Filters & Sorting - Dealroom API

You can also discover the available filters programmatically with GET /reference/filters?scope={scope}. For id_lookup and enum filters, fetch the accepted values from GET /reference/filters/{key}/values. The Dealroom API supports 141 filters across 9 scopes. Use the filter query parameter to apply filters, and the sort parameter to order results.

Value types

The Type column below — and the type field returned by GET /reference/filters — uses these values:

Type	Meaning
`id_lookup`	An ID you resolve by search — fetch the valid values (and their labels) from `GET /reference/filters/{key}/values`. Covers entity UUIDs, location IDs, tag IDs, and similar.
`enum`	A fixed set of string values; also discoverable via the `/values` endpoint.
`numeric`	A number.
`boolean`	`true` or `false`.
`date`	An ISO 8601 date or period.
`text`	Free-text search.

A · suffix adds display context: · currency (monetary value), · year (year-granular), · count (whole number).

Companies

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

Company Info (17 filters)

Filter	Key	Type	Status	Operators	Description
Specific Companies	`id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Pick specific companies by name (entity ids, UUID).
Company Name	`name`	text	✅	`eq` `neq`	Companies whose name contains the search term.
Smart Keyword	`semantic_keyword`	text	✅	`eq`	Rank companies by how closely they match the meaning of your phrase.
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.
HQ location	`hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Founding location	`founding_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Office location	`office_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Founding or HQ location	`founding_or_hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Location (any role)	`any_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Area	`map_area`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	A specific area within the active ecosystem’s map.
Growth Stage	`growth_stage`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Companies at selected maturity stages.
Hiring	`is_hiring`	boolean	✅	`eq`	There are open job positions for this company.
Has Founder	`has_founder`	boolean	✅	`eq`	At least one known founder linked to this company.
Unicorn Date	`date_became_unicorn`	date	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies that became unicorns in a chosen period.
Has Patents	`has_patents`	boolean	✅	`eq`	Companies that hold at least one patent.
Tags	`taxonomy_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Companies by industry, sector, technology, business model, or other Dealroom tag.

Specific Companies

Example values:

55555555-5555-5555-5555-555555555555 — Example entity

Company Name

Example values:

Tesla
Stripe

Smart Keyword

Ranks companies by how closely their sector matches the meaning of your keyword, not just exact-match. Replaces sorting, and the top 1000 best matches are shown.Example values:

Small modular reactors
Space rockets
AI language translation

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

Discover the full set of valid values via GET /reference/filters/company_status/values.

HQ 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

Founding 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

Office 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

Founding or HQ 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

Location (any role)

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

Area

Matches entities assigned to one of the active ecosystem’s own geofile sub-areas — the same areas shown on the ecosystem’s map/choropleth. Only meaningful with an active ecosystem; matches nothing otherwise.

Growth Stage

Dealroom growth-stage assignments: early stage, breakout stage, late stage and mature. Use the multi-select operators to broaden across several stages. Values are growth-stage tag IDs from /reference/filters/growth_stage/values.Example values:

212 — Early stage
612 — Breakout stage
312 — Late stage
412 — Mature

Hiring

Profile-level hiring signal rather than a complete jobs-market feed. Coverage depends on the company maintaining its profile.

Has Founder

Useful as a precondition before applying founder-specific filters, since companies without linked founders will otherwise drop out of the result silently.

Unicorn Date

Year when valuation of a company with Unicorn status is > $1BExample values:

2024-01
2025-06

Filter	Key	Type	Status	Operators	Description
Labels	`classification`	enum	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Companies by Dealroom label (unicorn, VC backed, startup, …).

