How to scrape investment and VC data from Preqin using the Minexa API
- Minexa.ai
- Jun 26
- 2 min read
Preqin publishes structured updates about private markets, fund forecasts, credit ratings, and sustainability classifications. Analysts who track these updates manually visit the page, read through articles, and copy what they need. That works for one article. It breaks down when you need to monitor dozens of updates across weeks or months.
The Minexa API solves this by letting you train a scraper once on the Preqin help center articles page, then call it programmatically whenever you need fresh data. No browser, no copy-paste, no manual scheduling.
What the Minexa API workflow looks like
The developer workflow has two phases. First, you train a scraper using the Minexa Chrome extension on the target page. This takes a few minutes and produces a stable scraper ID. Second, you call the Minexa API with that scraper ID and a list of URLs to extract data at scale. The extension handles the visual training. The API handles the production runs.
Pagination on Preqin requires a JS code scenario defined during training. Unlike the Chrome extension, which handles pagination automatically, the API workflow needs you to specify what gets clicked to load more results. You define this once during setup, and it applies to every subsequent API call.
Watch the full walkthrough
Training the scraper: step by step
Open the Minexa home page and navigate to the Preqin help center articles listing.
Once the page loads, open the Minexa extension. Click 'I'm on the right page' to confirm the target URL.
Minexa detects pagination automatically during training. Review the detected pages and click Continue.
Choose whether to scrape the list page only or follow each article link to extract detail page content as well. For a monitoring pipeline, list-only extraction is usually sufficient.
Highlight the article container. Minexa identifies all data points within each repeating result block automatically.
Review the extracted fields. Minexa surfaces article titles, publication dates, full descriptions, and article link paths without requiring you to name them in advance.
The code samples screen shows your scraper ID and a ready-to-run Python snippet. Copy the scraper ID. You will use it in every API call. Click 'Complete Configuration' to save.
Calling the API
With your scraper ID saved, you can now call the Minexa API to extract data from any Preqin articles page programmatically.
import requests
url = "https://api.minexa.ai/data"
headers = {"Authorization": "Bearer YOUR_API_KEY", "Content-Type": "application/json"}
payload = {
"scraper_id": 7341,
"urls": ["https://www.preqin.com/help-center/articles"],
"columns": "top_20"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
Sample extracted data
news_title | event_date | article_link |
Introducing Preqin Private Credit | 6 May 2026 | /help-center/articles/view/introducing-preqin-private-credit |
New Fund Forecast tool in Preqin Pro | 13 Mar 2026 | /help-center/articles/view/new-fund-forecast-tool-in-preqin-pro |
Release notes - November 2025 | 25 Nov 2025 | /help-center/articles/view/release-notes-november-2025 |
Each row maps to one article. The long_description field carries the full article body text, making it suitable for downstream NLP, tagging, or summarisation workflows without a separate detail-page request.
For recurring extraction, set up a cron job on your own infrastructure and pass updated URL lists to the same API endpoint. The scraper ID stays stable across runs, so no retraining is needed unless Preqin changes the page structure.
Get your API key and review the full endpoint reference at minexa.stoplight.io/docs/minexa.
For a comparable API-based extraction tutorial on a different data source, see how to scrape institution data from Carnegie Classifications using the Minexa API.
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