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PitchBook Data as JSON: Collect Public Company Profiles with an API in 2026

Private-company research has a paywall problem: the numbers live on PitchBook, and a seat there is priced for funds, not for a Tuesday-afternoon question. The public profile pages carry a real slice, though: funding, investors, latest deals, competitors. I'll walk through collecting that slice by hand, show where it breaks, and then use the PitchBook Company API on Apify, which turns a list of profile URLs into one structured JSON row per company.

Disclosure: the Apify links in this post are affiliate links. If you run the Actor, I may earn a referral commission at no extra cost to you.

Does PitchBook have an API?

It does, for subscribers: official access rides on enterprise licensing, with no self-serve signup and no public price list. If you have a license, use it; the licensed dataset goes far deeper than any public page. For everyone else, the public profile pages are the accessible layer, and a scraper you call like an API turns them into uniform records: URLs in, rows out.

What the PitchBook Company API returns

The PitchBook Company API returns one flat row per company: firmographics, ownership and financing status, the latest deal, named investors, acquirers and competitors, and a plain-language summary as structured JSON.

Data point Example Notes
Firmographics name, website, HQ, founding year plus a company description
Industry and verticals fintech, SaaS as tagged on the profile
Headcount as listed with the financing status
Latest deal type, date, amount plus financing round counts
Investors and acquirers named with counts of recorded investments
Competitors named useful for market maps

Profiles that fail to load come back as error rows instead of sinking the batch, which matters once your URL list gets long.

Who this is for

VC and PE teams sourcing deals from target lists, sales and RevOps people enriching accounts with size, industry, and funding stage, and analysts mapping a sector by funding, headcount, and who competes with whom.

The manual way, and where it breaks

The hand route is searching a company name plus "pitchbook", opening the profile, copying the visible fields, and moving to the next. It holds for a handful of companies. At fifty you are fighting JavaScript-rendered pages, login prompts, format drift between profiles, and your own typos in the deal-amount column. The moment someone asks whether the sheet can refresh monthly, you are maintaining a pipeline, not answering a question.

The faster way: run the PitchBook Company API

Apify Console

  1. Open the PitchBook Company API and click Try for free.
  2. Paste profile URLs into companyUrls; up to 1,000 fit in one run.
  3. Run it and export the dataset as JSON, CSV, or Excel.

REST

curl -X POST "https://api.apify.com/v2/acts/johnvc~pitchbook-company-api/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "companyUrls": ["https://pitchbook.com/profiles/company/10874-98"] }'
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The run endpoint itself is documented in the Apify API docs.

Collect PitchBook data in Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("johnvc/pitchbook-company-api").call(
    run_input={
        "companyUrls": [
            "https://pitchbook.com/profiles/company/10874-98",
            "https://pitchbook.com/profiles/company/521432-65",
        ]
    }
)

for company in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(company)
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Reach for the latest deal, the investor names, and headcount first; those three answer most sourcing questions. A runnable version sits in the task PitchBook company data API for Python.

Bulk-collect profiles from a URL list

Bulk collect PitchBook companies from a URL list turns a spreadsheet column of profile links into uniform rows in one batch.

Private company data for deal sourcing

Collect private company data from PitchBook is the sourcing loop: firmographics plus financing status across a target sector.

Extract deal and financing data

Extract deal financing data from PitchBook narrows the output to deals: latest deal details, financing rounds, and who invested.

Straight to structured JSON

Scrape PitchBook company data to structured JSON is the minimal version for piping into whatever you already run.

Use it in Claude via MCP

Connected over the Model Context Protocol, the Actor is a lookup tool an agent can call: ask Claude about a private company and it fetches the profile row instead of reciting stale training data. The walkthrough is Get PitchBook company data in Claude via MCP, and new users can grab Claude at claude.ai.

FAQ about scraping PitchBook

What does the PitchBook scraper cost per company?

About 1.1 cents per company returned on the free tier, so 500 profiles land near $5.50. You pay per returned row, and Apify's free credit usually absorbs the first batches.

Where does PitchBook get its data, and what can a scraper see?

PitchBook builds its dataset through its own research operation, and most of it sits behind the license. A scraper sees none of that depth: it reads exactly what the public profile page displays and standardizes it into rows. Honest expectations here save you disappointment later.

Can I export PitchBook data with a scraper instead of platform exports?

Different things. Platform exports come with a subscription and its terms. This Actor never touches the licensed platform; it collects the public profile pages only, and exporting just means downloading your own dataset as CSV or JSON.

Does the scraper work from Claude via MCP?

Yes, through the Apify MCP server it becomes a callable tool in Claude, Claude Code, and Cursor, same inputs and outputs as the API.

Can I schedule the scraper to watch a target list?

Yes: save your URL list as a task, schedule it monthly, and diff the latest-deal field between runs to catch new financings. Start at the PitchBook Company API.

What are the limits of a PitchBook scraper?

It returns the public slice only: no logged-in financials, no full deal tables. Runs take up to 1,000 URLs by default, and failed URLs come back as error rows you can retry rather than silent gaps.

More from Truffle Pig Data

Neighboring Actors for company research: the Crunchbase Company API for funding and firmographics from the other big database, the Startup Investors Data Scraper for investor lists, and the Earnings Call Transcript API for what public companies say out loud.

Wrapping up

For sourcing and enrichment, the public slice of PitchBook goes a long way once it arrives as rows instead of pages. Feed your URL list to the PitchBook Company API and skip the copy-paste afternoon.

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