Labels

Dealroom labels, the values of classifications[]. unicorn: a verified $1B valuation or exit. vc_backed: raised a venture-capital round (Seed, Series A–I, Early / Late / Growth Equity VC, Angel, Convertible, SPAC Private Placement). funded: at least one financing record or investor. startup: a company with a website, not “Mature”, not closed, not tagged “Outside Tech”. colt: annual revenue $25M–$100M (not a thoroughbred). thoroughbred: individually verified as reaching $100M revenue — a curated list that lags latest_revenue both ways. titan: curated landmark companies. rising_star: founded 2020 or later, Signal ≥85, valued under $1B, independent. spinout: spun out of a university, lab or company. exited: acquisition, IPO or merger. pe_owned: majority-owned by a private equity firm. nin_any / nin_all count an unset label as absent.Example values:

unicorn — Unicorn
vc_backed — VC backed
startup — Startup

Discover the full set of valid values via GET /reference/filters/classification/values.

Signals (5 filters)

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 (6 filters)

Filter	Key	Type	Status	Operators	Description
Employees	`employees_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.
Latest Valuation Date	`latest_valuation_date`	date	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies whose latest valuation was recorded in a chosen period.
Valuation Year	`valuation_year`	numeric · year	✅	`eq` `neq` `gt` `gte` `lt` `lte` `in_any` `nin_any`	Companies with a valuation recorded in a chosen year (any valuation on record, not just the latest).
Latest Revenue	`latest_revenue`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Companies by latest known revenue.
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.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

Valuation Year

Matches any valuation row for the company in the given year, unlike Latest Valuation Date which only looks at the most recent valuation.Example values:

2020
2024

Latest Revenue

Most recent revenue figure on record, which may be several years old. Sorting by it therefore compares different fiscal years across companies.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 (3 filters)

Filter	Key	Type	Status	Operators	Description
Founder Labels	`founder.classification`	enum	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Companies with at least one founder carrying the label.
Gender	`founder.gender`	enum	✅	`eq` `neq` `in_any` `nin_any`	Companies by recorded gender of linked founders.
Founder University	`founder__university.id`	id_lookup	✅	`eq` `in_any`	Companies with at least one founder who studied at one of the selected universities.

Founder Labels

Founder-quality labels. super_founder: previously built a company at significant scale. strong_founder: meaningful company-building experience, just below super. promising_founder: early, with strong signals (top company or university, managerial experience, age profile). serial_founder: founded more than one company.Example values:

super_founder — Super founder
serial_founder — Serial founder

Discover the full set of valid values via GET /reference/filters/founder.classification/values.

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

Discover the full set of valid values via GET /reference/filters/founder.gender/values.

Founder University

Traverses founder → education links: matches any company with at least one founder whose education record names one of the selected university entities. Select universities from the autocomplete dropdown; values are university entity UUIDs.Example values:

11111111-1111-1111-1111-111111111111 — Example University

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.
Investor Name	`investor_name`	text	✅	`eq` `neq`	Companies backed by an investor whose name contains the search term.

Total Funding

Total funding raised across all recorded rounds, excluding debt rounds, IPOs, ICOs, acquisitions and unverified rounds.Example values:

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

Investor Name

Searches through funding round participants: matches any company that has received investment from an investor whose name contains the given substring.Example values:

Sequoia
Andreessen

Sort keys

added_at · alumni_count · alumni_founded_companies_count · alumni_founders_count · alumni_unicorn_companies_count · employee_count_1y_growth · employees_count · founded_companies_total_funding · investments_count · latest_revenue · latest_valuation · launch_date · name · patent_value_total · patents_count · signal_rating · spinouts_count · total_funding · total_invested · updated_at · year_of_exit Default order: -launch_date. Prefix a key with - for descending order.

Investors

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

Investor Info (14 filters)

Filter	Key	Type	Status	Operators	Description
Specific Investors	`id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Pick specific investors by name (entity ids, UUID).
Investor Name	`name`	text	✅	`eq` `neq`	Investors whose name contains the search term.
Roles	`roles`	enum	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Investors by role (investor, limited partner, fund manager).
HQ location	`hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Founding location	`founding_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Office location	`office_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Founding or HQ location	`founding_or_hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Location (any role)	`any_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Selected geographies where the organization operates: cities, regions, countries, or continents.
Area	`map_area`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	A specific area within the active ecosystem’s map.
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`	Investors that closed in a chosen period.
Added to Dealroom	`added_at`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by when they were added to Dealroom.

