Crunchbase is the definitive database for startup and company intelligence. Funding rounds, lead investors, founder backgrounds, headcount, industry classification, and HQ location — it's all there, updated in near real time as deals get announced and companies grow. For anyone in sales, venture capital, business development, or competitive strategy, it's an essential daily resource.
The problem? Crunchbase gates most of its export functionality behind a paid Pro subscription, and even then, getting structured data out of individual company pages and into your own tools requires manual copying or expensive API access. If you're researching twenty companies a day, that friction adds up fast.
That's where PixieBrix's AI Page Editor comes in. It's a browser-native, point-and-click interface that lets you build custom web scrapers - including for Crunchbase - by describing what you want in plain English. No terminal. No selectors. No debugging. Just: "grab the company name, funding stage, total funding, and lead investors from this page" - and the AI builds the extractor for you.
In this post, we'll walk you through everything: what PixieBrix is, why Crunchbase data matters, and a full step-by-step guide to building your own Crunchbase scraper from scratch using the AI Page Editor.
Before we get into the how, let's talk about the why - because the use cases here span sales, investing, recruiting, and competitive research.
Sales prospecting with funding signals. A company that just closed a Series A or Series B is almost certainly spending - on headcount, tooling, infrastructure, and services. Funding announcements are one of the strongest buying signals in B2B sales. Scraping Crunchbase company pages for funding stage, round size, and announcement date gives sales teams a prioritized list of warm accounts without paying for a dedicated intent data platform.
Venture capital and investor research. VCs use Crunchbase to track deal flow, monitor portfolio companies, and research competitors. Being able to extract structured data from company pages - funding history, co-investors, valuation indicators, and growth signals - and pipe it into a deal tracking sheet or CRM saves hours of manual data entry per week.
Business development and partnerships. BD teams hunting for integration partners, resellers, or acquisition targets use Crunchbase to filter by industry, funding stage, and geography. Scraping the relevant fields from a list of target companies and logging them to a spreadsheet builds a pipeline without a Crunchbase Pro seat.
Competitive intelligence. Tracking what your competitors are raising, who's investing in them, how fast they're growing headcount, and what new products they're announcing is a full-time job. Crunchbase company pages are a reliable source for that signal - and scraping them regularly means you're always working from current data rather than a months-old export.
PixieBrix is a low-code browser extension platform that lets you customize, automate, and extend any website - including ones you didn't build and don't control. Think of it as a toolkit for bending the web to your workflow.
At the core of PixieBrix is the Page Editor: a point-and-click interface that lives in your browser's developer panel. With it, you can create custom browser "mods" - mini extensions that do things like extract data from a page, inject new UI elements, trigger automations, or push data to external tools.
The building blocks of every mod are called bricks - pre-made components for things like extracting HTML, transforming data, calling APIs, and writing output to a Google Sheet or clipboard. You snap them together like Lego, configure them visually, and the result runs inside your browser tab.
The AI layer is what makes all of this feel like magic. Instead of manually identifying CSS selectors or writing JavaScript to grab page elements, you describe the data you want in natural language and the AI generates the appropriate extraction logic for you. It understands the structure of the page you're on, maps your description to the right DOM elements, and wires it all up automatically.
The instant feedback loop is a standout feature: changes preview live, with no recompiling or reloading required. Iterate in seconds, not minutes.
"Vibe coding" is a term that's been picking up steam in developer circles - it describes the practice of building software by describing your intent in natural language and letting AI handle the implementation details. Instead of writing code line by line, you articulate what you want and iterate on the output.
For most scraping tasks, the hard part has always been the implementation layer: figuring out the exact HTML attributes or XPath expressions that target the right data on a specific page, handling edge cases when the page structure changes, and debugging when something breaks. Vibe coding short-circuits all of that.
With PixieBrix's AI Page Editor, you don't need to know how Crunchbase structures its company page markup or which React component holds the funding data. You just say: "extract the company name, funding stage, total funding raised, most recent round size, lead investors, and founding year from this Crunchbase page" - and the AI does the selector hunting for you. If it gets something wrong, you describe the correction. You're steering, not building.
For non-technical users, this is a complete unlock. For developers, it's a massive speed multiplier. Either way, what used to take an afternoon now takes about ten minutes.
Install the PixieBrix browser extension. PixieBrix runs directly inside your browser and can interact with the SaaS tools your team already uses.
Once installed, navigate to any Crunchbase company page. Then open the PixieBrix Page Editor - you can access it through the PixieBrix toolbar icon or via Chrome DevTools. You'll see the editor open alongside your active tab.
Here's where the vibe coding magic happens. Instead of configuring bricks manually or writing a single line of code, you just type what you want the scraper to do into the Page Editor's AI prompt. Here's the exact prompt used to build the scraper in this post:
"When I right-click on Crunchbase from the context menu, extract the following information about the company and copy to my clipboard. Each item should be formatted as a nice table into separate columns in both plain text and HTML so I can paste it nicely in a Notion table or Google Sheet row. Do not include a header.
- Company Name
- Industry
- Funding Stage
- Total Funding Raised
- Most Recent Round Size
- Most Recent Round Date
- Lead Investors
- Founding Year
- HQ Location
- Page URL"
That's it. You're describing the trigger (right-click context menu), the data you want (ten fields from the company profile), the output format (a table in both plain text and HTML), and the destination (clipboard). No selectors, no configuration, no brick-by-brick assembly.
