Multiples
Private Companies and DealsTransactions

List of Transactions

Introduction

List and search transactions - M&A deals, funding rounds, and public listings - across the entire company universe.

Each row carries the target company plus the deal's headline economics (valuation, amount raised, implied multiples) and its participants: M&A deals populate buyers, funding rounds populate lead_investors and the full investors list (leads included, each with a role).

Use it to build deal screens, pull comparable transactions for a vertical, track every deal a given investor or acquirer took part in, or check for changes to deals you already show.

Each deal in the response is charged as one record; its target company and the buyers and investors on it are not charged - see What each request is charged.

For the target's sector context, fetch the single deal via GET /transactions/{id}.

Set up

Endpoint

POST https://multiples.vc/api/private/v1/transactions

Request - send a JSON body. Every field is optional; an empty body returns the most recent transactions across all deal types.

Get all (minimal) - most recent deals, first page:

{
  "sort": "deal_date:desc",
  "limit": 100
}

Get a filtered set - US M&A deals valued at $100M or more, 2023-2025:

{
  "filters": {
    "deal_type": ["M&A"],
    "target_country": ["USA"],
    "date_from": "2023-01-01",
    "date_to": "2025-12-31",
    "valuation_min": 100
  },
  "sort": "deal_date:desc",
  "limit": 100
}

Track one investor - every deal Sequoia took part in:

{
  "filters": {
    "investor_id": [
      "9918f9bb-0d74-434d-9029-a44cbee87637"
    ]
  },
  "sort": "deal_date:desc",
  "limit": 3
}

All amounts and bounds (valuation_*, raised_*, revenue_*, ebitda_*) are expressed in millions of USD.

fieldtypedescription
filters.idstring[] (uuid)Batch lookup by deal ID.
filters.target_idstring[] (uuid)Return deals whose target is any of these companies.
filters.investor_idstring[] (uuid)Match deals where any of these companies took part in any role: lead investor, non-lead investor in a funding round, or M&A buyer.
filters.deal_typestring[]One or more of Early, Growth, M&A, Public listing, Secondary, Venture. Write-down and its subtypes Impairment and Insolvency are accepted but match nothing: a write-down is a valuation event, not a transaction (see Transaction filters and vocabulary).
filters.deal_subtypestring[]One or more of PE buyout, Strategic M&A, ICO, Series A-Series J, Pre-seed, Seed, Angel, Strategic investment, Undisclosed stage, Secondary - private, Secondary - public.
filters.date_fromstring (date)Earliest deal date (inclusive).
filters.date_tostring (date)Latest deal date (inclusive).
filters.valuation_minnumberMinimum deal valuation (millions USD).
filters.valuation_maxnumberMaximum deal valuation (millions USD).
filters.raised_minnumberMinimum amount raised (millions USD).
filters.raised_maxnumberMaximum amount raised (millions USD).
filters.revenue_minnumberMinimum target revenue at the time of the deal (millions USD).
filters.revenue_maxnumberMaximum target revenue at the time of the deal (millions USD).
filters.ebitda_minnumberMinimum target EBITDA (millions USD).
filters.ebitda_maxnumberMaximum target EBITDA (millions USD).
filters.ev_revenue_minnumberMinimum implied EV/revenue multiple.
filters.ev_revenue_maxnumberMaximum implied EV/revenue multiple.
filters.ev_ebitda_minnumberMinimum implied EV/EBITDA multiple.
filters.ev_ebitda_maxnumberMaximum implied EV/EBITDA multiple.
filters.target_countrystring[]Target's ISO 3166-1 alpha-3 country codes (e.g. USA, GBR, DEU).
filters.target_regionstring[]Target's region (e.g. North America, Western Europe).
filters.target_verticalsstring[]Deals whose target is tagged with any of these verticals (e.g. Biopharmaceuticals, Medical Devices, Industrial Software).
filters.target_themesstring[]Deals whose target is tagged with any of these themes (e.g. FinTech, B2B SaaS, HealthTech).
filters.target_client_focusstring[]Deals whose target matches any of these client-focus tags.
filters.target_revenue_modelstring[]Deals whose target matches any of these revenue models.
filters.target_company_typestring[]Deals whose target matches any of these company types.
filters.updated_atstring (date-time)Change-feed checkpoint: returns deals updated at or after this timestamp.
filters.include_deletedbooleanInclude soft-deleted deals; set true on change-feed pulls. Default false.
sortstringfield:asc|desc (e.g. deal_date:desc, updated_at:asc). Valid fields are listed in /lookup/transactions. A bare field name sorts descending. Default deal_date:desc (newest first).
fieldsstringComma-separated allowlist of fields to return.
limitintegerPage size. Default 100, maximum 1000.
pageinteger1-indexed page number. Default 1. page * limit may not exceed 10,000; a request past that returns 400 (narrow your filters instead).