Specific Investors

Example values:

55555555-5555-5555-5555-555555555555 — Example entity

Investor Name

Example values:

Sequoia
Atomico

Roles

Example values:

limited_partner — Limited partner
fund_manager — Fund manager

Discover the full set of valid values via GET /reference/filters/roles/values.

HQ 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

Founding 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

Office 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

Founding or HQ 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

Location (any role)

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

Area

Investor Type

Investors are categorized by how they operate and deploy capital.Example values:

venture_capital — Venture capital
angel_fund — Angel fund
private_equity — Private equity
family_office — Family office

Discover the full set of valid values via GET /reference/filters/investor_type/values.

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

Discover the full set of valid values via GET /reference/filters/company_status/values.

Founded Date

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

2024-01
2025-06

Closing Date

Date the investor stopped operating. Accepts year or year-month input.Example values:

2024-01
2025-06

Added to Dealroom

Date the investor’s profile was created in Dealroom. Accepts year or year-month input.Example values:

2024
2025-06

Activity (13 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.
Rounds Participated In	`investments_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by the number of funding rounds they took part in.
Portfolio Companies	`portfolio_companies_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by the number of companies they invested in.
Participated in rounds totaling	`total_invested`	numeric · currency	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Total size of the funding rounds the investor participated in.
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	`investor_experience_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Investors with experience in selected industries, sectors, technologies, or business models.
Location Experience	`invested_in.location`	id_lookup	✅	`eq` `in_any`	Investors who backed companies in the selected locations.
Round Experience	`invested_in.round_type`	enum	✅	`eq` `in_any`	Investors who took part in rounds of the selected type.
Preferred Round	`preferred_round`	enum	✅	`eq` `neq` `in_any` `nin_any`	Investors by their preferred investment round type.
Last Round Date	`last_investor_round_date`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Investors by the date of their most recent investment round.
Company Invested In	`portfolio_company_id`	id_lookup	✅	`eq` `neq`	Investors who have invested in a specific company.
LP Investments Of	`lp_investor_id`	id_lookup	✅	`eq` `neq`	Investors the given investor backs as a limited partner.

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

Rounds Participated In

Counts every funding round the investor participated in, so several rounds in the same company count separately. Higher values indicate more active investors.Example values:

10
50
250

Portfolio Companies

Counts the distinct companies an investor has backed across all its funding rounds. Several rounds in the same company count once.Example values:

10
50
250

Participated in rounds totaling

Sum of the full round amounts of every round the investor took part in, not the investor’s own ticket size.Example values:

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

Investment Stage

Maps investors based on the growth stage of the companies they usually back. Values are growth-stage tag IDs from /reference/filters/growth_stage/values.Example values:

212 — Early growth
312 — Late growth
412 — 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

Location Experience

Matches investors with at least one funding round in a company based in the selected countries, regions or cities, e.g. anyone who invested in an Armenian company.Example values:

233 — United States
628061 — London

Round Experience

Matches investors with at least one funding round of the selected type, e.g. Seed or Series A.Example values:

SEED — Seed
SERIES A — Series A

Discover the full set of valid values via GET /reference/filters/invested_in.round_type/values.

Preferred Round

Filters by the investor’s stated or inferred round preference — the stage at which they most commonly invest.Example values:

SEED — Seed
SERIES A — Series A
EARLY VC — Early VC

Discover the full set of valid values via GET /reference/filters/preferred_round/values.

