Filters & Sorting - Dealroom API

This page is auto-generated from the API’s filter registry. Use GET /api/filters?scope={scope} to fetch this data programmatically.

The Dealroom API supports 88 filters across 6 scopes. Use the filter query parameter to apply filters, and the sort parameter to order results.

Companies

Scope: companies — Used on /api/entities when querying companies.

Company Info (11 filters)

Filter	Key	Type	Status	Operators	Description
Company Name	`name`	text	✅	`eq`	Companies whose name contains the search term.
Founded Date	`launch_date`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Year or period when the organization was launched.
Company Status	`company_status`	enum	✅	`eq` `neq` `in_any` `nin_any`	Lifecycle status.
Location	`location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates — cities, regions, countries, or continents.
Growth Stage	`growth_stage`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Companies at selected maturity stages.
Ecosystem	`ecosystem_id`	id_lookup	✅	`eq`	Companies inside a saved Dealroom ecosystem.
Unicorn	`is_unicorn`	boolean	✅	`eq`	Companies with unicorn status.
Hiring	`is_hiring`	boolean	✅	`eq`	Companies currently flagged as hiring.
Has Founder	`has_founder`	boolean	✅	`eq`	Companies with at least one linked founder record.
Unicorn Date	`date_became_unicorn`	date	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies that became unicorns in a chosen period.
Tags	`tag_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Companies by industry, sector, technology, business model, or other Dealroom tag.

Company Name

Example values:

Tesla
Stripe

Founded Date

Comparison against the recorded founding date. Accepts a year (2024) or year-month (2024-01) value.Example values:

2024-01
2025-06

Company Status

Lifecycle state recorded for each organization — whether they are operational, exited, inactive, etc.Example values:

operational — Operational
acquired — Acquired
closed — Closed
low_activity — Low activity

Location

Location IDs from the Dealroom location taxonomy. Defaults to headquarters; pair with the location_role parameter to filter by founding, office, or any role.Example values:

233 — United States
628061 — London
1297711 — Berlin

Growth Stage

Dealroom growth-stage assignments such as early growth, late growth, and mature. Use the multi-select operators to broaden across several stages.Example values:

3 — Early growth
4 — Late growth
5 — Mature

Ecosystem

Loads the selected ecosystem’s stored filter and applies its rules. The same boundary used by ecosystem pages and landscapes.

Unicorn

Companies with a verified $1B valuation or exit.

Hiring

There are open job positions for this company.

Has Founder

At least one known founder linked to this company.

Unicorn Date

When the company’s valuation crossed $1B. Accepts year or year-month input.Example values:

2024-01
2025-06

Filter	Key	Type	Status	Operators	Description
Dealroom Signal	`signal_rating`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by overall Dealroom Signal rating.
Growth Signal	`signal_growth`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by Dealroom Signal growth score.
Team Signal	`signal_team`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by Dealroom Signal team score.
Timing Signal	`signal_timing`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by Dealroom Signal timing score.
Completeness Signal	`signal_completeness`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by profile completeness score.

Dealroom Signal

Composite score on a 0–100 scale that blends growth, team, timing, and completeness signals. Higher values indicate stronger combined signal.Example values:

70
85

Growth Signal

0–100 component of Dealroom Signal that looks at employee growth in the company.Example values:

70
85

Team Signal

0–100 component of Dealroom Signal that looks at previous performance, experience, serial founders and education.Example values:

70
85

Timing Signal

0–100 component of Dealroom Signal that measures how likely the company is to raise its next round soon.Example values:

70
85

Completeness Signal

0–100 component of Dealroom Signal that measures how complete a company’s profile is.Example values:

70
85

Size (5 filters)

Filter	Key	Type	Status	Operators	Description
Employees	`employee_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by reported headcount.
Valuation	`latest_valuation`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by latest known valuation (currency-aware).
Latest Valuation Date	`latest_valuation_date`	date	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies whose latest valuation was recorded in a chosen period.
Latest Revenue	`latest_revenue`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by latest known revenue (currency-aware).
Website Traffic	`similarweb_traffic`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by SimilarWeb monthly visits.