A plain array matches deals whose target has any listed value. {"all": ["B2B SaaS", "FinTech"]} matches deals whose target is tagged with every listed value. The same shape works on target_verticals, target_themes, target_client_focus, target_revenue_model and target_company_type, and on POST /transactions/aggregate. An empty {"all": []} returns 400.

An empty array on any filter, including id: [], means no filter: it does not narrow the result.

An unknown value returns 400 and names the closest matches. Verticals and themes are distinct: FinTech is a theme, so sending it as target_verticals is rejected and the error points at target_themes. Accepted values are on Filter values.

Response - data is an array of deals; meta carries pagination. Absent values are returned as null (or empty arrays).

For the investor request above (all deals where Sequoia participated), the response is below. The first row is a funding round, so buyers is empty and lead_investors and investors are populated (an M&A row would instead populate buyers). The investors arrays are shortened here; live rows list every investor in the round:

{
  "data": [
    {
      "id": "f5079d76-2560-49d1-a094-58755b7911e3",
      "deal_date": "2026-05-27",
      "deal_type": "Growth",
      "deal_subtype": "Series H",
      "deal_synopsis": "Anthropic has closed a $65 billion Series H round at a $965 billion post-money valuation. The financing was led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, and co-led by Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ, and XN. The proceeds are earmarked for safety and interpretability research, additional compute to meet demand for Claude, and continued investment in the products and partnerships the company's customers depend on.\nThe round drew a broad investor base, including AMP PBC, Baillie Gifford, Blackstone, Brookfield, D.E. Shaw Ventures, DST Global, Fidelity Management & Research Company, General Catalyst, Insight Partners, Jane Street, Lightspeed Venture Partners, MGX, NTTVC, NX1 Capital, Situational Awareness LP, T. Rowe Price Associates, T. Rowe Price Investment Management, and Temasek. It also incorporates $15 billion of previously committed investment from hyperscalers, $5 billion of which comes from Amazon. Strategic infrastructure partners Micron, Samsung, and SK hynix—key suppliers of memory, storage, and logic chips—also joined. The company reports that adoption has continued to expand across enterprise customers since its Series G in February, with run-rate revenue passing $47 billion earlier this month.\nAlongside the raise, Anthropic has expanded its compute footprint through several agreements: up to five gigawatts of new capacity with Amazon, five gigawatts of next-generation TPU capacity with Google and Broadcom, and access to GPU capacity in Colossus 1 and Colossus 2 with SpaceX. Claude is now available on all three major cloud platforms—Amazon Web Services, Google Cloud, and Microsoft Azure—with AWS remaining the company's primary cloud provider and training partner.",
      "deal_valuation": 965000,
      "deal_raised": 65000,
      "deal_revenue": 47000,
      "deal_ebitda": null,
      "deal_multiples": {
        "ev_revenue": 20.53191489361702,
        "ev_ebitda": null
      },
      "target": {
        "id": "75bdc421-b56b-4624-9c1f-6aa931f7dfcb",
        "name": "Anthropic",
        "short_name": "Anthropic",
        "website": "https://www.anthropic.com",
        "country": "USA"
      },
      "buyers": [],
      "lead_investors": [
        {
          "id": "7a80d476-dd57-4b80-93fe-c92f04419fe7",
          "name": "Altimeter Capital",
          "country": "USA",
          "website": "http://www.altimeter.com",
          "short_name": "Altimeter Capital"
        },
        {
          "id": "0ab023f8-8c07-413b-9f4f-7a790df5ed3d",
          "name": "Dragoneer",
          "country": "USA",
          "website": "https://www.dragoneer.com",
          "short_name": "Dragoneer"
        },
        {
          "id": "096dbe57-57bd-444a-a67b-168a74cb9def",
          "name": "Greenoaks",
          "country": "USA",
          "website": "https://www.greenoaks.com",
          "short_name": "Greenoaks"
        },
        {
          "id": "9918f9bb-0d74-434d-9029-a44cbee87637",
          "name": "Sequoia Capital",
          "country": "USA",
          "website": "http://www.sequoiacap.com",
          "short_name": "Sequoia Capital"
        }
      ],
      "investors": [
        {
          "id": "00e687b3-f738-4c97-9a54-4f9b56b29edd",
          "name": "Temasek Holdings",
          "country": "SGP",
          "website": "http://www.temasek.com.sg",
          "short_name": "Temasek Holdings",
          "role": "investor"
        },
        {
          "id": "9918f9bb-0d74-434d-9029-a44cbee87637",
          "name": "Sequoia Capital",
          "country": "USA",
          "website": "http://www.sequoiacap.com",
          "short_name": "Sequoia Capital",
          "role": "lead_investor"
        }
      ],
      "created_at": "2026-06-04T17:15:56.814376+00:00",
      "updated_at": "2026-06-04T17:15:56.814376+00:00",