Last Round Date

Comparison against the date of the investor’s most recent portfolio round. Accepts year or year-month input. Useful for identifying active vs. inactive investors.Example values:

2024
2023-06

Company Invested In

Returns all investors who appear as a participant in at least one funding round of the given company entity. Select a company from the autocomplete dropdown.Example values:

55555555-5555-5555-5555-555555555555 — Acme Corp

LP Investments Of

Returns all investors that have the given investor among their known limited partners — the LP-side view of the lp_investments graph. Select an investor from the autocomplete dropdown.Example values:

55555555-5555-5555-5555-555555555555 — Acme Capital

Sort keys

added_at · employees_count · exit_pct · exit_total_value_usd · exits_count · investments_count · investor_rank · launch_date · max_deal_size · min_deal_size · name · portfolio_match_count · portfolio_match_invested · portfolio_total_valuation_usd · total_invested · updated_at

portfolio_match_count: requires portfolio_count_tag or portfolio_count_location, or a filter on invested_in.taxonomy_id or invested_in.location
portfolio_match_invested: requires portfolio_count_tag or portfolio_count_location, or a filter on invested_in.taxonomy_id or invested_in.location

Default order: investor_rank. Prefix a key with - for descending order.

Transactions

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

Company Info (16 filters)

Filter	Key	Type	Status	Operators	Description
Tags	`taxonomy_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Transactions involving companies in selected industries, sectors, technologies, or business models.
HQ location	`hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Transactions by the related company’s location.
Founding location	`founding_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Transactions by the related company’s location.
Office location	`office_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Transactions by the related company’s location.
Founding or HQ location	`founding_or_hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Transactions by the related company’s location.
Location (any role)	`any_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Transactions by the related company’s location.
Area	`map_area`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	A specific area within the active ecosystem’s map.
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 Status	`company_status`	enum	✅	`eq` `neq` `in_any` `nin_any`	Transactions by the related company’s lifecycle status.
Company Name	`name`	text	✅	`eq` `neq`	Transactions tied to a company whose name contains the search term.
Investor Name	`investor_name`	text	✅	`eq` `neq`	Transactions involving an investor whose name contains the search term.
Investors	`investor_id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Transactions a specific investor participated in.
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.

HQ location

Selected geographies where the organization operates — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Founding location

Selected geographies where the organization operates — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Office location

Selected geographies where the organization operates — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Founding or HQ location

Selected geographies where the organization operates — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Location (any role)

Selected geographies where the organization operates — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Area

Growth Stage

Compares deal activity across early, breakout, late, and mature growth-stage companies. Values are growth-stage tag IDs from /reference/filters/growth_stage/values.Example values:

212 — Early stage
612 — Breakout stage
312 — Late stage
412 — Mature

Company Status

Filters by the status of the related company, not the transaction record itself: operational, acquired, closed or low activity.Example values:

operational — Operational
closed — Closed

Discover the full set of valid values via GET /reference/filters/company_status/values.

Company Name

Example values:

OpenAI
Stripe

Investor Name

Searches through the list of investors in each round: matches any transaction where at least one participating investor’s name contains the given substring.Example values:

Sequoia
Andreessen

Investors

Matches rounds by participating investor entity UUID. Exclusion (neq, nin_any) drops every round any listed investor joined, so a round backed by one listed investor and one unlisted investor is excluded.Example values:

d8795151-5792-40da-8cd9-8ede02bc58de — Index Ventures
1c586454-f082-400a-a962-6bf5bfb222ef — Accel

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

Round (11 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.
Round Size (USD, fixed)	`amount_usd`	numeric	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Round size in real US dollars, unaffected by this ecosystem’s currency.
Round Year	`year`	numeric · year	✅	`eq` `neq` `gt` `gte` `lt` `lte` `in_any` `nin_any`	Transactions by the year the round itself closed.
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.
Exit	`is_exit`	boolean	✅	`eq`	Rounds that were the company’s exit event.
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

Discover the full set of valid values via GET /reference/filters/round_type/values.

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

Discover the full set of valid values via GET /reference/filters/standardized_round/values.