Employees

Latest reported employee count. Use minimums, maximums, or ranges to separate lean startups, scaleups, and larger organisations.Example values:

10
50
250

Valuation

Latest valuation amount, converted from the requested ?currency= to the underlying USD value before comparison. Useful for valuation bands and unicorn-adjacent searches.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

Latest Valuation Date

Date of the latest known valuation. Accepts year or year-month input.Example values:

2024-01
2025-06

Latest Revenue

Latest reported revenue, converted from the requested ?currency= before comparison. Coverage depends on whether revenue data has been collected for the company.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

Website Traffic

Latest monthly visit count from SimilarWeb. Most useful for consumer, marketplace, or web-first companies; less meaningful for businesses with limited public web presence.Example values:

10000 — 10k
100000 — 100k
1000000 — 1M

Founders (5 filters)

Filter	Key	Type	Status	Operators	Description
Promising Founder	`founder.is_promising_founder`	boolean	✅	`eq`	Companies with at least one founder marked as promising.
Super Founder	`founder.is_super_founder`	boolean	✅	`eq`	Companies with at least one super founder.
Strong Founder	`founder.is_strong_founder`	boolean	✅	`eq`	Companies with at least one strong founder.
Serial Founder	`founder.is_serial_founder`	boolean	✅	`eq`	Companies with at least one serial founder.
Gender	`founder.gender`	enum	✅	`eq` `neq` `in_any` `nin_any`	Companies by recorded gender of linked founders.

Promising Founder

Early in their journey but backed by strong signals: top company or university background, managerial experience, or the right age profile.

Super Founder

Has previously built a company at significant scale (large funding raised or big team).

Strong Founder

Has meaningful prior company-building experience, just below the super-founder threshold.

Serial Founder

Founders who have founded more than one company in Dealroom’s data.

Gender

Looks at gender values on linked founder records. A company is included when at least one associated founder has the selected recorded gender.Example values:

male — Male
female — Female
non_binary — Non-binary
prefer_not_to_say — Prefer not to say

Funding (2 filters)

Filter	Key	Type	Status	Operators	Description
Total Funding	`total_funding`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by total funding raised.
VC Backed	`is_vc_backed`	boolean	✅	`eq`	Companies that have raised venture capital.

Total Funding

Total funding raised across all recorded rounds, excluding debt rounds, IPOs, ICOs, acquisitions, and unverified rounds. Currency-aware: pass ?currency= to filter in a non-USD currency.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

VC Backed

Companies that have raised venture-capital-backed rounds: Early VC, Growth Equity VC, Late VC, Seed, Series A–I, Angel, Convertible, SPAC Private Placement.

Labels (10 filters)

Filter	Key	Type	Status	Operators	Description
Startup	`is_startup`	boolean	✅	`eq`	Companies classified as startups.
Funded	`is_funded`	boolean	✅	`eq`	Companies with any recorded funding event.
Crowdfunding	`is_crowdfunding`	boolean	✅	`eq`	Crowdfunding platforms and crowdfunded organisations.
Government	`is_government`	boolean	✅	`eq`	Government and public-sector organisations.
Non-Profit	`is_non_profit`	boolean	✅	`eq`	Non-profit organisations.
Colt	`is_colt`	boolean	✅	`eq`	Companies labelled Colt.
Thoroughbred	`is_thoroughbred`	boolean	✅	`eq`	Companies labelled Thoroughbred.
Spinout	`is_spinout`	boolean	✅	`eq`	Companies labelled as spinouts.
Titan	`is_titan`	boolean	✅	`eq`	Companies labelled Titan.
Rising Star	`is_rising_star`	boolean	✅	`eq`	Companies flagged as Rising Stars.

Startup

Active companies that are growing and operating in a tech sector.

Funded

Distinguishes companies with at least one financing record or investor from those with none.

Crowdfunding

Dealroom’s crowdfunding label. Apply when crowdfunding entities should be treated separately from venture-funded companies.

Government

Dealroom’s government label. Use to keep public-sector entities in or out of company-style result sets.

Non-Profit

Dealroom’s non-profit label. Apply when commercial and non-profit entities should be separated.

Colt

Startups with the most recent annual revenue between

25M and

100M USD.

Thoroughbred

Startups with annual revenue above $100M.

Spinout

Companies spun out from a university, research lab, or larger company.

Titan

Manually curated list of landmark companies.

Rising Star

Early-stage startups founded in 2020 or later with a Dealroom Signal score of ≥85, not yet a unicorn (valuation under $1B or unknown), and still actively independent.

Sort keys

name · launch_date · employee_count · signal_rating · latest_valuation · latest_revenue · total_funding · total_invested · year_of_exit · alumni_count · alumni_founder_count · alumni_founded_companies_count · alumni_unicorn_companies_count · total_investments_count · founded_companies_total_funding · created_at · updated_at Prefix with - for descending: sort=-name

Investors

Scope: investors — Used on /api/investors for investor search.

