# AI Vendor Intelligence Agent (`ramsford/ai-vendor-intel`) Actor Track pricing changes, new model launches, feature updates, outages and security incidents across major AI vendors (OpenAI, Anthropic, Google, Azure AI, Mistral, Cohere, AWS Bedrock, xAI). One report per vendor with sourced citations. Pay per report. - **URL**: https://apify.com/ramsford/ai-vendor-intel.md - **Developed by:** [Don Johnson](https://apify.com/ramsford) (community) - **Categories:** AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $1,000.00 / 1,000 ai vendor intelligence reports 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 ## AI Vendor Intelligence Agent > **Track every pricing change, model launch, outage and security incident across the major AI vendors — without spending hours on Twitter.** You select the AI vendors (OpenAI, Anthropic, Google, Azure AI, AWS Bedrock, Mistral, Cohere, xAI, or any other name) and a lookback window. The actor returns one consolidated **vendor intelligence report** per vendor — with sourced citations — covering: - **Pricing changes** — $/M tokens, plan changes, free-tier shifts - **Model launches** — new models, GA flips, deprecations - **Feature updates** — prompt caching, function calling, vision, batch API, fine-tuning - **Incidents & outages** — live status incidents and recent disruptions - **Security & compliance** — disclosures, CVEs, SOC 2 / HIPAA / GDPR notes - **Competitive moves** — acquisitions, partnerships, enterprise wins, funding Output is one structured JSON record per vendor, ready to drop into a Slack alert, a weekly CIO digest, or your internal vendor scorecard. --- ### Who this is for - **CIOs and IT leaders** evaluating which AI vendor to standardize on - **Procurement teams** tracking pricing changes mid-contract - **AI / tech consultants** advising 5+ clients across vendors - **SMB owners** dependent on a single AI tool who can't afford to miss an outage - **Builders** who want a single weekly digest of "what changed across all major AI vendors" --- ### What you get back (per vendor) ```json { "vendor": "OpenAI", "vendorSlug": "openai", "summary": "OpenAI: 2 pricing signals, 1 model launch, 3 feature updates, 0 incidents, 0 security notes, 1 competitive move in the last 30 days.", "lookbackDays": 30, "pricingChanges": [{ "title": "...", "url": "...", "date": "...", "evidence": "..." }], "modelLaunches": [{ ... }], "featureUpdates": [{ ... }], "incidents": [{ ... }], "securityNotes": [{ ... }], "competitiveMoves": [{ ... }], "sourceUrls": [ "https://openai.com/news/", "https://platform.openai.com/docs/changelog", "https://openai.com/api/pricing/", "https://status.openai.com/" ], "scrapedAt": "2026-05-16T01:23:45.000Z" } ```` Each item inside a category carries the source `url`, a `date`, and a short `evidence` snippet so you can audit and forward without re-checking. *** ### Pricing — pay per report | Event | Price | What you get | |---|---|---| | `vendor-report` | **$2.50 per report** | One complete intelligence report for one vendor, covering all six categories with sourced citations | A typical CIO weekly digest covering 5 vendors costs **$12.50**. A consultant tracking 10 vendors across 4 clients monthly = **$100/month** vs ~20 hours of manual research. > *Pricing is set at the Apify Store level via Pay-Per-Event. You only pay for reports successfully produced.* *** ### Example use cases 1. **"Alert me when any major AI vendor changes pricing or launches a new model."** Schedule the actor weekly across \[openai, anthropic, google, azure, mistral]; pipe the dataset into Slack / email when `pricingChanges` or `modelLaunches` is non-empty. 2. **"Have we seen any incidents this week?"** Run with `intelligenceTypes: ["incidents"]` against your production vendors and surface only the `incidents` array. 3. **CIO weekly digest.** Schedule Mondays 7am, monitor your top 5 vendors, render the `summary` line and `modelLaunches` + `pricingChanges` into an internal newsletter. 4. **Procurement renewal prep.** Run with `lookbackDays: 90` two weeks before a contract renewal — get all pricing signals and competitive moves in one PDF-ready report. 