Round Size

Filter by the amount assigned to the transaction round.Example values:

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

Round Size (USD, fixed)

Most round-size figures on this site are shown in this ecosystem’s own currency (for example, GBP for a UK-based ecosystem). This filter ignores that and always compares against the round’s actual US-dollar amount, so a cutoff like “$15M or more” means the same real amount everywhere. Use the regular “Round Size” filter instead if you want the cutoff to follow this ecosystem’s own currency.Example values:

15000000 — 15M
100000000 — 100M

Round Year

The round’s own year — not the company’s launch year or latest valuation year.Example values:

2020
2024

Valuation

Recorded valuation on the transaction.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.

Exit

Marks the round as the company’s exit event: Acquisition, Buyout, Merger, or IPO.

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

amount · date · round_type · valuation Default order: -date. Prefix a key with - for descending order.

People

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

Personal Info (5 filters)

Filter	Key	Type	Status	Operators	Description
Entity ID	`id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Fetch specific people by their entity id (UUID).
Name	`name`	text	✅	`eq` `neq`	People whose name contains the search term.
Location	`hq_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.
Background	`taxonomy_id`	id_lookup	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	People by professional or academic background.

Entity ID

Example values:

55555555-5555-5555-5555-555555555555 — Example entity

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

Discover the full set of valid values via GET /reference/filters/gender/values.

Background

Example values:

114 — Technical

Founder Status (2 filters)

Filter	Key	Type	Status	Operators	Description
Roles	`roles`	enum	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	People by role (founder, executive, partner, investor).
Founder Labels	`classification`	enum	✅	`eq` `neq` `in_any` `in_all` `nin_any` `nin_all`	Founders by Dealroom founder-quality label.

Roles

Stackable roles, the values of roles[]. roles[in_any]:founder is the main control for founder-only people lists.Example values:

founder — Founder
executive — Executive

Discover the full set of valid values via GET /reference/filters/roles/values.

Founder Labels

super_founder: previously built a company at significant scale. strong_founder: meaningful company-building experience, just below super. promising_founder: early, with strong signals (top company or university, managerial experience, age profile). serial_founder: founded more than one company.Example values:

serial_founder — Serial founder
super_founder — Super founder

Discover the full set of valid values via GET /reference/filters/classification/values.

Experience (2 filters)

Filter	Key	Type	Status	Operators	Description
Work Experience	`employer_id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	People who have worked at any of the selected companies.
Current Employer	`current_employer_id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	People currently employed at any of the selected companies.

Work Experience

Matches any person with a past or current people_entities link to one of the selected employer entities. Select companies from the autocomplete dropdown.Example values:

55555555-5555-5555-5555-555555555555 — Google

Current Employer

Restricts to active (is_past = false) employment records only. Select companies from the autocomplete dropdown.Example values:

66666666-6666-6666-6666-666666666666 — Google

Founder Info (1 filter)

Filter	Key	Type	Status	Operators	Description
Last Founded Company Launch Date	`last_founded_entity_launch_date`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Founders by when their most recently founded company was launched.

Last Founded Company Launch Date

Comparison against the launch year of the person’s last founded entity (via the lastFoundedEntityId denormalized FK). Accepts year (2020) or year-month (2020-06) input.Example values:

2020
2020-06

Sort keys

added_at · founded_companies_total_funding · name · signal_rating · updated_at Default order: -signal_rating. Prefix a key with - for descending order.

Universities

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

University Info (12 filters)

Filter	Key	Type	Status	Operators	Description
Entity ID	`id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Fetch specific universities by their entity id (UUID).
University Name	`name`	text	✅	`eq` `neq`	Universities whose name contains the search term.
HQ location	`hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Universities based in the selected geographies.
Founding location	`founding_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Universities based in the selected geographies.
Office location	`office_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Universities based in the selected geographies.
Founding or HQ location	`founding_or_hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Universities based in the selected geographies.
Location (any role)	`any_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Universities based in the selected geographies.
Alumni Count	`alumni_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Universities by total number of alumni.
Alumni Founders	`alumni_founders_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Universities by number of alumni who have founded companies.
Companies Founded	`alumni_founded_companies_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Universities by number of companies founded by their alumni.
Alumni Unicorns	`alumni_unicorn_companies_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Universities by number of unicorn companies founded by their alumni.
Has Patents	`has_patents`	boolean	✅	`eq`	Universities that hold at least one patent.

