# Atlantico VC LatAm Digital Transformation Reports Scraper (`jungle_synthesizer/atlantico-vc-latam-digital-transformation-reports-scraper`) Actor Scrapes Atlantico VC's annual Latin America Digital Transformation Reports (2020-2025). Extracts report metadata, executive highlights, chapter summaries, and download links for all six annual editions — the canonical institutional research series on LatAm tech. - **URL**: https://apify.com/jungle\_synthesizer/atlantico-vc-latam-digital-transformation-reports-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Business, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Atlantico VC LatAm Digital Transformation Reports Scraper Scrapes Atlantico VC's annual **Latin America Digital Transformation Reports** (2020-2025) — the canonical institutional research series on LatAm tech, cited by Bloomberg, FT, and TechCrunch. Extracts report metadata, executive summaries, key highlights, and DocSend download links for all six annual editions. ### What It Returns One record per annual report: | Field | Description | |-------|-------------| | `report_year` | Year of the annual edition (2020-2025) | | `report_title` | Full report title (e.g. "Tectonic Shifts:" for 2023) | | `report_url` | Canonical URL of the report page | | `published_date` | Publication date as shown on the page (e.g. "August, 2023") | | `executive_summary` | Page meta-description summary (~200 chars) | | `highlights` | Key insight titles from the Highlights section (newline-separated) | | `highlight_details` | Full description for each highlight (newline-separated, aligned to highlights) | | `pdf_url` | DocSend link for the EN edition | | `chapter_title` | Chapter title (null for top-level reports) | | `chapter_url` | Chapter URL (null for top-level reports) | ### Sample Output (2023 edition) ```json { "report_year": 2023, "report_title": "Tectonic Shifts:", "report_url": "https://www.atlantico.vc/latin-america-digital-transformation-report-2023", "published_date": "August, 2023", "executive_summary": "Latin America Digital Transformation Report 2023 - Download the report and access additional original information, data and analysis about technology in Latin America.", "highlights": "The Engine of The World\nUnexpected Winner of Geopolitical Turmoil\nDigital Democratization\nRenewal of the Entrepreneurial Spirit\nOptimism Warranted\nLatin America Punches Above Its Weight\nEntrepreneurship Beyond Tech\nMoney Goes Digital", "highlight_details": "Latin America is the world's mine and breadbasket, as the reverse of critical minerals...\nNeutral LatAm emerges as an unlikely beneficiary of US-China polarization...", "pdf_url": "https://docsend.com/view/48rpy858p2kqy479", "chapter_title": null, "chapter_url": null } ```` ### Use Cases - **LATAM strategy research** — programmatically compare year-over-year LatAm tech trends across all six annual editions - **VC / LP reporting** — extract key insights for fund-of-fund LP updates referencing Atlantico's flagship research - **Competitive intelligence** — track which sectors and countries Atlantico highlights year over year (fintech, healthtech, Brazil, Mexico) - **Academic / press** — structured access to the most-cited English-language institutional research on LatAm tech ### Inputs | Input | Type | Description | Default | |-------|------|-------------|---------| | `maxItems` | integer | Maximum number of annual reports to scrape. Leave blank for all. | 10 | The sitemap currently lists six annual report editions (2020-2025). A full run completes in under 30 seconds. ### How It Works 1. Fetches `https://www.atlantico.vc/sitemap.xml` (flat urlset) and filters for annual report URLs 2. Crawls each matching page with CheerioCrawler (no proxy required — site returns HTTP 200 for all agents) 3. Extracts: `.report-title`, `.color-white-80` (date), `.highlight-wrp` cards (titles + descriptions), `.download-btn` (DocSend link), meta description 4. Report year is parsed from the URL path No proxy, no CF bypass, no authentication required. ### Notes - `highlights` and `highlight_details` are newline-joined parallel arrays — split on `\n` to get individual insight pairs - The 2025 edition uses a newer page layout where highlight text is rendered inside images; that page returns `null` for `highlights` - `pdf_url` links to DocSend (gated viewer), not a direct PDF download - Atlantico publishes new editions annually (typically September) — re-run to capture the latest # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of report records to scrape (one per annual report). Leave blank for all. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/atlantico-vc-latam-digital-transformation-reports-scraper").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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/atlantico-vc-latam-digital-transformation-reports-scraper").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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }' | apify call jungle_synthesizer/atlantico-vc-latam-digital-transformation-reports-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/atlantico-vc-latam-digital-transformation-reports-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Atlantico VC LatAm Digital Transformation Reports Scraper", "description": "Scrapes Atlantico VC's annual Latin America Digital Transformation Reports (2020-2025). Extracts report metadata, executive highlights, chapter summaries, and download links for all six annual editions — the canonical institutional research series on LatAm tech.\n", "version": "0.1", "x-build-id": "HBB3E23tQVxGdhY3M" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~atlantico-vc-latam-digital-transformation-reports-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-atlantico-vc-latam-digital-transformation-reports-scraper", "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/jungle_synthesizer~atlantico-vc-latam-digital-transformation-reports-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-atlantico-vc-latam-digital-transformation-reports-scraper", "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/jungle_synthesizer~atlantico-vc-latam-digital-transformation-reports-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-atlantico-vc-latam-digital-transformation-reports-scraper", "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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of report records to scrape (one per annual report). Leave blank for all." } } }, "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 } } } } } } } } } } ```