      "deleted": false
    },
    {
      "id": "f3326b91-c793-44ce-bd19-bdb3f5ded2a1",
      "deal_date": "2026-04-29",
      "deal_type": "Growth",
      "deal_subtype": "Series A",
      "deal_synopsis": "Standard Intelligence, a six-person AI startup, raised $75 million in funding led by Sequoia and Spark Capital. Sequoia's investment team included Sonya Huang, Mikowai Ashwill, and Yasmin Razavi. The round also included prominent angel investors and advisors, including AI researcher Andrej Karpathy, as well as Milan Kovac and Stanley Druckenmiller. The company plans to use the capital to purchase additional computing capacity and develop AI safety guardrails optimized for computer use models. Standard Intelligence is focused on building models that explore and learn like humans do, with a long-term mission centered on building aligned AGI.",
      "deal_valuation": 500,
      "deal_raised": 75,
      "deal_revenue": null,
      "deal_ebitda": null,
      "deal_multiples": {
        "ev_revenue": null,
        "ev_ebitda": null
      },
      "target": {
        "id": "d092adc6-a48f-4713-8f5e-07bc22d238d5",
        "name": "Standard Intelligence",
        "short_name": "Standard Intelligence",
        "website": "https://si.inc/",
        "country": null
      },
      "buyers": [],
      "lead_investors": [
        {
          "id": "9918f9bb-0d74-434d-9029-a44cbee87637",
          "name": "Sequoia Capital",
          "country": "USA",
          "website": "http://www.sequoiacap.com",
          "short_name": "Sequoia Capital"
        },
        {
          "id": "39a3bfe5-4bbf-4c70-8cc7-a0302f7d505f",
          "name": "Spark Capital",
          "country": "USA",
          "website": "http://www.sparkcapital.com",
          "short_name": "Spark Capital"
        }
      ],
      "investors": [
        {
          "id": "9918f9bb-0d74-434d-9029-a44cbee87637",
          "name": "Sequoia Capital",
          "country": "USA",
          "website": "http://www.sequoiacap.com",
          "short_name": "Sequoia Capital",
          "role": "lead_investor"
        },
        {
          "id": "39a3bfe5-4bbf-4c70-8cc7-a0302f7d505f",
          "name": "Spark Capital",
          "country": "USA",
          "website": "http://www.sparkcapital.com",
          "short_name": "Spark Capital",
          "role": "lead_investor"
        }
      ],
      "created_at": "2026-05-01T14:47:10.710446+00:00",
      "updated_at": "2026-05-01T14:47:10.710446+00:00",
      "deleted": false
    },
    {
      "id": "70a6b6d1-4e4e-4e49-a058-f606cceee6d9",
      "deal_date": "2026-04-28",
      "deal_type": "Growth",
      "deal_subtype": "Series D",
      "deal_synopsis": "Rogo raised $160 million in an equity Series D funding round in April 2026, led by Kleiner Perkins with participation from Sequoia Capital, Thrive Capital, Khosla Ventures, J.P. Morgan Growth Equity Partners, BoxGroup, Mantis VC, Jack Altman, Evantic, and Positive Sum. The post-money valuation reached approximately $2 billion, up from $750 million following the $75 million Series C in January 2026. Total funding raised exceeds $300 million.\nThe capital will accelerate international growth, deepen partnerships with major financial institutions, and expand the AI agent Felix. This follows the Series C, which supported the opening of a London office for European expansion.\nRogo, a New York-based generative AI platform purpose-built for financial services workflows, launched in 2021 and serves over 250 institutional clients including Rothschild & Co, Jefferies, and Lazard. The agentic platform targets investment banking and finance operations.",
      "deal_valuation": 2000,
      "deal_raised": 160,
      "deal_revenue": null,
      "deal_ebitda": null,
      "deal_multiples": {
        "ev_revenue": null,
        "ev_ebitda": null
      },
      "target": {
        "id": "d57c0554-c234-47ab-a78d-23bc44f13edb",
        "name": "Rogo",
        "short_name": "Rogo",
        "website": "https://rogo.ai",
        "country": "USA"
      },
      "buyers": [],
      "lead_investors": [
        {
          "id": "2bdca794-d427-47d2-9a51-94c626163180",
          "name": "Kleiner Perkins",
          "country": "USA",
          "website": "https://www.kleinerperkins.com",
          "short_name": "Kleiner Perkins"
        }
      ],
      "investors": [
        {
          "id": "2bdca794-d427-47d2-9a51-94c626163180",
          "name": "Kleiner Perkins",
          "country": "USA",
          "website": "https://www.kleinerperkins.com",
          "short_name": "Kleiner Perkins",
          "role": "lead_investor"
        },
        {
          "id": "9918f9bb-0d74-434d-9029-a44cbee87637",
          "name": "Sequoia Capital",
          "country": "USA",
          "website": "http://www.sequoiacap.com",
          "short_name": "Sequoia Capital",
          "role": "investor"
        }
      ],
      "created_at": "2026-05-01T14:47:10.710446+00:00",
      "updated_at": "2026-05-01T14:47:10.710446+00:00",
      "deleted": false
    }
  ],
  "meta": {
    "page": 1,
    "limit": 3,
    "returned": 3,
    "total": 1445,
    "has_more": true
  }
}

