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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.
AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.
Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.
Open-source desktop app for running AI chat models locally or via APIs, as a private ChatGPT alternative.
No public pricing
Free trial available
Free trial available
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
- ✦NVIDIA GPU instances (H100, H200, B200, GB200)
- ✦On-demand and preemptible GPU pricing
- ✦High-performance and object storage
- ✦Managed Kubernetes and Slurm (Soperator)
- ✦Serverless and managed inference (Token Factory)
- ✦MLOps tooling and 24/7 expert support
- ✦Commitment discounts up to 35%
- ✦Switch across 300+ hosted and local AI models
- ✦Native macOS app with global shortcut and screenshot-to-answer
- ✦Reusable agents, projects, and forked chats
- ✦Multimodal analysis of PDFs, images, and code
- ✦MCP tools and code execution
- ✦Local chat storage with encryptable API keys
- ✦Run open-source LLMs locally
- ✦Connect to online models (OpenAI, Claude, Gemini)
- ✦Private, offline-capable AI chat
- ✦Open source and self-hostable
- ✦Model library via Hugging Face
- ✦Cross-platform desktop app
- →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
- →Train large AI/ML models on GPU clusters
- →Run scalable inference workloads
- →Store and manage large training datasets
- →Run Slurm/Kubernetes AI pipelines
- →Using multiple AI providers in one place
- →Explaining or fixing on-screen content instantly
- →Building reusable task-specific agents
- →Analyzing documents and screenshots privately
- →Private local AI chat
- →Using multiple models in one app
- →Avoiding cloud data sharing
- →Experimenting with open models