Investor Info (7 filters)

Filter	Key	Type	Status	Operators	Description
Investor Name	`name`	text	✅	`eq`	Investors whose name contains the search term.
Location	`location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates — cities, regions, countries, or continents.
Investor Type	`investor_type`	enum	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Investors by category.
Investor Status	`company_status`	enum	✅	`eq` `neq` `in_any` `nin_any`	Lifecycle status.
Founded Date	`launch_date`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Year or period when the organization was launched.
Closing Date	`closing_date`	date	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Funds that closed in a chosen period.
Ecosystem	`ecosystem_id`	id_lookup	✅	`eq`	Investors inside a saved Dealroom ecosystem.

Investor Name

Example values:

Sequoia
Atomico

Location

Location IDs from the Dealroom location taxonomy. Defaults to headquarters; pair with the location_role parameter to filter by founding, office, or any role.Example values:

233 — United States
628061 — London
1297711 — Berlin

Investor Type

Investors are categorized by how they operate and deploy capital — venture capital, angel, family office, private equity, accelerator, and more.Example values:

venture_capital — Venture capital
angel — Angel
private_equity — Private equity
family_office — Family office

Investor Status

Lifecycle state recorded for each organization. Most scouting work stays on operational; including the other states surfaces exits and inactive records.Example values:

operational — Operational
acquired — Acquired
closed — Closed
low_activity — Low activity

Founded Date

Comparison against the recorded launch date. Accepts year or year-month input.Example values:

2024-01
2025-06

Closing Date

Date the fund closed its fundraising. Accepts year or year-month input.Example values:

2024-01
2025-06

Ecosystem

Loads the selected ecosystem’s stored filter and applies its rules to investor results. Aligns investor discovery with an ecosystem boundary.

Activity (6 filters)

Filter	Key	Type	Status	Operators	Description
Deal Size (Min)	`min_deal_size`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by their minimum deal size.
Deal Size (Max)	`max_deal_size`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by their maximum deal size.
Portfolio Size	`total_investments_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by number of recorded investments.
Total Invested	`total_invested`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by total invested amount across their portfolio.
Investment Stage	`investor_stage_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Investors by the company stages they prefer to back.
Experience	`tag_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Investors with experience in selected industries, sectors, technologies, or business models.

Deal Size (Min)

Filters by the smallest deal size recorded for the investor.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

Deal Size (Max)

Filters by the largest deal size recorded for the investor.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

Portfolio Size

Higher values can indicate more active or historically prolific investors, depending on data coverage.Example values:

10
50
250

Total Invested

Cumulative invested amount across the investor’s portfolio. Currency-aware: pass ?currency= to filter in a non-USD currency.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

Investment Stage

Maps investors based on the growth stage of the companies they usually back.Example values:

3 — Early growth
4 — Late growth
5 — Mature

Experience

Tags linked to the investor based on their portfolio and stated focus. Use for sector, industry, technology, or business-model fit when building investor shortlists.Example values:

126403 — Fintech
2268001 — AI Agents
10202 — AI

Sort keys

name · launch_date · investor_rank · total_invested · total_investments_count · min_deal_size · max_deal_size · employee_count · created_at · updated_at Prefix with - for descending: sort=-name

Transactions

Scope: transactions — Used on /api/transactions for funding rounds.

Company Info (9 filters)

Filter	Key	Type	Status	Operators	Description
Tags	`tag_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Transactions involving companies in selected industries, sectors, technologies, or business models.
Location	`location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Transactions by the related company’s location.
Growth Stage	`growth_stage`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Transactions by the related company’s maturity stage.
Company Name	`name`	text	✅	`eq`	Transactions tied to a company whose name contains the search term.
Founded Date	`launch_date`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Year or period when the organization was launched.
EV/Revenue	`ev_revenue_multiple`	numeric	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Transactions filtered by their enterprise-value-to-revenue multiple.
EV/EBITDA	`ev_ebitda_multiple`	numeric	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Transactions filtered by their enterprise-value-to-EBITDA multiple.
EV/Profit	`ev_profit_multiple`	numeric	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Transactions filtered by their enterprise-value-to-profit multiple.
Ecosystem	`ecosystem_id`	id_lookup	✅	`eq`	Transactions whose related company belongs to a Dealroom ecosystem.