Fields

Deal

fieldtypedescription
idstring (uuid)Unique deal identifier.
deal_datestring (date) | nullDate the deal was announced or completed. May be null.
deal_typestring | nullDeal category. Common values: Early, Growth, M&A, Public listing, Secondary, Venture (non-exhaustive; may be null). Never Write-down: impairments and insolvencies are valuation events, not transactions.
deal_subtypestring | nullMore specific classification (e.g. Strategic M&A, PE buyout, Series A). May be null.
deal_synopsisstring | nullNarrative summary of the deal.
deal_valuationnumber | nullDeal valuation, millions USD.
deal_raisednumber | nullAmount raised, millions USD (funding rounds).
deal_revenuenumber | nullTarget revenue at the time of the deal, millions USD.
deal_ebitdanumber | nullTarget EBITDA, millions USD.
deal_multiplesobjectImplied transaction multiples (see below).
targetobject | nullThe company that was acquired, raised, or listed (see Company reference).
buyersobject[]Ordered list of acquirers; populated only for M&A deals (empty for funding rounds, Public listing, and Secondary deals). Company references.
lead_investorsobject[]Ordered list of lead investors (funding rounds). Company references.
investorsobject[]Every investor in the funding round, leads included. Company references plus role: lead_investor (led the round) or investor (took part without leading). Empty for M&A deals.
created_atstring (date-time) | nullWhen the record was first created (UTC).
updated_atstring (date-time) | nullTimestamp of the last update to this record (UTC).
deletedbooleantrue if the record has been soft-deleted; appears in change-feed pulls.

Deal multiples (deal_multiples)

fieldtypedescription
ev_revenuenumber | nullEV/revenue multiple implied by the deal, where available.
ev_ebitdanumber | nullEV/EBITDA multiple implied by the deal, where available.

Company reference (target, buyers[], lead_investors[], investors[])

fieldtypedescription
idstring (uuid)Company identifier.
namestring | nullCompany display name.
short_namestring | nullShort display name.
websitestring | nullCompany website URL.
countrystring | nullISO 3166-1 alpha-3 country code.
rolestringinvestors[] only: lead_investor or investor.

Pagination (meta)

fieldtypedescription
pageinteger1-indexed page number echoed back.
limitintegerPage size used.
returnedintegerRows in this response.
totalinteger | nullTotal rows matching the query.
has_morebooleantrue when further pages remain. false on the last page inside the 10,000-row window, even if total is larger.
usageobjectRecords this call used from the monthly quota. See Rate Limits.

Resolve Investors

Turn an investor name, ticker or website into a Multiples investor ID, for free. Start every investor lookup here, then query by ID.

Transaction Details

Returns a single transaction with its full participant lists.

On this page

IntroductionSet upDealDeal multiples (deal_multiples)Company reference (target, buyers[], lead_investors[], investors[])Pagination (meta)