Get company growth scores, heat trends and predictions
View all Crunchbase Company & Investment Data endpoints →Retrieve growth and heat signals for one Crunchbase company with GET /companies/growth. The required company query parameter accepts an organization permalink, UUID or Crunchbase organization URL; openai is the supplied example. The documented response example is a flat object with company identity fields id, image, link, name, type and uuid; growth_score and heat_score; growth_score_delta_90d and heat_score_delta_90d; growth_score_history and heat_score_history; and growth_trend_365d and heat_trend_365d. The example history and trend values are numeric arrays, without individual timestamps or a documented sampling cadence. growth_insight contains customers, finance, generated_on and press, whose articles have author, id, link, posted_on, publisher and title. investor_insight contains generated_on, categories with id and name, locations, and portfolio_status_counts such as ipo and operating. predictions contains generated_on, type, probability, tier, media_sentiment, unicorn_status and timeline probabilities named months_00_to_05, months_06_to_11, months_12_to_24 and months_24_plus. The documented purpose includes funding, IPO and acquisition predictions; these are model-derived research signals, not confirmed transactions or investment advice. rank contains company, overall and delta_90d. No live probe result was supplied for this operation: these field names come from an unverified documentation example, not an observed response. Some example fields, including finance, article author, tier and media_sentiment, are null. Coverage, score ranges, scoring methodology and refresh frequency are not established by the supplied evidence.
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/api/project/crunchbase/company-growth-signals API Response (JSON)
{} curl -X GET 'https://api.opendata-api.com/api/project/crunchbase/company-growth-signals?key=<API_KEY>&company=openai'
Query Result
Use Cases
- Prioritize a startup-triage queue using available growth and heat scores alongside analysts' qualitative notes, without treating a score as an investment recommendation.
- Maintain a watchlist of model-derived funding, IPO and acquisition predictions, with explicit labels separating predictions from announced transactions.
- Compare retrieved numeric score-history arrays during periodic company reviews while recording retrieval times independently rather than inventing observation dates.
- Give an account-research team press context and investor-category signals to investigate unusual momentum before updating its internal company assessment.
Frequently asked questions
Which company identifier can I pass to the growth-signals endpoint?
The required company query parameter accepts a Crunchbase organization permalink such as openai, an organization UUID or a full Crunchbase organization URL. A company name or website domain alone is not a documented input form.
Are the growth and heat score fields verified by a live response?
No live probe result was supplied for this operation. growth_score, heat_score, their 90-day delta fields and the other described fields appear in a documentation example and remain unverified for live requests.
Do the predictions confirm a funding round, IPO or acquisition?
No. The documented purpose includes predictions of those events, with probability and timeline fields in the example. They are model-derived research signals, not transaction confirmations, guarantees or investment advice.
Can I assign dates to the score-history array entries?
Not from the supplied example alone. growth_score_history, heat_score_history, growth_trend_365d and heat_trend_365d are numeric arrays without per-entry timestamps. Their sampling cadence and the score scale are not documented.
Can insight or prediction values be null?
Yes. The documentation example includes null finance, press author, tier and media_sentiment values. Handle missing or null information explicitly; the example does not establish universal field coverage or a refresh schedule.