# Uk Ai Procurement Monitor (`hugo369/uk-ai-procurement-monitor`) Actor Monitor official UK Find a Tender notices for new or updated AI, data, analytics, and software procurement opportunities. - **URL**: https://apify.com/hugo369/uk-ai-procurement-monitor.md - **Developed by:** [Guoyong Hu](https://apify.com/hugo369) (community) - **Categories:** AI, Automation, News - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $200.00 / 1,000 results 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## UK AI & Data Procurement Monitor Monitor official UK Find a Tender notices for new or updated AI, data, analytics, and software procurement opportunities. This Actor reads the official Find a Tender open-contracting feed. It does not scrape pages, bypass logins, or process personal data. ### What You Get Each run writes matching procurement opportunities to the default dataset. Results include: - Notice title - Buyer - Description - Estimated value, when published - Deadline - UK region or delivery location, when available - Matched keywords - Unique OCID - Official Find a Tender notice link The first successful run checks the previous 30 days. Later runs report new or updated still-open opportunities. A notice must have an active tender status and a future deadline to be included. ### Best For - AI and machine learning suppliers tracking UK public-sector demand - Data platform and analytics vendors looking for open tenders - Software development suppliers monitoring relevant procurement notices - Business development teams that want a repeatable daily opportunity feed ### Input #### Keywords Terms to match in a notice title or description. Default keywords: - `artificial intelligence` - `AI` - `machine learning` - `data platform` - `data analytics` - `software development` You can replace these with your own terms, such as product names, service categories, or specialist technology keywords. #### Maximum results Caps the number of changed opportunities written in one run. Default: `100` Maximum: `500` #### Check updates since Optional ISO-8601 timestamp, for example: ```text 2026-07-01T00:00:00.000Z ```` Leave this empty for normal monitoring. The Actor will resume from its saved state after the first successful run. ### Output The default dataset contains one row per matching opportunity. Key fields: - `changeType`: `initial`, `new`, or `updated` - `ocid`: Open Contracting ID - `noticeId`: Find a Tender notice ID - `title`: notice title - `buyer`: public-sector buyer - `description`: tender description - `estimatedValue`: estimated contract value, if available - `publishedAt`: tender period start date, if available - `updatedAt`: release update timestamp - `deadline`: submission deadline - `region`: UK region or delivery location, if available - `matchedKeywords`: keywords that matched the notice - `sourceUrl`: official Find a Tender notice URL ### Pricing This Actor uses pay-per-event pricing based primarily on dataset results. You are charged for matching results written to the dataset. Runs with no matching opportunities should have minimal cost. ### Recommended Usage For ongoing monitoring: 1. Create a task from this Actor. 2. Keep `Check updates since` empty. 3. Use the default keywords or customize them for your market. 4. Schedule the task to run daily, for example at 08:00 Europe/London. 5. Download the dataset as CSV or JSON, or connect it to your downstream workflow. ### Data Source The Actor uses the official UK Find a Tender OCDS release packages API. Official notices remain the source of truth. Always review the linked Find a Tender notice before making business or bid decisions. # Actor input Schema ## `keywords` (type: `array`): Match terms in notice titles and descriptions. Leave blank to use the recommended AI and data software terms. ## `maxResults` (type: `integer`): Maximum number of changed opportunities written to the dataset in one run. ## `updatedSince` (type: `string`): Optional ISO-8601 timestamp. If omitted, the monitor resumes after its last successful run; the first run checks the previous 30 days. ## Actor input object example ```json { "keywords": [ "artificial intelligence", "AI", "machine learning", "data platform", "data analytics", "software development" ], "maxResults": 100, "updatedSince": "2026-07-01T00:00:00.000Z" } ``` # Actor output Schema ## `opportunities` (type: `string`): New or updated matching procurement opportunities. # 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 = { "keywords": [ "artificial intelligence", "AI", "machine learning", "data platform", "data analytics", "software development" ] }; // Run the Actor and wait for it to finish const run = await client.actor("hugo369/uk-ai-procurement-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "keywords": [ "artificial intelligence", "AI", "machine learning", "data platform", "data analytics", "software development", ] } # Run the Actor and wait for it to finish run = client.actor("hugo369/uk-ai-procurement-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "artificial intelligence", "AI", "machine learning", "data platform", "data analytics", "software development" ] }' | apify call hugo369/uk-ai-procurement-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hugo369/uk-ai-procurement-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Uk Ai Procurement Monitor", "description": "Monitor official UK Find a Tender notices for new or updated AI, data, analytics, and software procurement opportunities.", "version": "0.0", "x-build-id": "q8g3foQvvR9Z8f5ck" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hugo369~uk-ai-procurement-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hugo369-uk-ai-procurement-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/hugo369~uk-ai-procurement-monitor/runs": { "post": { "operationId": "runs-sync-hugo369-uk-ai-procurement-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/hugo369~uk-ai-procurement-monitor/run-sync": { "post": { "operationId": "run-sync-hugo369-uk-ai-procurement-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "keywords": { "title": "Keywords", "type": "array", "description": "Match terms in notice titles and descriptions. Leave blank to use the recommended AI and data software terms.", "items": { "type": "string" } }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of changed opportunities written to the dataset in one run.", "default": 100 }, "updatedSince": { "title": "Check updates since", "type": "string", "description": "Optional ISO-8601 timestamp. If omitted, the monitor resumes after its last successful run; the first run checks the previous 30 days." } } }, "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 } } } } } } } } } } ```