# PolicySignal โ€” AI-powered policy & regulatory intelligence (`policypulse/policy-pulse----ai-regulatory-intelligence-risk-monitoring`) Actor PolicySignal detects meaningful policy changes, assesses risk, and surfaces what actually matters. Powered by AI, it analyzes semantic differences, classifies content, and delivers actionable regulatory intelligence so you can act with confidence. - **URL**: https://apify.com/policypulse/policy-pulse----ai-regulatory-intelligence-risk-monitoring.md - **Developed by:** [Jacques Phillip Louwrens](https://apify.com/policypulse) (community) - **Categories:** AI, Automation, Developer tools - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $150.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## ๐Ÿค– PolicySignal โ€” Semantic Policy Intelligence Monitoring ![PolicySignal โ€” Signal vs Noise](https://raw.githubusercontent.com/JacquesLouwrens/policy-pulse-actor/main/assets/policy-pulse-hero-signal-vs-noise.png) > Detect meaningful policy changes โ€” not noise. > **Know what changed. Know what matters.** > Built for compliance, legal, and risk-aware monitoring workflows. **Built with Apify โ€ข Node.js โ€ข Production-ready** --- ### ๐Ÿš€ Why PolicySignal Most monitoring tools show *what changed*. PolicySignal shows **what matters**. - Detects **semantic changes**, not just text differences - Filters **noise vs meaningful impact** - Scores **risk, severity, and business impact** - Delivers **clear, actionable insights** --- ### ๐ŸŽฏ Overview **PolicySignal** is an AI-powered policy and regulatory intelligence engine designed to detect meaningful changes across policy, legal, compliance, and website terms pages. Traditional monitoring tools generate noise by flagging every visual or textual edit. PolicySignal focuses on **changes in meaning**, helping you identify updates that actually require attention. It combines semantic analysis with classification, risk scoring, and structured outputs to deliver clear, actionable intelligence for real-world decision-making. --- ### ๐Ÿง  What PolicySignal Answers Most tools answer: > *"Did something change?"* PolicySignal answers: - Did the **meaning** change? - Was a new **obligation introduced**? - Did **risk increase**? - Is this **signal or noise**? - Should this be **reviewed now**? --- ### โœจ Core Features #### ๐Ÿ” Semantic Change Detection Understands meaning, not just raw text differences. #### ๐Ÿง  Policy Classification Categorizes content into policy-relevant types. #### โš ๏ธ Risk Scoring Evaluates the potential business and compliance impact of changes. #### ๐Ÿ“Š Relevance & Materiality Assessment Filters out low-value edits and highlights meaningful updates. #### ๐Ÿšจ Signal Decision Layer Determines whether a change should trigger action or notification. #### ๐Ÿงพ Review Recommendations Provides structured guidance for follow-up actions. #### ๐Ÿ”„ Baseline-Aware Monitoring Creates a baseline on first run and detects real changes over time. #### ๐ŸŒ Multi-URL Support Monitor multiple policy pages in a single run. --- ### ๐Ÿงฉ How It Works 1. Provide one or more URLs 2. PolicySignal fetches and extracts content 3. First run creates a **baseline snapshot** 4. Future runs compare against the baseline 5. Outputs structured intelligence, including: - `semanticDiff` - `policyClassification` - `riskAssessment` - `relevanceAssessment` - `materialityAssessment` - `priorityAssessment` - `signalDecision` - `resultSummary` - `reviewRecommendation` --- ### ๐Ÿ“Š Example Output Visualization ![PolicySignal Output](https://raw.githubusercontent.com/JacquesLouwrens/policy-pulse-actor/main/assets/policy-pulse-output-structured-ui.png) Structured, risk-aware outputs designed for real decision-making and automation. --- ### ๐Ÿข Use Cases #### Compliance Monitoring Track changes in privacy policies, regulations, and compliance frameworks. #### Vendor Risk Management Monitor supplier and partner policy updates. #### Legal & Policy Tracking Stay informed about terms of service and legal document changes. #### Competitive Intelligence Observe how competitors evolve their policies. #### AI Governance Track updates in AI-related policies and usage guidelines. --- ### ๐Ÿงฉ Where PolicySignal Fits ![PolicySignal Use Cases](https://raw.githubusercontent.com/JacquesLouwrens/policy-pulse-actor/main/assets/policy-pulse-use-cases-grid.png) Built for compliance, legal, vendor risk, and governance workflows. --- ### ๐Ÿ“Œ When to Use PolicySignal - Detect meaningful policy changes - Reduce noise from traditional diff tools - Enable structured, actionable outputs - Support risk-aware decision-making --- ### โš ๏ธ Notes - The first run creates a baseline snapshot - Subsequent runs detect changes relative to that baseline - Best suited for structured policy or legal content - Designed to support review workflows, not replace legal judgment --- ### ๐Ÿ”— Links Run Actor https://console.apify.com/actors/ScXMKVtO10tXHiBJN/runs Apify API Documentation https://docs.apify.com/api/v2 --- ### ๐Ÿ“ž Support PolicySignal integrates into alerting systems, digest pipelines, and compliance workflows. Actor ID: ScXMKVtO10tXHiBJN Version: Release Candidate โ€” Store Packaging Phase # Actor input Schema ## `url` (type: `string`): Use this field to monitor one policy, legal, compliance, or terms page. ## `plan` (type: `string`): Select the customer plan for tier-aware testing and enforcement. ## Actor input object example ```json { "plan": "free" } ```` # Actor output Schema ## `results` (type: `string`): Structured result items stored in the default dataset. ## `dataset` (type: `string`): The dataset containing all Policy Pulse result items for this run. ## `keyValueStore` (type: `string`): Run artifacts and persisted records such as snapshots, diffs, or raw state keys if present. # 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("policypulse/policy-pulse----ai-regulatory-intelligence-risk-monitoring").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("policypulse/policy-pulse----ai-regulatory-intelligence-risk-monitoring").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 policypulse/policy-pulse----ai-regulatory-intelligence-risk-monitoring --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=policypulse/policy-pulse----ai-regulatory-intelligence-risk-monitoring", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PolicySignal โ€” AI-powered policy & regulatory intelligence", "description": "PolicySignal detects meaningful policy changes, assesses risk, and surfaces what actually matters. Powered by AI, it analyzes semantic differences, classifies content, and delivers actionable regulatory intelligence so you can act with confidence.", "version": "0.0", "x-build-id": "DoVLFFbjsauNzUmAD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/policypulse~policy-pulse----ai-regulatory-intelligence-risk-monitoring/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-policypulse-policy-pulse----ai-regulatory-intelligence-risk-monitoring", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/policypulse~policy-pulse----ai-regulatory-intelligence-risk-monitoring/runs": { "post": { "operationId": "runs-sync-policypulse-policy-pulse----ai-regulatory-intelligence-risk-monitoring", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/policypulse~policy-pulse----ai-regulatory-intelligence-risk-monitoring/run-sync": { "post": { "operationId": "run-sync-policypulse-policy-pulse----ai-regulatory-intelligence-risk-monitoring", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "url" ], "properties": { "url": { "title": "Single Policy URL", "minLength": 1, "type": "string", "description": "Use this field to monitor one policy, legal, compliance, or terms page." }, "plan": { "title": "Plan", "enum": [ "free", "starter", "growth", "pro", "enterprise" ], "type": "string", "description": "Select the customer plan for tier-aware testing and enforcement.", "default": "free" } } }, "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 } } } } } } } } } } ```