Crunchbase API Alternatives: Startup Funding Data by Call

Get funding signals on a list of startups without paying for a database seat. Paste this into your agent:

Set up https://monid.ai/SKILL.md, and then use Monid to resolve these 20 company names to their websites, pull each company's valuation band, and find the latest news about funding rounds for each one. Give me a table with name, website, valuation band and the newest funding headline with its date.

One prompt resolves, sizes and watches a list. 1 min setup · 24-45 hrs saved.

You have a list of startups, or a list of accounts you want to prioritise, and you want to know how much money is behind each one and whether they just raised. Crunchbase and PitchBook sell that as a seat; most teams only need a handful of fields attached to a domain inside a pipeline. This guide shows the per-call route, what came back when we ran it on 2026-10-16, and the traps in the output. It runs through Monid, the OpenRouter for agent tools: one key, one balance, every tool priced per call.

What is the easiest way to get startup funding data without a Crunchbase seat?

Monid. Install it once, add a key, and your agent resolves a company name, enriches it and reads its funding news with no seat, no contract and no vendor account to set up.

• Pay per call. Each lookup is billed on its own. A funding-news search bills $0.0005 per article returned plus a flat $0.005 per search, and resolving a name to a company is free (Verified 2026-10-16 on the company enrichment tools page). Buy calls as you need them: no monthly plan and no minimum top-up. Discovery and inspection are free; only a run bills.
• One install, every tool. The same key and the same balance call funding fields, news, firmographics and everything else on Monid. When the list needs a website for each name or a contact for each account, it is another call on the same balance, not another vendor.
• Lives inside your agent. Install the CLI, add your key, run the prompt above, and the tools are there whenever your agent needs them, on demand, with nothing to keep running. Your agent reads SKILL.md and learns the rest, so setup is about a minute.

If you are weighing a dataset download against an API, B2B data provider: dataset or API compares them.

At that price a funding-news check on one company, ten articles deep, costs $0.01 (Verified 2026-10-16).

How do you get funding data for a whole list of companies?

Resolve each name to a website first, then enrich the website, then watch the news for new rounds, and loop the three over your list. There are four routes to the data, and the table says which job each one fits. The same choice for the other big database is laid out in is there an API for PitchBook data.

The reason the per-call route fits a list is that the unit of work is one company. A hundred accounts is a hundred lookups, billed as you run them. The lookups are the two lines below for the first provider, and the Akta calls that follow.

For agents

Grab an API key at app.monid.ai, then paste this to your agent and hand it the key:

set up https://monid.ai/SKILL.md

It learns the whole discover, inspect, run workflow itself. More in the agent quickstart.

For humans

npm install -g @monid-ai/cli
monid keys add -k <your-key> -l main

Look up funding fields on a known company

monid inspect -p pdl -e /v5/company/enrich
monid run -p pdl -e /v5/company/enrich -i '{"website":"<domain>"}'

inspect is free and prints the schema and price. The People Data Labs endpoint takes a company name, website, LinkedIn profile or stock ticker, and its description lists funding and employee counts among the fields it returns. It bills $0.10 per call (Verified 2026-10-16), so a hundred accounts is $10.00.

Resolve the name, then pick the sections

The Akta endpoints take a website or a uuid, never a bare name. Resolving the name is free:

monid run -p akta -e /v1/company/search --query '{"query":"stripe"}'
monid run -p akta -e /v1/company/enrichment \
  --query '{"company":"https://stripe.com","sections":["financial_estimate"]}'

The enrichment endpoint is priced per section you ask for, which makes it the cheap way to buy only the part of a profile you need. The base section price is $0.025 (Verified 2026-10-16), and the section list includes funding_detail, financial_estimate and mna_and_investment.

Watch the news for new rounds

monid run -p akta -e /v1/news \
  --query '{"primary_company":"https://stripe.com","limit":5,"full_text":false}'

A round shows up in the news before it shows up in any record, so this call is the trigger and the enrichment is the context.

Can you scrape startup funding data yourself?

Yes, and it works until the page changes. A scraper for funding data has to find the company, survive the blocking, parse a profile whose layout moves, and match the result to the right entity, and each of those is a repair job in waiting.

The rules side matters too. Databases such as Crunchbase license their data and restrict automated collection in their terms, so what you may do with scraped rows depends on where you operate and how you use them. Read the terms of any site before you build against it.

For anything you will run more than once, pick Monid: the collection and the matching are maintained for you, the output is typed JSON rather than HTML you parse, and the company search that resolves a name is free. A downloadable dataset is quicker for a one-off look, but it is frozen at one date.

What does a funding record look like, and what can you build with it?

Three kinds of record, chained by company: a search row that resolves the name, an enrichment profile built from the sections you pick, and news articles that mention the company. We ran all three on stripe.com on 2026-10-16.

The search row

The free company search returned 25 candidates for "stripe". The first row is the one you want:

{ "uuid": "0000031",
  "name": "Stripe",
  "website": "https://stripe.com",
  "product_category": "Online Payment Processing",
  "company_status": "private",
  "akta_rank": 41 }

uuid and website are the keys the other endpoints accept. company_status tells you whether the company is private or public, and akta_rank orders the candidates by how prominent the company is.