Entity ID

Example values:

55555555-5555-5555-5555-555555555555 — Example entity

University Name

Example values:

Stanford
Oxford

HQ location

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

233 — United States
628061 — London
1297711 — Berlin

Founding location

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

233 — United States
628061 — London
1297711 — Berlin

Office location

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

233 — United States
628061 — London
1297711 — Berlin

Founding or HQ location

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

233 — United States
628061 — London
1297711 — Berlin

Location (any role)

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

233 — United States
628061 — London
1297711 — Berlin

Alumni Count

Total recorded alumni count for the university. Use range operators to find large or niche alumni networks.Example values:

1000
10000

Alumni Founders

Number of alumni recorded as founders in Dealroom. Higher values indicate entrepreneurial output from the institution.Example values:

10
100

Companies Founded

Total companies in Dealroom whose founders include alumni of this university.Example values:

10
100

Alumni Unicorns

Number of $1B+ companies whose founders include alumni of this university.Example values:

1
10

Sort keys

Government & NGO

Scope: gov_ngo — Used on /data/gov-ngo for government & NGO search.

Organization Info (10 filters)

Filter	Key	Type	Status	Operators	Description
Entity ID	`id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Fetch specific government & NGO entities by their entity id (UUID).
Organization Name	`name`	text	✅	`eq` `neq`	Government bodies and NGOs whose name contains the search term.
HQ location	`hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Government bodies and NGOs based in the selected geographies.
Founding location	`founding_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Government bodies and NGOs based in the selected geographies.
Office location	`office_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Government bodies and NGOs based in the selected geographies.
Founding or HQ location	`founding_or_hq_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Government bodies and NGOs based in the selected geographies.
Location (any role)	`any_location`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Government bodies and NGOs based in the selected geographies.
Founded Date	`launch_date`	date · year	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Year or period when the organization was launched.
Employees	`employees_count`	numeric · count	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Government bodies and NGOs by reported headcount.
Has Patents	`has_patents`	boolean	✅	`eq`	Government bodies and NGOs that hold at least one patent.

Entity ID

Example values:

55555555-5555-5555-5555-555555555555 — Example entity

Organization Name

Example values:

European Commission
Red Cross

HQ location

Government bodies and NGOs based in selected geographies — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Founding location

Government bodies and NGOs based in selected geographies — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Office location

Government bodies and NGOs based in selected geographies — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Founding or HQ location

Government bodies and NGOs based in selected geographies — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Location (any role)

Government bodies and NGOs based in selected geographies — cities, regions, countries, or continents.Example values:

233 — United States
628061 — London
1297711 — Berlin

Founded Date

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

2024-01
2025-06

Employees

Latest reported employee count. Use minimums, maximums, or ranges to separate small and large organizations.Example values:

10
50
250

Sort keys

News

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

Article (7 filters)

Filter	Key	Type	Status	Operators	Description
Source	`source`	text	✅	`eq` `neq` `in_any` `nin_any`	News article source — currently always `dealroom`.
Article Type	`article_type`	enum	✅	`eq` `neq` `in_any` `nin_any`	News articles by type.
News Type	`news_type`	enum	✅	`eq` `neq` `in_any` `nin_any`	News articles tagged with a news-type label.
Publish Date	`published_at`	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.
Search	`q`	text	✅	`eq`	Full-text + fuzzy search across headline and body.

Source

All next-gen news is in-house editorial, so every article’s source is dealroom. Retained for forward-compatibility if syndicated sources return.Example values:

dealroom

Article Type

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

Product announcements
Financial milestones
Funding rounds

Discover the full set of valid values via GET /reference/filters/article_type/values.

