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Open-source RAG infrastructure with SDKs and an API for developers to build accurate, cited AI chat and search on their own data.
AI social-listening and customer-feedback platform that tracks brand mentions, creators, and sentiment across video-first social platforms.
AI knowledge-management app oriented toward ADHD users.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
High-performance open-source vector database for production AI retrieval and RAG, for teams needing scale, hybrid search, or self-hosting.
No public pricing
No public pricing
No public pricing
- ✦Managed RAG pipeline (extraction, chunking, retrieval)
- ✦Automatic source citations
- ✦Multimodal support (images, tables, graphs)
- ✦Model-agnostic: choose vector DB, embeddings, LLM
- ✦Metadata filtering
- ✦MCP server and AI SDK integration
- ✦22+ file-format ingestion
- ✦Cross-platform social listening including video (TikTok, Reels, Shorts)
- ✦Competitive analysis of rival brands' content and creators
- ✦Speech-to-text and AI vision analysis of video content
- ✦Plain-language query interface for filtering data
- ✦Creator discovery and campaign tracking
- ✦Centralized customer feedback intake with AI tagging and sentiment
- ✦MCP connector for using data inside Claude/ChatGPT workflows
- ✦AI-powered note-taking and organization
- ✦Smart inbox for managing new notes
- ✦Tag suggestions using AI
- ✦Relevant note suggestions
- ✦AI writing assistance
- ✦Task management
- ✦Integration with other apps
- ✦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
- ✦Hybrid dense and sparse vector search (BM25, SPLADE, miniCOIL)
- ✦Advanced metadata filtering applied during search traversal
- ✦Multivector support for multimodal retrieval
- ✦Reranking with score boosting and late-interaction models (ColBERT, MMR)
- ✦Flexible deployment: cloud, hybrid, private, or edge
- ✦Rust-based engine optimized for low-latency, high-scale search
- →Build a chatbot over private documents
- →Add semantic or deep search to an app
- →Ground answers in a large corpus with citations
- →Ship production RAG without building it in-house
- →Consumer brands monitoring sentiment and share of voice on social video
- →Marketing teams finding and vetting influencer partners
- →CX teams unifying feedback from tickets, chat, surveys and reviews
- →Learning new knowledge
- →Brainstorming new ideas
- →Summarizing meeting notes
- →Creating newsletters
- →Synthesizing training documents
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Building retrieval-augmented generation (RAG) pipelines
- →Powering AI recommendation and semantic search systems
- →Enterprises needing on-prem or hybrid deployment for compliance
- →AI agent platforms needing fast contextual retrieval at scale