Location

Selected geographies where the organization is headquartered (default) — cities, regions, countries, or continents. Pair with location_role to filter by founding, office, or any role instead.Example values:

233 — United States
628061 — London
1297711 — Berlin

Growth Stage

Compares deal activity across early, breakout, late, and mature growth-stage companies.Example values:

3 — Early growth
4 — Late growth
5 — Mature

Company Name

Example values:

OpenAI
Stripe

Founded Date

Useful for understanding whether deal activity is concentrated in newer companies or older cohorts. Accepts a year (2024) or year-month (2024-01) value.Example values:

2018
2024

EV/Revenue

The ratio of a company’s enterprise value to its revenue at the time of the transaction. Useful for benchmarking valuations across deals where revenue figures are available.Example values:

3 — 3x
10 — 10x

EV/EBITDA

The ratio of enterprise value to EBITDA at the time of the transaction. A profitability-based valuation metric — useful when comparing deals where earnings data is available.Example values:

3 — 3x
10 — 10x

EV/Profit

The ratio of enterprise value to profit at the time of the transaction. A useful benchmarking lens when profit is a more meaningful measure than revenue or EBITDA.Example values:

3 — 3x
10 — 10x

Ecosystem

Uses the same filters as this ecosystem’s pages and landscapes.

Round (8 filters)

Filter	Key	Type	Status	Operators	Description
Round Type	`round_type`	enum	✅	`eq` `neq` `in_any` `nin_any`	Transactions by reported round type.
Standardized Round	`standardized_round`	enum	✅	`eq` `neq` `in_any` `nin_any`	Normalized round labels, accounting for deal size, company age, and funding history.
Round Size	`amount`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Transactions by round size.
Valuation	`valuation`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Transactions by valuation.
VC Round	`is_vc_round`	boolean	✅	`eq`	Rounds backed by venture capital.
Funding Round	`is_funding_round`	boolean	✅	`eq`	Records that represent funding rounds.
Verified	`is_verified`	boolean	✅	`eq`	Transactions that have been verified by Dealroom.
Round Date	`date`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Transactions in a chosen time period.

Round Type

From early grants and angel rounds through Series A–I, IPOs, buyouts, debt, and acquisitions — covering the full range of funding and transaction types.Example values:

SEED — Seed
SERIES A — Series A
SERIES B — Series B

Standardized Round

Assigns a consistent round label based on the announced name, deal size, company age, and funding history. Useful when source data uses inconsistent labels.Example values:

seed — Seed
series_a — Series A
pre_seed — Pre-seed
series_b — Series B

Round Size

Filter by the amount assigned to the transaction round. Currency-aware: pass ?currency= to filter in a non-USD currency.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

Valuation

Recorded valuation on the transaction. Currency-aware: pass ?currency= to filter in a non-USD currency.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

VC Round

Transactions that are specifically VC rounds: Early VC, Growth Equity VC, Late VC, Seed, Series A–I, Angel, Convertible, SPAC Private Placement.

Funding Round

Distinguishes financings from acquisitions, mergers, and other transaction records in the same dataset.

Verified

Higher-confidence subset of the transaction data. Use when accuracy matters more than coverage.

Round Date

Comparison against the transaction date. Accepts year or year-month input.Example values:

2024-01
2025-06

Sort keys

date · amount · round_type Prefix with - for descending: sort=-date

People

Scope: people — Used on /api/founders for people/founder search.

Personal Info (4 filters)

Filter	Key	Type	Status	Operators	Description
Name	`name`	text	✅	`eq`	People whose name contains the search term.
Location	`location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	People based in selected geographies.
Gender	`gender`	enum	✅	`eq` `neq` `in_any` `nin_any`	People by recorded gender.
Ecosystem	`ecosystem_id`	id_lookup	✅	`eq`	People inside a Dealroom ecosystem.

Name

Example values:

Ada
John

Location

People based in selected geographies — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Gender

Reflects available profile data. Coverage varies and not all people have a recorded gender value.Example values:

male — Male
female — Female
non_binary — Non-binary
prefer_not_to_say — Prefer not to say

Ecosystem

Uses the same filters as this ecosystem’s pages and landscapes.

