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Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.
Free crowdsourced benchmark that pits top AI models head-to-head on design tasks and ranks them by public votes.
AI research lab building multimodal 'omni' foundation models and infrastructure aimed at robotics and physical-world applications.
Ultra-lightweight, self-hosted open-source AI assistant in Go that runs on sub-$10 hardware like Raspberry Pi with under 10MB RAM.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
- ✦Enterprise search across company apps
- ✦Personal AI assistant grounded in work data
- ✦Agent builder, orchestration and governance
- ✦250+ connectors and actions
- ✦Enterprise knowledge graph and hybrid search
- ✦Security controls for scaling AI
- ✦One-line API calls to run community and proprietary AI models
- ✦Support for image, video, speech, and LLM generation models
- ✦Fine-tuning and custom model deployment via Cog
- ✦Per-second usage billing on shared or dedicated hardware
- ✦Automatic scaling for high-traffic private models
- ✦Thousands of community-published models with production APIs
- ✦Side-by-side model output comparison
- ✦Public voting on results
- ✦Leaderboards ranking AI models by 'taste'
- ✦Coverage of websites, games, 3D, UI, images, logos, SVG, video and slides
- ✦Omni multimodal model research and development
- ✦Real-time inference API (Infer) for enterprise use
- ✦Video tagging, search, and clipping infrastructure
- ✦Training data generation from egocentric and robotics footage
- ✦Single self-contained binary requiring under 10MB RAM
- ✦Sub-1-second startup even on low-power processors
- ✦Support for 16+ chat channels including Telegram, Discord, Slack, WeCom
- ✦Compatibility with multiple LLM providers (OpenAI, Claude, DeepSeek, Gemini, etc.)
- ✦Runs on Raspberry Pi, RISC-V, ARM64, x86_64, Android, and Docker
- ✦Self-hosted design keeping data and configuration local
- ✦Gateway/API mode for connecting to chat platforms via MCP protocol
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows
- →Developers embedding image/video/speech generation into an app via API
- →Teams deploying and scaling their own fine-tuned models
- →Builders comparing outputs from multiple AI models in one playground
- →Companies avoiding GPU infrastructure management for ML inference
- →Compare which AI model produces the best design output
- →Track AI design model rankings
- →Discover models for a specific creative task
- →Powering robotics perception with multimodal AI
- →Running large-scale video search and analysis via API
- →Sourcing specialized training data for frontier AI models
- →Running a private AI assistant on minimal or embedded hardware
- →Local code assistance that keeps proprietary code off the cloud
- →Home automation and personal task scheduling via chat bots
- →Privacy-conscious users wanting self-hosted AI on low-cost devices