News Type

Matches any of a note’s news-type tags (note_news_types.name), not just the single article_type derived from the first known key. A note tagged both Funding rounds and Fintech matches either value.Example values:

Funding rounds
Fintech

Discover the full set of valid values via GET /reference/filters/news_type/values.

Publish Date

News articles published in a chosen window.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.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

Discover the full set of valid values via GET /reference/filters/round_type/values.

Search

Matches headline and body text — full-text ranked, with a trigram fuzzy fallback on the headline so typos (‘quantom computing’, ‘Glasgo’) still surface the right stories. Forces relevance ordering (whole-word/phrase headline match, then ts_rank_cd, then trigram); pages by cursor within the first 1000 ranked results.Example values:

quantum computing

Entity (3 filters)

Filter	Key	Type	Status	Operators	Description
Mentioned Entities	`entity_id`	id_lookup	✅	`eq` `neq` `in_any` `nin_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.
Tags	`taxonomy_id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	News articles about entities in selected industries, sectors, technologies, or other Dealroom tags.

Mentioned Entities

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

345d1ab6-33df-4759-9e17-0d0c0ec9ab1c — 10x Science

Location

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

233 — United States
628061 — London
1297711 — Berlin

Sort keys

amount · importance_score · published_at Default order: -published_at. Prefix a key with - for descending order.

Jobs

Scope: jobs — Used on /data/jobs for job opening search.

Job (6 filters)

Filter	Key	Type	Status	Operators	Description
Hiring Company	`entity_id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Job openings for a specific hiring entity.
Source	`source`	text	✅	`eq` `neq` `in_any` `nin_any`	Job openings by source / provider.
Country	`country_id`	numeric	✅	`eq` `in_any`	Job openings by country location ID.
City	`city_id`	numeric	✅	`eq` `in_any`	Job openings by city location ID.
Region / State	`region_id`	numeric	✅	`eq` `in_any`	Job openings by region or state location ID.
Posted Date	`posted_at`	date	✅	`gte` `lte`	Job openings posted in a chosen window.

Hiring Company

The most direct way to retrieve active openings for a known Dealroom company.Example values:

81f9478f-f016-4302-a9dd-1dfef280a9d8 — Dwelly

Source

Filters by the posting source (e.g. linkedin, predictleads).Example values:

linkedin

Country

Matches jobs.country_unique_id against a locations.id for a country row. Resolve IDs via GET /reference/filters/location/values?q=<country>.Example values:

133 — Germany

City

Matches jobs.city_unique_id against a locations.id for a city row.Example values:

1297711 — Berlin

Region / State

Matches city-region IDs via jobs.city_region_unique_ids or state/province IDs via jobs.state_unique_id.Example values:

8205

Posted Date

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

2024-01-01T00:00:00Z — 2024-01-01

Sort keys

posted_at Default order: -posted_at. Prefix a key with - for descending order.

Funds

Scope: funds — Used on /data/funds for fund vehicle search.

Fund (4 filters)

Filter	Key	Type	Status	Operators	Description
Fund Type	`fund_type`	enum	✅	`eq` `neq` `in_any` `nin_any`	Funds by category.
Is Closed	`is_closed`	boolean	✅	`eq` `neq`	Funds by close status (true = closed to new commitments).
Amount	`amount`	numeric	✅	`eq` `neq` `gt` `gte` `lt` `lte`	Funds by native fund size — matched against the fund’s own currency, NOT currency-converted (mirrors `amount_source.amount` in the response).
Vintage Year	`year`	numeric · year	✅	`eq` `neq` `gt` `gte` `lt` `lte` `in_any` `nin_any`	Funds by vintage year (year of the fund’s close/announcement date).

