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Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
Creative AI infrastructure giving studios access to 500+ image, video, 3D, and audio models plus custom brand-trained models.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
Voice-AI platform offering real-time text-to-speech, speech-to-text and voice-agent models through one API.
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
- ✦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
- ✦Custom LoRA model training from 5-100 reference images
- ✦Access to 500+ models across 50+ providers
- ✦Visual workflow builder for multi-step generation pipelines
- ✦API-first and MCP-ready for agent integration
- ✦Batch generation at scale with reusable templates
- ✦One-click shareable apps built from workflows
- ✦SOC 2 Type II compliance and SSO
- ✦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
- ✦Sonic real-time text-to-speech
- ✦Ink speech-to-text
- ✦Line voice agents
- ✦Low-latency real-time output
- ✦Voice cloning
- ✦Single multilingual API
- ✦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
- →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
- →Generating on-brand creative assets at scale
- →Building custom AI-powered creative workflows and apps
- →Comparing outputs across many AI models in one workspace
- →Automating batch content production for teams
- →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 voice agents
- →Text-to-speech and transcription apps
- →Fraud-detection verification calls
- →Real-time customer support voice
- →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