# EU AI Act Tracker โ€” GPAI, Enforcement & High-Risk Registry API (`nexgendata/eu-ai-act-intelligence`) Actor Monitor EU AI Act developments in one feed โ€” GPAI training-content transparency, AI Office enforcement, and high-risk rules. For compliance and legal teams. - **URL**: https://apify.com/nexgendata/eu-ai-act-intelligence.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Business, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $100.00 / 1,000 ai act records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## EU AI Act Tracker Monitor EU AI Act developments in one feed โ€” GPAI training-content transparency, AI Office enforcement & governance, and the high-risk system rules. Built for compliance, legal and policy teams tracking the Act as it comes into force. > Factual public regulatory data assembled from official EU sources. Not legal advice. ### โฐ Run this as a weekly compliance watch (recommended) ```json { "feeds": ["gpai", "enforcement", "high_risk"], "maxResults": 25 } ```` Weekly cron (`0 8 * * 1`) keeps a standing watch on the AI Office and the Act's implementation as new guidance and enforcement land. ### ๐Ÿ“Š What you get Clean JSON, one record per tracked item (fields from a live test run): - `feed` โ€” gpai / enforcement / high\_risk - `source` โ€” publishing body (AI Office, EU Commission, โ€ฆ) - `title` โ€” item title (parsed from the live page) - `link` โ€” canonical source URL - `publishedDate` โ€” where the source exposes one (best-effort) - `recordType` โ€” `live` or `roadmap-stub` - `fetched` โ€” whether the source responded this run - `note` โ€” roadmap/context where relevant **Pricing:** $0.10 per AI Act record (Pay-Per-Event) โ€” about **10 records per $1**. Plus a $0.01 actor-start. Decision-grade regulatory data; the universe is small but each record is compliance-relevant. ### ๐Ÿ—“๏ธ What ships today vs. what activates later (high-risk deferred to Dec 2027) | Feed | Status today | Activates | |---|---|---| | **GPAI transparency** | **LIVE** โ€” the AI Office public-summary template (published Jul 2025) + Code of Practice + FAQ; obligation active since Aug 2 2025 | โ€” | | **Enforcement & governance** | **LIVE** โ€” AI Office, regulatory-framework and implementation-timeline sources | grows as decisions publish | | **High-risk registry** | **ROADMAP STUB** โ€” tracks the fallback guidance sources (high-risk classification guidelines) today | **~Dec 2, 2027** โ€” the **Article-71 EU central database** public surface plugs into a marked integration point when it publishes (deferred from Aug 2 2026 by the EU Digital Omnibus, adopted Jun 2026) | This is stated plainly so you know exactly what the feed delivers now and what switches on when the EU database publishes. ### ๐Ÿค– Use with AI agents **Sample agent prompt:** ``` Pull this week's EU AI Act enforcement and GPAI transparency records and flag anything mentioning systemic-risk models. ``` **Agentic payments (x402):** Supports agentic payment via x402 โ€” agents can call this actor with USDC, no API key required. ### ๐Ÿ”— Related regulatory actors Part of the Regulatory cluster: [FTC Enforcement](https://apify.com/nexgendata/ftc-enforcement-actions-scraper) ยท [Federal Register Rules](https://apify.com/nexgendata/federal-register-rules-scraper) ยท [Regulatory Enforcement RAG](https://apify.com/nexgendata/regulatory-enforcement-rag) **Agent front doors:** [Legal MCP](https://apify.com/nexgendata/legal-mcp-server) ยท [Regulatory Filings MCP](https://apify.com/nexgendata/regulatory-filings-mcp) *** *Factual public EU regulatory data. Not legal advice.* **EU platform-regulation suite:** [EU DSA Transparency Database](https://apify.com/nexgendata/eu-dsa-transparency-tracker) โ€” per-platform content-moderation records. # Actor input Schema ## `feeds` (type: `array`): Which feeds to pull: gpai (training-content summaries), enforcement (AI Office & governance), high\_risk (guidance + Article-71 stub). ## `dateFrom` (type: `string`): YYYY-MM-DD filter (best-effort; where a publication date is exposed). ## `maxResults` (type: `integer`): Maximum records to return across the selected feeds. ## Actor input object example ```json { "feeds": [ "gpai", "enforcement", "high_risk" ], "maxResults": 25 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/eu-ai-act-intelligence").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/eu-ai-act-intelligence").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call nexgendata/eu-ai-act-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/eu-ai-act-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "EU AI Act Tracker โ€” GPAI, Enforcement & High-Risk Registry API", "description": "Monitor EU AI Act developments in one feed โ€” GPAI training-content transparency, AI Office enforcement, and high-risk rules. For compliance and legal teams.", "version": "0.0", "x-build-id": "J98tfU1nIXXO731eD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~eu-ai-act-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-eu-ai-act-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~eu-ai-act-intelligence/runs": { "post": { "operationId": "runs-sync-nexgendata-eu-ai-act-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~eu-ai-act-intelligence/run-sync": { "post": { "operationId": "run-sync-nexgendata-eu-ai-act-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "feeds": { "title": "Feeds", "type": "array", "description": "Which feeds to pull: gpai (training-content summaries), enforcement (AI Office & governance), high_risk (guidance + Article-71 stub).", "items": { "type": "string", "enum": [ "gpai", "enforcement", "high_risk" ] }, "default": [ "gpai", "enforcement", "high_risk" ] }, "dateFrom": { "title": "Published after", "type": "string", "description": "YYYY-MM-DD filter (best-effort; where a publication date is exposed)." }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum records to return across the selected feeds.", "default": 25 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```