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AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.
Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
Free crowdsourced benchmark that pits top AI models head-to-head on design tasks and ranks them by public votes.
Ultra-lightweight, self-hosted open-source AI assistant in Go that runs on sub-$10 hardware like Raspberry Pi with under 10MB RAM.
A Japanese AI firm that grew from shogi-AI research into industry ML solutions and a generative-AI platform, HEROZ ASK.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦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%
- ✦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
- ✦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
- ✦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
- ✦Deep-learning and machine-learning core technology
- ✦HEROZ ASK generative-AI platform
- ✦BtoB and BtoC AI solutions
- ✦BLOOMWORKS product
- ✦Industry AI deployment case studies
- →Train large AI/ML models on GPU clusters
- →Run scalable inference workloads
- →Store and manage large training datasets
- →Run Slurm/Kubernetes AI pipelines
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows
- →Compare which AI model produces the best design output
- →Track AI design model rankings
- →Discover models for a specific creative task
- →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
- →Deploying generative AI in enterprises
- →Applying ML to industry-specific problems
- →AI-driven business transformation (DX)