After you send the prompt, PixieBrix's AI reads it, analyzes the Crunchbase page structure, and generates the entire mod for you - trigger, extraction logic, formatting, and clipboard output, all wired together automatically. No configuration required on your end.
Once the AI is done, the Page Editor reveals exactly what it constructed. You'll see a three-brick pipeline:
@company.Hit the green "Test" button in the top-right corner of the Page Editor to do a live test against the company page currently open in your tab. If everything looks right, you'll see a popup appear directly on the Crunchbase page.
From here, navigate to any Crunchbase company page and right-click anywhere on the page. Select "Copy Crunchbase Company to Clipboard" from the context menu and PixieBrix will extract the company data in real time. A small popup appears directly on the page with a single "Copy text" button - click it, and the formatted table lands on your clipboard.
Because PixieBrix copies the data in both plain text and HTML table format simultaneously, pasting works cleanly in either tool - no reformatting required.
In Google Sheets: Click into the first empty cell in your target row, then hit Cmd+V (Mac) or Ctrl+V (Windows). The data will paste across ten columns automatically - Company Name, Industry, Funding Stage, Total Funding Raised, Most Recent Round Size, Most Recent Round Date, Lead Investors, Founding Year, HQ Location, and Page URL each land in their own cell. If you're building a prospecting list or deal flow tracker, just keep a running sheet open in a pinned tab and paste after every company page you visit.
In Notion: Click into a table row, then paste. Notion picks up the HTML table format and distributes the fields across columns cleanly. If you're pasting into a Notion database, make sure your column names match the fields you configured in the prompt and the data will slot right in.
That's the full workflow: right-click a Crunchbase company page → click "Copy text" → paste into your sheet or database. Ten fields, one click, zero manual typing.
Google Sheets and Notion are just the starting point. PixieBrix integrates directly with a wide range of databases and tools - so instead of copying to clipboard and pasting manually, you can configure your mod to push extracted data straight to wherever your workflow lives. Popular destinations include Airtable, Salesforce, HubSpot, Slack, Microsoft Excel, Coda, Monday.com, Jira, and any tool that accepts a webhook or REST API call. If your stack has an API endpoint, PixieBrix can send data to it. That means the same Crunchbase scraper mod you built in this post can feed a CRM pipeline, trigger a Slack alert for your BD team when a target company closes a new round, append rows to an Airtable deal tracker, or kick off a Zapier or Make workflow - all without leaving your browser or writing a single line of code.
You don't need to configure anything from scratch. Open PixieBrix's Page Editor on any Crunchbase company page, paste the prompt below, and the mod will be built for you in seconds:
"When I right-click on Crunchbase from the context menu, extract the following information about the company and copy to my clipboard. Each item should be formatted as a nice table into separate columns in both plain text and HTML so I can paste it nicely in a Notion table or Google Sheet row. Do not include a header.
- Company Name
- Industry
- Funding Stage
- Total Funding Raised
- Most Recent Round Size
- Most Recent Round Date
- Lead Investors
- Founding Year
- HQ Location
- Page URL"
That's the whole thing. One prompt, one built mod, one click to copy any Crunchbase company into your workflow.
Once you're comfortable with the company scraper, the Page Editor opens up a lot more. Here are four natural extensions of the same approach:
Funding Round Scraper. Rather than scraping the company overview, build a mod targeted at Crunchbase's funding round detail pages - extracting round type, amount, announcement date, all participating investors, and the company's valuation if disclosed. Useful for VCs and analysts who need clean, structured deal data without manual entry.
Investor Profile Scraper. Crunchbase investor pages list a fund's portfolio companies, check size, stage focus, and recent investments. Build a mod that extracts this data from any investor page so you can quickly research which funds are active in your space, who's backed your competitors, and which investors are writing the kinds of checks you're looking for.
People Profile Scraper. Crunchbase has rich profiles on founders and executives - current company, role, past companies, LinkedIn URL, and notable investments if they angel invest. Build a mod to extract this data from people pages to enrich your outreach lists or research founding teams before a call.
Search Results Scraper. Crunchbase's search and discovery pages let you filter companies by industry, funding stage, geography, and founding date. Build a mod that extracts all visible company names, funding stages, and URLs from a filtered search results page in one pass - turning a Crunchbase search into an instant prospecting list.
Each of these follows the same build pattern as the company scraper - just a different page, different fields, and a different trigger. Once you've built one, the rest take a fraction of the time.
Crunchbase data has always been valuable. What's changed is who can access it efficiently. Until recently, pulling structured company data out of Crunchbase meant either paying for API access, subscribing to Pro, or copying fields by hand one company at a time.
PixieBrix's AI Page Editor changes that equation entirely. You describe the data you want, the AI builds the extractor, you point it at a company page - and ten fields of structured company intelligence land exactly where you need them. No code, no setup, no developer required.
If you want to try it yourself, install PixieBrix from the Chrome Web Store, open the Page Editor on any Crunchbase company page, and paste the prompt from this post. The whole setup - from install to first scraped row in a Google Sheet - takes about fifteen minutes.
And if Crunchbase is just the beginning, the same approach works on virtually any website: LinkedIn profiles, Indeed job postings, Glassdoor reviews, Google Maps listings, and more. Keep an eye on upcoming posts in this series.
Part of the Vibe Code Your Scraper series - building AI-powered web scrapers for popular platforms using PixieBrix's Page Editor.