5. **Vendor diligence for an investment.** Run with `lookbackDays: 180` across the candidate's stack to see how often their AI vendors change pricing or have outages. *** ### Input ```json { "vendors": ["openai", "anthropic", "google", "mistral"], "intelligenceTypes": [ "pricing", "model_launches", "feature_updates", "incidents", "security", "competitive_moves" ], "lookbackDays": 30, "maxItemsPerCategory": 5, "outputFormat": "report" } ``` | Field | Type | Default | Description | |---|---|---|---| | `vendors` | string\[] | — (required) | Vendor slugs or freeform names. Built-in slugs: `openai`, `anthropic`, `google`, `azure`, `aws`, `mistral`, `cohere`, `xai`. Unknown names fall back to a web-search-driven harvester. | | `intelligenceTypes` | string\[] | all 6 categories | Filter which categories to include in the report. | | `lookbackDays` | int | `30` | How far back to consider changelog / blog entries. | | `maxItemsPerCategory` | int | `5` | Cap per category per vendor. | | `outputFormat` | string | `report` | `report` = full structured report. `compact` = headline summary + counts only. | *** ### Built-in vendors | Slug | Vendor | Sources | |---|---|---| | `openai` | OpenAI | News, pricing, platform changelog, status | | `anthropic` | Anthropic | News, pricing, API release notes, status | | `google` | Google AI / Gemini / Vertex | Blog, Gemini API changelog, Cloud pricing, Cloud status | | `azure` | Microsoft Azure OpenAI / AI | Pricing, blog, "what's new", Azure status | | `aws` | AWS Bedrock | Pricing, what's new, doc history, AWS health | | `mistral` | Mistral AI | News, pricing, changelog, status | | `cohere` | Cohere | Blog, pricing, changelog, status | | `xai` | xAI (Grok) | News, API page, docs changelog, status | Pass a freeform name (e.g. `"Together AI"` or `"Replicate"`) and the actor falls back to a web-search-driven harvester that still produces a categorized report — handy for less common vendors. *** ### How the report is built 1. For each known vendor, fetches the vendor's news / changelog / blog, pricing pages, and status page. 2. Extracts article titles, dates, and snippets from each page (resilient to most blog / changelog layouts). 3. Classifies every snippet into one of six categories with a heuristic pattern set. 4. Deduplicates within category, caps to `maxItemsPerCategory`, attaches source URLs and dates. 5. Renders a one-line `summary` so the report is glanceable. 6. Emits one PPE `vendor-report` event so usage is tracked per real report produced. For unknown vendors, the actor runs 5 targeted Google queries (pricing change, model launch, outage, security, partnership) and classifies the results the same way. *** ### Competitive comparison | | This actor | Generic AI news scrapers | Vendor-specific changelog scrapers | Manual research | |---|---|---|---|---| | Categorized output (pricing / launches / incidents / security / competitive) | ✅ | ❌ | ❌ | ✅ (slow) | | Multi-vendor in one run | ✅ | partial | ❌ (one per vendor) | ❌ | | Incident / status detection | ✅ | ❌ | ❌ | ❌ | | Pay-per-result pricing | ✅ ($2.50/report) | usually per-run | usually per-run | n/a | | Built-in vendor registry | ✅ (8 vendors out of the box) | ❌ | ❌ | n/a | | Web-search fallback for unknown vendors | ✅ | ❌ | ❌ | ✅ | *** ### Operational notes - Built on `apify/actor-node-playwright-chrome:20`, headless Chromium. - Resilient to most cookie / consent overlays (Accept / Got it / Dismiss). - Each vendor processed independently — one vendor failure does not abort the run. - Default run: 4 GB memory, 15 min timeout — enough for 8–10 vendors with full reports. - The actor emits one PPE event per successfully produced report; failed vendor records do not charge. *** ### Roadmap - Diff mode (only show what changed vs the last run) - Slack / webhook output template - Daily digest combining all selected vendors into a single Markdown report - Subscriptions to specific change types (pricing-only, incidents-only) at a discounted rate *** Built by **Johnson AI Consulting** — part of the Apify Revenue Initiative. # Actor input Schema ## `vendors` (type: `array`): List of AI vendors to monitor. Supports built-in slugs (openai, anthropic, google, azure, aws, mistral, cohere, xai) or any vendor name — for unknown names the actor falls back to web search. ## `intelligenceTypes` (type: `array`): Categories of changes to surface. Defaults to all. ## `lookbackDays` (type: `integer`): How many days of changelog / blog history to consider when summarizing changes. ## `maxItemsPerCategory` (type: `integer`): Cap on the number of items kept per intelligence category per vendor (default 5). ## `outputFormat` (type: `string`): 'report' returns a full intelligence report. 'compact' returns just the headline summary and counts. ## Actor input object example ```json { "vendors": [ "openai", "anthropic", "google", "mistral" ], "intelligenceTypes": [ "pricing", "model_launches", "feature_updates", "incidents", "security", "competitive_moves" ], "lookbackDays": 30, "maxItemsPerCategory": 5, "outputFormat": "report" } ``` # 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 = { "vendors": [ "openai", "anthropic", "google", "mistral" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ramsford/ai-vendor-intel").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 = { "vendors": [ "openai", "anthropic", "google", "mistral", ] } # Run the Actor and wait for it to finish run = client.actor("ramsford/ai-vendor-intel").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 '{ "vendors": [ "openai", "anthropic", "google", "mistral" ] }' | apify call ramsford/ai-vendor-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ramsford/ai-vendor-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Vendor Intelligence Agent", "description": "Track pricing changes, new model launches, feature updates, outages and security incidents across major AI vendors (OpenAI, Anthropic, Google, Azure AI, Mistral, Cohere, AWS Bedrock, xAI). One report per vendor with sourced citations. Pay per report.", "version": "0.1", "x-build-id": "RPEEiJwKCqX3o3tVs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ramsford~ai-vendor-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ramsford-ai-vendor-intel", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ramsford~ai-vendor-intel/runs": { "post": { "operationId": "runs-sync-ramsford-ai-vendor-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ramsford~ai-vendor-intel/run-sync": { "post": { "operationId": "run-sync-ramsford-ai-vendor-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "vendors" ], "properties": { "vendors": { "title": "Vendors to monitor", "type": "array", "description": "List of AI vendors to monitor. Supports built-in slugs (openai, anthropic, google, azure, aws, mistral, cohere, xai) or any vendor name — for unknown names the actor falls back to web search.", "items": { "type": "string" } }, "intelligenceTypes": { "title": "Intelligence types", "type": "array", "description": "Categories of changes to surface. Defaults to all.", "items": { "type": "string", "enum": [ "pricing", "model_launches", "feature_updates", "incidents", "security", "competitive_moves" ], "enumTitles": [ "Pricing changes", "Model launches", "Feature updates", "Incidents & outages", "Security & compliance", "Competitive / partnership moves" ] }, "default": [ "pricing", "model_launches", "feature_updates", "incidents", "security", "competitive_moves" ] }, "lookbackDays": { "title": "Lookback window (days)", "minimum": 1, "maximum": 180, "type": "integer", "description": "How many days of changelog / blog history to consider when summarizing changes.", "default": 30 }, "maxItemsPerCategory": { "title": "Max items per category", "minimum": 1, "maximum": 25, "type": "integer", "description": "Cap on the number of items kept per intelligence category per vendor (default 5).", "default": 5 }, "outputFormat": { "title": "Output format", "enum": [ "report", "compact" ], "type": "string", "description": "'report' returns a full intelligence report. 'compact' returns just the headline summary and counts.", "default": "report" } } }, "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 } } } } } } } } } } ```