Persona: Venture Capital and M&A Teams

Use Case: Discover Early-Stage Investment Opportunities

Primary API(s): Search (Organizations) & Lookup an Organization

Goal: Discover Early-Stage Investment Opportunities

Use this Recipe when you want to systematically identify and monitor early-stage investment opportunities that align with your investment thesis. This workflow helps venture capital, corporate venture, and M&A teams reduce manual sourcing, detect momentum early, and build prioritized deal pipelines based on financial signals and company traction. Move from reactive deal flow to proactive, signal-based sourcing—prioritizing companies based on funding momentum, financial benchmarks, and market validation.

Step 1

Filter Companies to Relevant ICP

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

Endpoint

https://data.crunchbase.com/reference/searchorganizations-2

API Reference & Documentation

https://data.crunchbase.com/docs/using-search-apis https://data.crunchbase.com/reference/searchorganizations-2

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 the last 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 type of organization (e.g., SaaS, Android, Cloud Computing, Medical Device	blank;includes;includes_all;not_includes;not_includes_all

Sample Query - Pull companies matching core ICP firmographics

The following call is narrowing down companies to Seed and Series A as well as those that were funded in 2026. The field_ids ask to return information around categories (i.e. industries), the last funding date of the company, the type of funding it raised most recently, it's current valuation and the number of funding rounds they have gone through before.

POST /v4/data/searches/organizations HTTP/1.1
Accept: application/json
Content-Type: application/json
X-Cb-User-Key: *********************
Host: api.crunchbase.com

{"field_ids":[
   "categories",
   "identifier",
   "last_funding_at",
   "last_funding_type",
   "valuation",
   "num_funding_rounds"],


"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"
   ]}]}

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

"count": 126,
 "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
       },
       "num_funding_rounds": 2,
       "last_funding_at": "2026-01-06",
       "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://data.crunchbase.com/reference/getorganization-2

API Reference & Documentation

https://data.crunchbase.com/docs/using-search-apis https://data.crunchbase.com/reference/searchorganizations-2

In this query, we’re going to look at past funding activity, investors and press references using the UUID from the previous code block that were returned to us in step 1

GET /v4/data/entities/organizations/31bb23c0-d028-43c0-a49c-16908a5867e8?field_ids=&card_ids=raised_funding_rounds,press_references,investors HTTP/1.1
Accept: application/json
X-Cb-User-Key: ****************
Host: api.crunchbase.co,

Response

This response shows that from an early-stage investment perspective, LMArena is no longer an early discovery opportunity but rather a highly validated, later-entry company that has already cleared most early-stage risk. Although labeled “early stage,” a $150M Series A at a $1.55B pre-money valuation, backed by top-tier firms like Andreessen Horowitz, Kleiner Perkins, Lightspeed, and Felicis, signals strong institutional consensus and a competitive, fully priced deal. For early-stage investors, LMArena is best understood as a market signal rather than as a viable target itself, pointing instead toward smaller, earlier companies in adjacent or enabling spaces where true early-stage upside still exists.

