Assess company prediction signals

Before you begin

This example was verified with Predictions and Insights access. Your API key must include the fields and collections requested below. Check your API package if an endpoint or field is unavailable. Complete your first API request to set CRUNCHBASE_API_KEY in bash or zsh. Commands below include response headers; look for HTTP 200, then read the JSON body.

Persona: Venture capital and M&A teams

Use case: Assess company prediction signals

Primary APIs: Organization Search and Organization Lookup

Goal: Filter companies, retrieve growth insights and prediction records, and inspect those signals to support company research. These signals do not forecast investment returns.

Before interpreting the results, review prediction scores and timing. See API Packages Overview for the reference matching your licensed access.

Step 1

Filter Companies to Relevant ICP

In this step, we’ll target our relevant ICP using filters such as industry, geography, revenue range, financial benchmarks and operating status.

Endpoint

https://api.crunchbase.com/v4/data/searches/organizations

API Reference & Documentation

Using Search APIs

Search Organizations

Key Fields for this Query

field_id	What this field does	operator_id (these are the compatible operators per field)
last_funding_at	Identifies the date of most recent Funding Round	between;blank;eq;gte;lte
last_funding_type	Identifies the last funding round type (e.g. Seed, Series A, Private Equity)	blank;eq;includes;not_eq;not_includes
categories	Identifies the types of organization (e.g. SaaS, Android, Cloud Computing, Medical Device)	blank;includes;includes_all;not_includes;not_includes_all
growth_insight_direction	Filters by the direction of the company's growth trajectory	blank;eq;includes;not_eq;not_includes

Sample Query - Pull companies matching core ICP firmographics that are growing

This call is narrowing down companies to Seed and Series A as those that were funded in 2026. The field_ids ask to return information around categories (i.e., industries), the date the company was last funded at and the type, current valuation and the Growth Insight that indicates whether the company is growing or not.

curl --include --request POST \
  --url 'https://api.crunchbase.com/v4/data/searches/organizations' \
  --header "X-cb-user-key: $CRUNCHBASE_API_KEY" \
  --header 'Accept: application/json' \
  --header 'Content-Type: application/json' \
  --data '{
  "field_ids": [
    "categories",
    "identifier",
    "last_funding_at",
    "last_funding_type",
    "valuation",
    "growth_insight_direction"
  ],
  "query": [
    {
      "field_id": "last_funding_at",
      "operator_id": "gte",
      "type": "predicate",
      "values": [
        "2026-01-01"
      ]
    },
    {
      "field_id": "last_funding_type",
      "operator_id": "includes",
      "type": "predicate",
      "values": [
        "seed",
        "series_a"
      ]
    },
    {
      "field_id": "growth_insight_direction",
      "operator_id": "eq",
      "type": "predicate",
      "values": [
        "c400_growing"
      ]
    }
  ],
  "limit": 3
}'

Here is an example of a response to the query above:

{
  "count": 191,
  "entities": [
    {
      "uuid": "31bb23c0-d028-43c0-a49c-16908a5867e8",
      "properties": {
        "identifier": {
          "permalink": "lmarena",
          "image_id": "64a0297694304c1b9ee644c9e0fca405",
          "uuid": "31bb23c0-d028-43c0-a49c-16908a5867e8",
          "entity_def_id": "organization",
          "value": "LMArena"
        },
        "valuation": {
          "value": 1700000000,
          "currency": "USD",
          "value_usd": 1700000000
        },
        "last_funding_at": "2026-01-06",
        "growth_insight_direction": "c400_growing",
        "last_funding_type": "series_a",
        "categories": [
          {
            "permalink": "artificial-intelligence",
            "image_id": "930c72a5a7b544999596ac1c0dc8b549",
            "uuid": "c4d8caf3-5fe7-359b-f9f2-2d708378e4ee",
            "entity_def_id": "category",
            "value": "Artificial Intelligence (AI)"
          },
          {
            "permalink": "information-services-f579",
            "image_id": "3561862d356f4b61ad312f13a43abe38",
            "uuid": "f579213a-60af-8bb3-309b-1d80607ad2a9",
            "entity_def_id": "category",
            "value": "Information Services"
          },
          {
            "permalink": "machine-learning",
            "image_id": "e83f580a280f48f39d789180bce8c2d9",
            "uuid": "5ea0cdb7-c9a6-47fc-50f8-c9b0fac04863",
            "entity_def_id": "category",
            "value": "Machine Learning"
          },
          {
            "permalink": "product-research",
            "image_id": "03a37b78c144455fa9b0a62b5c2a0f78",
            "uuid": "f213df87-6356-e51f-245a-cf9b7e788b13",
            "entity_def_id": "category",
            "value": "Product Research"
          }
        ]
      }
    }
  ]
}

Step 2

Reveal Key Signals for Identified Companies

In this step, we’ll reveal additional information about the organizations you identified in step 1, such as funding rounds, investors and press releases.

