> ## Documentation Index
> Fetch the complete documentation index at: https://docs.matproof.com/llms.txt
> Use this file to discover all available pages before exploring further.
# AI Providers (Anthropic, OpenAI, Hugging Face, W&B)
> Connect AI provider credentials so Matproof can produce automated EU AI Act and ISO 42001 evidence against your AI training and inference infrastructure.
# AI Providers
Matproof's AI integrations capture evidence about the AI systems your organization develops or deploys — for the EU AI Act, ISO 42001, and the AI-related parts of NIS 2 and DORA. These integrations differ from cloud or identity integrations: they don't continuously sync data into Matproof. Instead, you store credentials with read-only scopes, and Matproof's [AI Systems inventory](/frameworks/eu-ai-act) module runs targeted checks against your AI infrastructure when you trigger them or on a schedule.
## What's available
| Provider | Use case | Evidence produced |
| -------------------- | -------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| **Anthropic** | Claude API usage tracking | Model versions in production, usage logs, content-filter configuration, system-prompt inventory |
| **OpenAI** | GPT API usage tracking | Same as Anthropic — model versions, usage logs, fine-tune lineage |
| **Hugging Face** | Open-source model registry, dataset cards, fine-tuning history | Model cards (Article 53 GPAI documentation), dataset provenance, training-data lineage |
| **Weights & Biases** | ML experiment tracking | Training runs, hyperparameters, evaluation metrics, model artefacts — for technical-documentation evidence under EU AI Act Annex IV |
## Why these matter for the EU AI Act
The EU AI Act expects providers and deployers of high-risk AI systems to produce specific technical documentation (Article 11, Annex IV) and post-market monitoring evidence (Article 72). Without these integrations, you'd produce that evidence by hand — exporting screenshots from each provider, pasting CSVs of training runs into spreadsheets, manually tracking model versions through deployment cycles.
Matproof's AI integrations populate the [Foundation Model Cards](/frameworks/eu-ai-act) and AI System Inventory directly from the provider, so your evidence stays current as your models change.
## Connecting an AI provider
The connection flow is identical across providers. Each requires only a read-only API key (no OAuth flow — these providers don't offer OAuth for org-level reads).
| Provider | Where |
| ---------------- | ---------------------------------------------------------------------------------------- |
| Anthropic | [console.anthropic.com](https://console.anthropic.com) → Settings → API Keys |
| OpenAI | [platform.openai.com](https://platform.openai.com) → API Keys |
| Hugging Face | [huggingface.co](https://huggingface.co) → Settings → Access Tokens (use **Read** scope) |
| Weights & Biases | [wandb.ai](https://wandb.ai) → User Settings → API keys |
* **OpenAI**: scope the key to **Read-only** project permissions
* **Anthropic**: scope to a specific workspace
* **Hugging Face**: pick **Read** scope (not **Write**)
* **W\&B**: viewer-level access; restrict to specific projects if you only want certain projects scanned
Go to **Settings → Integrations**, find the AI provider, and click **Connect**. Paste the API key. Matproof tests the connection and stores the credential encrypted.
Open **AI Systems** in the sidebar. For each AI system you've registered, link the relevant provider credential. Matproof now pulls model metadata, usage logs, and training metadata for that system on the next scheduled scan (or run a manual scan immediately).
## What evidence each integration produces
### Anthropic
* **Models in use** — every Claude model version your org has called in the last 90 days, by API key
* **Usage logs** — request count, token volume, error rate per model (rolled up; no individual prompts retained)
* **Content-filter configuration** — Anthropic's safety settings on each workspace
* **System-prompt inventory** — for AI systems registered with system-prompt tracking enabled
Maps to: EU AI Act Article 13 (transparency), Article 17 (QMS), Article 72 (post-market monitoring); ISO 42001 A.6.
### OpenAI
* **Models in use** — production model versions, including fine-tune lineage (which base model + which fine-tune dataset)
* **Usage logs** — request volume per project per model
* **Moderation flag rate** — how often the OpenAI moderation API flagged content over time
* **Fine-tune history** — datasets used, training runs, evaluation metrics
Maps to: EU AI Act Article 11 (technical docs), Annex IV; ISO 42001 A.6, A.7.
### Hugging Face
* **Organization model cards** — Matproof imports model cards for any model your HF org publishes or maintains. These satisfy EU AI Act Article 53(1)(a–c) GPAI documentation requirements.
* **Dataset cards** — for training datasets your org owns or uses
* **Fine-tune lineage** — base model → fine-tune model relationships
* **Evaluation results** — published evaluation metrics on model cards
Maps to: EU AI Act Article 53 (GPAI obligations), Annex IV; ISO 42001 A.7.
### Weights & Biases
* **Training runs** — every run with hyperparameters, dataset references, evaluation metrics
* **Model artefacts** — versioned model weights with provenance
* **Sweep / experiment results** — hyperparameter tuning campaigns
* **Reports** — W\&B reports linked as documentation artefacts
Maps to: EU AI Act Article 11 (technical documentation), Annex IV (records of training/testing); ISO 42001 A.6.2.
## Privacy and data handling
These integrations read **metadata** about your AI usage — not the prompts, completions, or training data themselves.
* Matproof does not store any prompts you send to Anthropic or OpenAI
* Matproof does not download training datasets from Hugging Face (only the dataset card / metadata)
* Matproof does not store model weights from W\&B (only the run metadata)
If your AI infrastructure processes personal data, your existing GDPR / DPA obligations apply at the provider level, not at the Matproof level.
## Disconnecting
For each provider, **Settings → Integrations → \[Provider] → Disconnect**. The encrypted credential is purged from Matproof's secrets store.
Also revoke the API key in the provider's console — disconnection only removes the credential from Matproof; the key itself remains valid in the provider's system until you delete it there.
The framework that drives most AI-integration use cases
AI management system companion standard