{
 "properties": {
   "identifier": {
     "uuid": "31bb23c0-d028-43c0-a49c-16908a5867e8",
     "value": "LMArena",
     "image_id": "64a0297694304c1b9ee644c9e0fca405",
     "permalink": "lmarena",
     "entity_def_id": "organization"
   }
 },
 "cards": {
   "investors": [
     {
       "num_diversity_spotlight_investments": 304,
       "identifier": {
         "uuid": "ce91bad7-b6d8-e56e-0f45-4763c6c5ca29",
         "value": "Andreessen Horowitz",
         "image_id": "a6eb3a1422d244bb940a52ea0fea7f36",
         "permalink": "andreessen-horowitz",
         "entity_def_id": "organization"
       },
       "linkedin": {
         "value": "https://www.linkedin.com/company/a16z"
       },
       "short_description": "Andreessen Horowitz is a stage-agnostic venture capital firm with assets under management across multiple funds.",
       "num_portfolio_organizations": 1005,
       "num_investments": 1832,
       "revenue_range": "r_00100000",
       "operating_status": "active",
       "num_exits_ipo": 43,
       "hub_tags": [
         "cbvp"
       ],
   "press_references": [
     {
       "author": "FinSMEs",
       "posted_on": "2026-01-07",
       "publisher": "FinSMEs",
       "created_at": "2026-01-07T11:16:23Z",
       "title": "LMArena Raises $150M in Series A Funding",
       "updated_at": "2026-01-07T11:16:23Z",
       "activity_entities": [
         {
           "uuid": "ce91bad7-b6d8-e56e-0f45-4763c6c5ca29",
           "value": "Andreessen Horowitz",
           "image_id": "a6eb3a1422d244bb940a52ea0fea7f36",
           "permalink": "andreessen-horowitz",
           "entity_def_id": "organization"
         },
         {
           "uuid": "735a53c6-a7ba-2434-d97d-b788536da89d",
           "value": "Felicis",
           "image_id": "xopgjqvaqpada8zp498g",
           "permalink": "felicis-ventures",
           "entity_def_id": "organization"
         },
         {
           "uuid": "2d0a5bf0-e53e-9a07-2243-9bcd561421ec",
           "value": "Kleiner Perkins",
           "image_id": "ljhuy3jgwhjt4dvsok2o",
           "permalink": "kleiner-perkins-caufield-byers",
           "entity_def_id": "organization"
         },
         {
           "uuid": "6f10b245-46de-4329-8935-1bd716669fb8",
           "value": "Laude Ventures",
           "image_id": "f7e41f723596440d80f2f9c3ad9c962d",
           "permalink": "laude-ventures",
           "entity_def_id": "organization"
         },
         {
           "uuid": "d5df3873-7871-c608-0284-c74d0b555ccd",
           "value": "Lightspeed Venture Partners",
           "image_id": "c1ae649c69584f05bfc2f20ddea9d7c0",
           "permalink": "lightspeed-venture-partners",
           "entity_def_id": "organization"
         },
         {
           "uuid": "31bb23c0-d028-43c0-a49c-16908a5867e8",
           "value": "LMArena",
           "image_id": "64a0297694304c1b9ee644c9e0fca405",
           "permalink": "lmarena",
           "entity_def_id": "organization"
         },
         {
           "uuid": "2cb29b76-6989-7df3-a16a-c5e750e8169f",
           "value": "The House Fund",
           "image_id": "ckoilt6gllnkr7rajdlt",
           "permalink": "the-house-fund",
           "entity_def_id": "organization"
         },
         {
           "uuid": "3adab854-79b1-4e75-9932-7ed38b398580",
           "value": "UC Investments",
           "permalink": "uc-investments",
           "entity_def_id": "organization"
         }
       ],
       "identifier": {
         "uuid": "9ada1f4e-5341-4071-bbb0-89c9d1dbc751",
         "value": "LMArena Raises $150M in Series A Funding",
         "entity_def_id": "press_reference"
       },
       "url": {
         "value": "https://www.finsmes.com/2026/01/lmarena-raises-150m-in-series-a-funding.html"
       }
"raised_funding_rounds": [
     {
       "num_partners": 3,
       "announced_on": "2026-01-06",
       "funded_organization_funding_stage": "early_stage_venture",
       "is_equity": true,
       "funded_organization_categories": [
         {
           "uuid": "c4d8caf3-5fe7-359b-f9f2-2d708378e4ee",
           "value": "Artificial Intelligence (AI)",
           "image_id": "930c72a5a7b544999596ac1c0dc8b549",
           "permalink": "artificial-intelligence",
           "entity_def_id": "category"
         },
         {
           "uuid": "f579213a-60af-8bb3-309b-1d80607ad2a9",
           "value": "Information Services",
           "image_id": "3561862d356f4b61ad312f13a43abe38",
           "permalink": "information-services-f579",
           "entity_def_id": "category"
         },
         {
           "uuid": "5ea0cdb7-c9a6-47fc-50f8-c9b0fac04863",
           "value": "Machine Learning",
           "image_id": "e83f580a280f48f39d789180bce8c2d9",
           "permalink": "machine-learning",
           "entity_def_id": "category"
         },
         {
           "uuid": "f213df87-6356-e51f-245a-cf9b7e788b13",
           "value": "Product Research",
           "image_id": "03a37b78c144455fa9b0a62b5c2a0f78",
           "permalink": "product-research",
           "entity_def_id": "category"
         }
       ],
       "funded_organization_location": [
         {
           "uuid": "528f5e3c-90d1-1111-5d1c-2e4ff979d58e",
           "value": "San Francisco",
           "permalink": "san-francisco-california",
           "entity_def_id": "location",
           "location_type": "city"
         },
         {
           "uuid": "eb879a83-c91a-121e-0bb8-829782dbcf04",
           "value": "California",
           "permalink": "california-united-states",
           "entity_def_id": "location",
           "location_type": "region"
         },
         {
           "uuid": "f110fca2-1055-99f6-996d-011c198b3928",
           "value": "United States",
           "permalink": "united-states",
           "entity_def_id": "location",
           "location_type": "country"
         },
         {
           "uuid": "b25caef9-a1b8-3a5d-6232-93b2dfb6a1d1",
           "value": "North America",
           "permalink": "north-america",
           "entity_def_id": "location",
           "location_type": "continent"
         }
       ],
       "lead_investor_identifiers": [
         {
           "uuid": "735a53c6-a7ba-2434-d97d-b788536da89d",
           "value": "Felicis",
           "image_id": "xopgjqvaqpada8zp498g",
           "permalink": "felicis-ventures",
           "entity_def_id": "organization"
         },
         {
           "uuid": "3adab854-79b1-4e75-9932-7ed38b398580",
           "value": "UC Investments",
           "permalink": "uc-investments",
           "entity_def_id": "organization"
         }
       ],
       "investor_identifiers": [
         {
           "role": "investor",
           "uuid": "ce91bad7-b6d8-e56e-0f45-4763c6c5ca29",
           "value": "Andreessen Horowitz",
           "image_id": "a6eb3a1422d244bb940a52ea0fea7f36",
           "permalink": "andreessen-horowitz",
           "entity_def_id": "organization"
         },
         {
           "role": "investor",
           "uuid": "735a53c6-a7ba-2434-d97d-b788536da89d",
           "value": "Felicis",
           "image_id": "xopgjqvaqpada8zp498g",
           "permalink": "felicis-ventures",
           "entity_def_id": "organization"
         },
         {
           "role": "investor",
           "uuid": "2d0a5bf0-e53e-9a07-2243-9bcd561421ec",
           "value": "Kleiner Perkins",
           "image_id": "ljhuy3jgwhjt4dvsok2o",
           "permalink": "kleiner-perkins-caufield-byers",
           "entity_def_id": "organization"
         },
         {
           "role": "investor",
           "uuid": "6f10b245-46de-4329-8935-1bd716669fb8",
           "value": "Laude Ventures",
           "image_id": "f7e41f723596440d80f2f9c3ad9c962d",
           "permalink": "laude-ventures",
           "entity_def_id": "organization"
         },
         {
           "role": "investor",
           "uuid": "987c9a94-0dac-d8d0-cfc3-6481c358d1cd",
           "value": "LDV Partners",
           "image_id": "v1465449884/z6sku8m4jqbqkqtfgm5y.png",
           "permalink": "ldv-partners",
           "entity_def_id": "organization"
         },
         {
           "role": "investor",
           "uuid": "d5df3873-7871-c608-0284-c74d0b555ccd",
           "value": "Lightspeed Venture Partners",
           "image_id": "c1ae649c69584f05bfc2f20ddea9d7c0",
           "permalink": "lightspeed-venture-partners",
           "entity_def_id": "organization"
         },
         {
           "role": "investor",
           "uuid": "2cb29b76-6989-7df3-a16a-c5e750e8169f",
           "value": "The House Fund",
           "image_id": "ckoilt6gllnkr7rajdlt",
           "permalink": "the-house-fund",
           "entity_def_id": "organization"
         },
         {
           "role": "investor",
           "uuid": "3adab854-79b1-4e75-9932-7ed38b398580",
           "value": "UC Investments",
           "permalink": "uc-investments",
           "entity_def_id": "organization"
         }
       ],
       "funded_organization_identifier": {
         "role": "investee",
         "uuid": "31bb23c0-d028-43c0-a49c-16908a5867e8",
         "value": "LMArena",
         "image_id": "64a0297694304c1b9ee644c9e0fca405",
         "permalink": "lmarena",
         "entity_def_id": "organization"
       },
       "created_at": "2026-01-07T03:47:25Z",
       "pre_money_valuation": {
         "value": 1550000000,
         "currency": "USD",
         "value_usd": 1550000000
       },
       "identifier": {
         "uuid": "58c7f201-f989-495e-b9f9-8fa690aae2fa",
         "value": "Series A - LMArena",
         "image_id": "64a0297694304c1b9ee644c9e0fca405",
         "permalink": "lmarena-series-a--58c7f201",
         "entity_def_id": "funding_round"
       },
       "money_raised": {
         "value": 150000000,
         "currency": "USD",
         "value_usd": 150000000
       },
       "short_description": "LMArena raised $150000000 on 2026-01-06 in Series A",
       "investment_stage": "early_stage_venture",
       "num_investors": 8,
       "post_money_valuation": {
         "value": 1700000000,
         "currency": "USD",
         "value_usd": 1700000000
       },
       "funded_organization_funding_total": {
         "value": 250000000,
         "currency": "USD",
         "value_usd": 250000000
       },
       "investment_type": "series_a",
       "funded_organization_description": "LMArena is a web-based platform that evaluates large language models (LLMs) through anonymous, crowd-sourced pairwise comparisons.",
       "updated_at": "2026-01-07T03:47:25Z"
     },