Founder Status (5 filters)

Filter	Key	Type	Status	Operators	Description
Founder	`is_founder`	boolean	✅	`eq`	People flagged as founders.
Serial Founder	`is_serial_founder`	boolean	✅	`eq`	Founders who have founded more than one company.
Promising Founder	`is_promising_founder`	boolean	✅	`eq`	Founders flagged as promising by Dealroom.
Super Founder	`is_super_founder`	boolean	✅	`eq`	Founders flagged as super founders by Dealroom.
Strong Founder	`is_strong_founder`	boolean	✅	`eq`	Founders flagged as strong founders by Dealroom.

Founder

The main control for founder-only people lists. Use as a precondition before applying further founder-specific filters.

Promising Founder

Early in their journey but backed by strong signals: top company or university background, managerial experience, or the right age profile.

Super Founder

Has previously built a company at significant scale (large funding raised or big team).

Strong Founder

Has meaningful prior company-building experience, just below the super-founder threshold.

Sort keys

name · launch_date · signal_rating · created_at · updated_at Prefix with - for descending: sort=-name

Universities

Scope: universities — Used on /api/universities for university search.

University Info (3 filters)

Filter	Key	Type	Status	Operators	Description
University Name	`name`	text	✅	`eq`	Universities whose name contains the search term.
University Location	`location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Universities based in selected geographies.
Ecosystem	`ecosystem_id`	id_lookup	✅	`eq`	Universities inside a Dealroom ecosystem.

University Name

Example values:

Stanford
Oxford

University Location

Universities based in selected geographies — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Ecosystem

Uses the same filters as this ecosystem’s pages and landscapes.

Sort keys

News

Scope: news — Used on /api/news for news article search.

Article (5 filters)

Filter	Key	Type	Status	Operators	Description
Source	`source`	text	✅	`eq` `neq` `in_any` `nin_any`	News articles by source system or publisher.
Article Type	`article_type`	text	✅	`eq` `neq` `in_any` `nin_any`	News articles by type.
Publish Date	`publish_date`	date	✅	`gte` `lte`	News articles published in a chosen window.
Amount	`amount`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	News articles tied to a deal amount in the selected range.
Round Type	`round_type`	enum	✅	`eq` `neq` `in_any` `nin_any`	News articles mentioning a specific funding round type.

Source

Filters by the article source value. Useful when source quality or coverage matters.Example values:

Opoint

Article Type

News articles by type — product announcements, financial milestones, funding rounds, etc.Example values:

Product announcements
Financial milestones
Funding rounds

Publish Date

Comparison against the article publish timestamp. Accepts ISO 8601 timestamps.Example values:

2024-01-01T00:00:00Z — 2024-01-01
2025-01-01T00:00:00Z — 2025-01-01

Amount

Mentioned deal amount extracted from the article. Currency-aware: pass ?currency= to filter in a non-USD currency.Example values:

1000000 — 1M
10000000 — 10M
100000000 — 100M

Round Type

From early grants and angel rounds through Series A–I, IPOs, buyouts, debt, and acquisitions — covering the full range of funding and transaction types.Example values:

SEED — Seed
SERIES A — Series A
SERIES B — Series B

Entity (3 filters)

Filter	Key	Type	Status	Operators	Description
Mentioned Entities	`entity_id`	numeric	✅	`eq` `in_any`	News articles that mention a specific entity.
Location	`location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	News articles about entities in selected geographies.
Sector	`sector`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	News articles about entities in selected sectors.

Mentioned Entities

The most direct way to retrieve articles about known Dealroom entities.Example values:

6368814 — 10x Science

Location

Mentioned entities based in selected geographies (default: headquarters) — cities, regions, countries, or continents. Pair with location_role to filter by founding, office, or any role instead.Example values:

233 — United States
628061 — London
1297711 — Berlin

Sector

Sectors are cross-cutting themes that span multiple industries (e.g. climate tech, industrial robotics, advanced materials).Example values:

2144601 — Regtech Fintech
2206101 — Climate Fintech

Sort keys

publish_date · amount Prefix with - for descending: sort=-publish_date

Documentation Index

​Companies

​Company Name

​Founded Date

​Company Status

​Location

​Growth Stage

​Ecosystem

​Unicorn

​Hiring

​Has Founder

​Unicorn Date

​Tags

​Dealroom Signal

​Growth Signal

​Team Signal

​Timing Signal

​Completeness Signal

​Employees

​Valuation

​Latest Valuation Date

​Latest Revenue

​Website Traffic

​Promising Founder

​Super Founder

​Strong Founder

​Serial Founder

​Gender

​Total Funding

​VC Backed

​Startup

​Funded

​Crowdfunding

​Government

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