Runs Docling behind an HTTP API, exposing document conversion endpoints and an OpenAPI schema so other services can submit files for parsing. Built and maintained by WIEWAVE for Azure Marketplace, on Ubuntu and Debian.
| Built & maintained by | WIEWAVE |
|---|---|
| Category | AI & Machine Learning |
| Operating systems | Ubuntu, Debian |
| Marketplaces | Azure Marketplace |
| Offer types | Public listing, with private offers on request |
| Marketplace | Status |
|---|---|
| Azure Marketplace | Published |
| AWS Marketplace | Available on request |
| Google Cloud Marketplace | Available on request |
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.
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.
Fine-tuning setup for diffusion models that teaches a subject from a handful of images, with PyTorch, CUDA and training scripts preinstalled.
Optical character recognition library covering more than eighty languages, packaged with PyTorch, detection and recognition models, and a short Python API.
Python library for readable tensor reshaping, reduction and repetition across NumPy, PyTorch and TensorFlow, installed in a prepared data science environment.
Transformer model pretrained with replaced-token detection, provided with Hugging Face Transformers for fine-tuning on classification and question answering tasks.
AI & Machine LearningEnvironment for EleutherAI open models such as GPT-Neo, GPT-J and Pythia, with Transformers, PyTorch and CUDA libraries ready for inference.
Python package that explains machine learning classifiers by showing feature weights and per-prediction breakdowns for scikit-learn, XGBoost and text pipelines.
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.
