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A Japanese AI firm that grew from shogi-AI research into industry ML solutions and a generative-AI platform, HEROZ ASK.
AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.
Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.
Enterprise unified API gateway giving one integration point to 100+ LLMs like Claude, GPT, and Gemini with reliability guarantees.
Cloud platform to run open-source AI apps like ComfyUI and Stable Diffusion and train LoRAs on rented GPUs, billed hourly.
No public pricing
No public pricing
Free trial available
- ✦Deep-learning and machine-learning core technology
- ✦HEROZ ASK generative-AI platform
- ✦BtoB and BtoC AI solutions
- ✦BLOOMWORKS product
- ✦Industry AI deployment case studies
- ✦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%
- ✦On-demand GPU pods across 30+ GPU types and 31 regions
- ✦Serverless GPU endpoints with sub-200ms cold starts
- ✦Zero idle cost billing for inference workloads
- ✦Multi-node clusters for distributed training
- ✦Persistent network storage for full pipelines
- ✦Real-time logs, monitoring and autoscaling from 0 to hundreds of workers
- ✦Unified API for 100+ AI models
- ✦Intelligent request routing across models
- ✦AI Model Insurance for quality/reliability guarantees
- ✦Enterprise-focused LLM access layer
- ✦Pre-installed open-source AI apps (ComfyUI, SD, Fooocus)
- ✦LoRA and custom model training
- ✦Image, video, audio, and LLM workflows
- ✦Hourly GPU rental across several tiers
- ✦Private storage and shareable workflows
- ✦No-deployment, browser-based access
- →Deploying generative AI in enterprises
- →Applying ML to industry-specific problems
- →AI-driven business transformation (DX)
- →Train large AI/ML models on GPU clusters
- →Run scalable inference workloads
- →Store and manage large training datasets
- →Run Slurm/Kubernetes AI pipelines
- →Renting GPUs for model training and fine-tuning
- →Deploying low-latency real-time inference APIs
- →Running AI agents that need to scale instantly
- →Processing compute-heavy batch or distributed workloads
- →Building applications that need failover across multiple LLM providers
- →Consolidating billing/access to many AI models under one API
- →Enterprises requiring guaranteed model output reliability
- →Running ComfyUI/Stable Diffusion without a local GPU
- →Training custom LoRA models
- →Face swapping and voice conversion
- →Generating images, video, and audio at scale