Open source H2O platform for distributed machine learning, exposing AutoML, GLM, GBM and deep learning through Flow, Python and R interfaces. Built and maintained by WIEWAVE for Azure Marketplace, AWS Marketplace and Google Cloud Marketplace, on Ubuntu, Debian, Red Hat Enterprise Linux, AlmaLinux and Rocky Linux.
| Built & maintained by | WIEWAVE |
|---|---|
| Category | AI & Machine Learning |
| Operating systems | Ubuntu, Debian, Red Hat Enterprise Linux, AlmaLinux, Rocky Linux |
| Marketplaces | Azure Marketplace, AWS Marketplace and Google Cloud Marketplace |
| Offer types | Public listing, with private offers on request |
| Marketplace | Status |
|---|---|
| Azure Marketplace | Published |
| AWS Marketplace | Published |
| Google Cloud Marketplace | Published |
Need it on another marketplace, or as a private offer for your organisation? cloud@wiewave.com
Each image follows its distribution's own provisioning model, package manager and security tooling — not one build relabelled several times.
LTS and interim releases, Minimal and Pro variants, built to Canonical's cloud-image conventions.
Stable and oldstable, with backports where a workload needs a newer runtime than the release ships.
RHEL 8 and 9 images, including BYOS and pay-as-you-go licensing models on each marketplace.
The 1:1 RHEL-compatible rebuild, and the default landing spot for teams migrating off CentOS Linux.
Enterprise-grade RHEL compatibility with a community governance model, on 8 and 9 streams.
The same four steps behind every offer we've published, including the hardening and CIS Benchmark checks every build goes through.
The distribution, licensing model and target marketplaces are agreed before anything is built.
Packer templates, Ansible provisioning and a pinned package set — then hardened, scanned and checked against the CIS Benchmark for its distribution.
Taken through each cloud's own certification pipeline before it goes live on the marketplace.
Rebuilt on the upstream security cadence and re-published, with old versions retired without breaking deployments.
If yours isn't here, ask our marketplace team directly.
GPU-ready training and inference images with drivers, CUDA and frameworks already matched to each other.
Open source framework from deepset for building retrieval-augmented generation and search pipelines, connecting document stores, embedders, retrievers and LLM providers.
Environment preloaded with Transformers, Datasets and Tokenizers plus PyTorch, ready for fine-tuning and serving natural language models pulled from the Hub.
Text Generation Inference with tensor parallelism and continuous batching configured for GPU serving at real concurrency.
Platform for natural language data work, letting teams cluster, label and curate conversational utterances into intents and training sets for NLU models.
Python library for hyperparameter search using random, TPE and adaptive algorithms, installed alongside SciPy and a Jupyter environment for distributed trials.
Tooling and SDK access for Google's Imagen text-to-image models, covering image generation, editing, upscaling and captioning through Vertex AI endpoints.
Tell us the distribution, the marketplace and the commercial model — we'll build, certify and publish it as a public listing or a private offer.