Fund Type

Fund category — e.g. Venture Capital, Private Equity, Growth Equity, Corporate, Life Sciences, Renewables, Fund of Funds, Other.Example values:

Venture Capital
Private Equity
Growth Equity

Is Closed

Whether the fund is closed to new commitments.Example values:

false

Amount

The as-stored fund size in the fund’s native currency. Unlike other monetary filters this is not currency-aware — the ?currency= param only affects the converted amount in the response, not this filter’s threshold.Example values:

100000000 — 100M
500000000 — 500M

Vintage Year

Matched against the year of the fund’s announced_date.Example values:

2023
2024

Manager (1 filter)

Filter	Key	Type	Status	Operators	Description
Manager (GP)	`investor_id`	id_lookup	✅	`eq` `neq` `in_any` `nin_any`	Funds raised by a specific manager (GP) entity.

Manager (GP)

The firm (general partner) that raised the fund, by its entity UUID.Example values:

345d1ab6-33df-4759-9e17-0d0c0ec9ab1c — Index Ventures

Sort keys

amount · announced_date Default order: -announced_date. Prefix a key with - for descending order.

Other lists

Sort keys of the lists that have no filter scope above: nested lists of a record, valuations, and map points.

Entities

/data/entities · /data/entities/geo Same sort keys as Companies above.

Notes

/data/notes Same sort keys as News above.

Valuations

/data/valuations date · value Default order: -date. Prefix a key with - for descending order.

Team

/data/companies/{id}/team · /data/investors/{id}/team · /data/universities/{id}/team · /data/gov-ngo/{id}/team is_strong_founder · name · signal_rating · team_rank Default order: team_rank,name. Prefix a key with - for descending order.

Portfolio

/data/investors/{id}/portfolio last_round_date · latest_valuation Default order: -last_round_date. Prefix a key with - for descending order.

Investor funds

/data/investors/{id}/funds amount · announced_date Default order: -announced_date. Prefix a key with - for descending order.

Alumni

/data/universities/{id}/alumni end_date · name Default order: -end_date,name. Prefix a key with - for descending order.

Career

/data/people/{id}/career · /data/founders/{id}/founded-companies is_founder · is_past · launch_date · name · start_date Default order: -is_founder,is_past,-start_date,name. Prefix a key with - for descending order.

Education

/data/people/{id}/education start_date Default order: -start_date. Prefix a key with - for descending order.

Patents

/data/companies/{id}/patents · /data/universities/{id}/patents · /data/gov-ngo/{id}/patents value Default order: -value. Prefix a key with - for descending order.

Company investors

/data/companies/{id}/investors Fixed order: -rounds_count,-is_lead,name; sort is ignored.

Funding rounds

/data/companies/{id}/funding-rounds Fixed order: -date; sort is ignored.

Company valuations

/data/companies/{id}/valuations Fixed order: -date; sort is ignored.

LP funds

/data/investors/{id}/lp-funds · /data/entities/{id}/lp-funds Fixed order: name; sort is ignored.

Similar

/data/companies/{id}/similar · /data/investors/{id}/similar Ranked by similarity to the record; sort is ignored.

Map points

/data/companies/geo · /data/investors/geo · /data/universities/geo · /data/gov-ngo/geo sort is ignored. With size_by, points are ordered by that value, largest first: total_funding · employees_count · latest_valuation · total_invested · investments_count · alumni_count · alumni_founders_count. Without it, they follow the collection’s default order.

​Value types

​Companies

​Specific Companies

​Company Name

​Smart Keyword

​Founded Date

​Company Status

​HQ location

​Founding location

​Office location

​Founding or HQ location

​Location (any role)

​Area

​Growth Stage

​Hiring

​Has Founder

​Unicorn Date

​Tags

​Labels

​Dealroom Signal

​Growth Signal

​Team Signal

​Timing Signal

​Completeness Signal

​Employees

​Valuation

​Latest Valuation Date

​Valuation Year

​Latest Revenue

​Website Traffic

​Founder Labels

​Gender

​Founder University

​Total Funding

​Investor Name

​Sort keys

​Investors

​Specific Investors

​Investor Name

​Roles

​HQ location

​Founding location

​Office location

​Founding or HQ location

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