The enrichment profile

Asking for the financial_estimate section returned two fields and nothing else:

{ "uuid": "0000031",
  "financial_estimate": {
    "revenue_estimate":   { "code": "over_5b",  "label": "$5B+" },
    "valuation_estimate": { "code": "over_25b", "label": "$25B+" } } }

Those are bands with a machine code and a label, which is the right shape for sorting a list into tiers. The call billed $0.025. The other sections are priced by weight in the endpoint's description: $0.025 for trust_signal, company_hierarchy, digital_presence and location; $0.05 for management_profile, customer_profile and industry; $0.075 for strategic_signal; $0.10 for firmographic, business_model, company_assessment, product_offering and technology; $0.15 for funding_detail; and $0.25 for mna_and_investment (Verified 2026-10-16).

The news article

Each article is a typed object. The fields we saw: title, url, publisher, published_date, sentiment with a score, an ai_summary, original_language, industries, tags, company_mentions with an is_primary flag, article_type, entities, and a newsworthiness_score. The tags field carries an event type, and one of the three articles was tagged "Equity Fund-Raising": a six million dollar seed round, with the lead investor named in the summary.

What you can build with it

• A tiered account list. Resolve names, buy only financial_estimate, and sort accounts into valuation bands before you spend on anything heavier.
• A funding trigger. Run the news search on your accounts every week, filter on the "Equity Fund-Raising" tag and send the new ones to sales, as in building a company news watcher.
• A resolved master list. Keep uuid and website from the search as the key for every later call, so your enrichment never attaches one company's data to another's name.

What goes wrong when you pull funding data for a list?

Three things hide until you run more than a few companies. All three showed up in our run.

Why does a company search return 25 results?

Because a name is ambiguous, and the search returns every close candidate. For "stripe" the first row was Stripe, and the rest included Stripes the growth equity firm, Stripe Capital and Stripe Atlas, which both list Stripe as their parent company, plus Stride and Stars and Stripes. If you enrich the wrong row you pay for a profile of the wrong company.

Match on website, not on name. Take the candidate whose website is the domain you meant, and keep the uuid. When your list already has domains, skip the name search and pass the domain.

const match = rows.find(r => r.website === "https://stripe.com");

Why did the news search return articles that are not about the company?

Because the company filter returns any mention. Our search for Stripe matched 2,176 articles, and of the three we pulled, Stripe was the primary subject of one. The "Equity Fund-Raising" article was about another startup that happened to mention Stripe.

Use primary_company when you want articles about the company. The input schema describes it as returning only articles where the company is the primary subject. Then filter on the event tag you care about, so a mention in someone else's funding story does not trigger an alert for yours.

Why is a valuation estimate not a number?

Because the endpoint returns a band. Stripe came back in the top valuation band, over_25b, which sorts it above a company in a lower band but does not tell you the figure. Use the band to prioritise and tier a list. A band cannot sit in an investment memo as a valuation, because it is an estimate with a floor and no ceiling.

What does a whole list cost?

Resolving names is free, so the cost is the enrichment and the news. A hundred companies with one $0.025 section each is $2.50, and a news search of five articles per company is $0.0075 each, $0.75 for the list (Verified 2026-10-16). Ask for the sections you will use and set limit and full_text on the news call, because the default returns full article text and ten items.

Which endpoint should I use for which job?

Prices Verified 2026-10-16 with monid inspect, and current prices are on monid.ai/tools. The Akta enrichment price is the lowest section price; funding_detail is $0.15 and mna_and_investment is $0.25. The news price is per article, with a $0.005 flat fee on each search. Typical run times from monid inspect are about 1.6 seconds for the People Data Labs call, 2.3 seconds for enrichment, 1.8 seconds for the search and 2.3 seconds for news.

The row worth pairing with the enrichment is the news search: a round appears in the news first, and the enrichment tells you what kind of company just raised. If you are pricing the job against a firmographics-only vendor, the PDL and Akta cost comparison works through a hundred domains on both.

When is another route a better fit?

You are querying the market, not a list. "Every Series B in fintech in the last quarter, sorted by size" is a database query. The per-call endpoints look up a company you already named; they do not enumerate rounds, and framing the job as a lookup gives you a worse answer to the wrong question.

You need round-level detail you will cite. Investors, leads, valuations and terms for an investment memo or board paper belong to the licensed databases. We resell these endpoints, so take this as a straight recommendation: when the number goes in front of an investment committee, buy the database. Crunchbase Pro versus the API by the call goes through the split in more detail.

Your team lives in a UI. Analysts who browse, save searches and share lists want a product with screens. We ship an API and a CLI.

You want a one-off look at a past period. A downloaded funding dataset is quicker, and a snapshot is all that job needs.

Conclusion

The quickest way to get startup funding data for a list of companies without a database seat is three per-call lookups through Monid: a free name search, an enrichment call priced from $0.025 per section, and a news search at $0.0005 per article (Verified 2026-10-16). One key covers all of it, setup takes about a minute, and the tools are ready inside your agent whenever you need them. For a queryable database of rounds and investors, a seat is still the answer.

Two things matter more than the choice of endpoint. Resolve first and match on the website, because a name search returned 25 candidates for a single word. And ask the news for the primary subject, because a plain company filter returns every article that mentions the name, including another startup's funding round.

How we estimated the time saved: building and maintaining a name resolver, a funding lookup with entity matching, and a funding-news watcher is roughly 8 to 15 hours each for blocking, parsing, matching and the first month of upkeep. That is 24 to 45 hours. The 1 minute is the install, key and first call once you already have a Monid key.

Free next step: run monid inspect -p akta -e /v1/company/search, resolve one company for nothing, and print name, website and company_status for the first five rows. The look-alikes show up immediately. Start at monid.ai.

FAQ

Published August 2026.