Endpoint

https://api.crunchbase.com/v4/data/entities/organizations/{entity_id}

API Reference & Documentation

Using Entity Lookup

Lookup an Organization

Retrieve predictions for a selected organization

The lookup uses LMArena as a concrete example. Replace lmarena with an organization UUID returned in Step 1 to investigate your own result.

curl --include --request GET \
  --url 'https://api.crunchbase.com/v4/data/entities/organizations/lmarena?field_ids=identifier,growth_insight_direction,growth_insight_confidence&card_ids=funding_predictions,layoff_predictions,ipo_predictions' \
  --header "X-cb-user-key: $CRUNCHBASE_API_KEY" \
  --header 'Accept: application/json'

Response

Response examples below are historical, shortened JSON samples; search samples show one entity and card samples show at most one record per card. Other fields or records may be omitted. Counts and values change; count is the total matching records, while entities contains the returned page.

The historical response combines an organization growth insight with funding, IPO, and layoff prediction cards. Inspect each prediction’s generated_on and select the latest record before using its score. Overall probabilities have no fixed time horizon; interpret timing intervals separately. Supporting references provide context and do not establish which signals caused a model result.

{
  "properties": {
    "growth_insight_direction": "c400_growing",
    "identifier": {
      "uuid": "31bb23c0-d028-43c0-a49c-16908a5867e8",
      "value": "LMArena",
      "image_id": "64a0297694304c1b9ee644c9e0fca405",
      "permalink": "lmarena",
      "entity_def_id": "organization"
    }
  },
  "cards": {
    "funding_predictions": [
      {
        "generated_on": "2025-10-04",
        "identifier": {
          "uuid": "213a4da5-af74-4ca1-9b4b-746ebc23d7c6",
          "value": "Funding Prediction 2025-10-04",
          "image_id": "9936fca57e3145ccb3d9f8e15975538b",
          "entity_def_id": "funding_prediction"
        },
        "probability_score": 0.9039,
        "created_at": "2025-10-06T20:11:15Z",
        "partnership_announcement": {
          "uuid": "5ce714d9-fad5-4495-8761-20c95f0d9a9a",
          "image_id": "9936fca57e3145ccb3d9f8e15975538b",
          "entity_def_id": "partnership_announcement"
        },
        "updated_at": "2025-10-06T20:11:15Z",
        "probability_tier": "p200_positive_low",
        "probability_score_timeseries": {
          "months_24_plus": 1.077442552104743e-06,
          "months_00_to_05": 0.9999987543203556,
          "months_06_to_11": 1.059329221048746e-07,
          "months_12_to_24": 6.230417009239019e-08
        },
        "growth_insight": {
          "uuid": "5e308c44-f2eb-45e2-99b9-ec327b844167",
          "value": "Growth Insight 2025-07-14",
          "image_id": "75e16c7af7234747a3af2f4333c8bf33",
          "entity_def_id": "growth_insight"
        },
        "product_launch": {
          "uuid": "a6de206c-98cc-416a-98c8-6f30b0751f51",
          "image_id": "9936fca57e3145ccb3d9f8e15975538b",
          "entity_def_id": "product_launch"
        },
        "organization": {
          "uuid": "31bb23c0-d028-43c0-a49c-16908a5867e8",
          "value": "LMArena",
          "image_id": "64a0297694304c1b9ee644c9e0fca405",
          "permalink": "lmarena",
          "entity_def_id": "organization"
        }
      }
    ]
  }
}

From this response, we’re able to conclude:

Use the growth insight and the latest prediction from each requested card as separate research inputs. Review missing cards before concluding that a signal is absent.

Having this level of forward-looking visibility into growth trajectory, funding probability, and supporting context allows your team to anticipate upside before it materializes—and to adjust entry timing, ownership targets, or risk exposure ahead of the broader market.

Additional Suggestions

Suggested CRM / Deal Tool Mapping (Salesforce, HubSpot, Affinity, DealCloud)

Map prediction probabilities into custom fields for sorting and prioritization
Create simple flags like “High Upside = Yes” when funding or IPO probability crosses your threshold
Create “Elevated Risk = Yes” when closure or downside risk signals increase
Add prediction summaries directly into Investment Notes / IC memo prep
Trigger alerts when prediction scores materially change over time

Suggested Data Warehouse / Reverse ETL Setup

Store historical prediction scores to track changes in outlook over time
Keep event probability scores separate from assumptions about investment returns
Push upside/risk flags and priority scores back into Affinity, DealCloud, or your CRM

Best Practices

Treat predictions as decision-support signals, not guarantees
Combine prediction data with qualitative context to strengthen conviction
Interpret the returned timing intervals relative to generated_on; the overall probability score has no fixed horizon
Regularly compare predictions to actual outcomes to refine internal thresholds

Check your result

Check the organization UUID and prediction generation date before using a score. An empty result is not a zero probability. Interpret scores and timing using the prediction definitions.

Search requests here use limit: 3 for a small first page. For a complete result set, follow search pagination while preserving the filters and ordering. For request failures, use the shared request and retry guidance.