From this response, we’re able to conclude:

LMArena has recently raised a $150M Series A at a $1.55B pre-money valuation, backed by top-tier investors including Andreessen Horowitz, Kleiner Perkins, Lightspeed, and Felicis.

The size of the round, valuation, and institutional backing signal strong market validation and reduced early-stage risk—indicating this is now a competitive, later-entry opportunity.

Having this level of detail on funding momentum, investor quality, and market validation can allow your team to quickly assess whether a company represents a viable early-stage opportunity—or a market signal pointing toward adjacent whitespace—so you can deploy capital more strategically than your competitors.

Additional Suggestions

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

Map funding stage + last round date to your internal deal stages
Use **employee count + revenue range **to gauge company maturity and check size fit
Create a simple field like “Recently Funded = Yes” for companies that raised in your target window
Add funding and press summaries directly into Investment Notes / IC Memo prep
Auto-flag companies that match your thesis for analyst review or partner queue

Suggested Data Warehouse / Reverse ETL Setup

Store funding history and valuation snapshots to track momentum over time
Push priority scores and flags back into Affinity, DealCloud, or your CRM
Track how signals (new funding, investor quality, press) impact deal progression

Best Practices

Cache the organization UUID (it doesn’t change)
Refresh funding and press data every 24–48 hours
Use press as an early signal for product launches, partnerships, expansions
Prioritize companies that show both thesis fit + recent activity