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Startup Technographics

Which software companies use, linked to the vendors and their stock tickers.

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  • 10M+companies
  • 200+public tickers mapped
01

Sample

2 records

Company with full tech-stack to ticker mapping

Representative. The tech_stack to tech_stack_tickers pairing is the core signal.

companies.jsonl
{
  "company_id": "comp_xx",
  "name": "<voice-AI startup>",
  "sector": "Artificial Intelligence",
  "headcount": 500,
  "headcount_growth_90d": 62,
  "total_raised": 281000000,
  "last_round_stage": "Series C",
  "tech_stack": ["AWS", "Snowflake", "Datadog", "MongoDB Atlas", "Cloudflare", "Okta"],
  "tech_stack_tickers": ["AMZN", "SNOW", "DDOG", "MDB", "NET", "OKTA"]
}

Technographic migration record (displacement signal)

Representative. Captures a vendor switch - the cleanest competitive signal in the product.

technographic.jsonl
{
  "company_id": "comp_xx",
  "observation_date": "2026-01-15",
  "technology": "CrowdStrike Falcon",
  "category": "endpoint_security",
  "ticker": "CRWD",
  "adoption_status": "Migrated",
  "migrated_from": "Legacy EDR",
  "migrated_from_ticker": "<prior vendor>"
}
02

Specifications

Startup Technographics specifications
FormatsJSON, CSV, Parquet
DeliveryS3, REST API
CadenceWeekly refresh
Companies10M+
Data layers5 integrated
Tickers mapped200+
CoverageGlobal (US, Europe, APAC)
History15+ years of deal history
AccessFor internal research and model development; redistribution requires a separate agreement. Company-level data; individual names in talent data are anonymized; no consumer PII or MNPI.

What ships

  • Fundraising & Valuation

    Round-level data with valuations, investors, and terms across 10M+ companies.

  • Technographic Mapping

    Track which startups adopt which enterprise tools (Snowflake, Datadog, MongoDB) - mapped to public tickers.

  • Investor Network

    Fund-level portfolio construction, co-investment patterns, and LP/GP relationships.

Fields

13 fields

FieldDescription
company_idstringUnique company identifier.Example comp_xx
namestringCompany name.Example <AI company>
sectorstringPrimary sector.Example Artificial Intelligence
headcountintCurrent employee count.Example 500
headcount_growth_90dint · nullableNet headcount change over 90 days.Example 62
total_raisedint · USD · nullableTotal funding to date; null when undisclosed.Example 281000000
last_round_stagestring · nullableMost recent funding stage.Example Series C
tech_stackstring[]Products the company uses.Example ["AWS","Snowflake","Datadog"]
tech_stack_tickersstring[]Public tickers mapped from the tech stack - the proprietary value-add.Example ["AMZN","SNOW","DDOG"]
technologystring · nullableTechnographic row: a specific product observed in use.Example CrowdStrike Falcon
adoption_statusstring · nullableActive, Removed, or Migrated.Example Migrated
migrated_from_tickerstring · nullablePrevious vendor ticker on a switch - the cleanest displacement signal.Example <prior vendor>
observation_datedate · nullablePoint-in-time stamp for the technographic observation.Example 2026-01-15
03

Quality checks

1 check

Technographic adoption as a vendor-revenue leading indicator

Whether net startup adoption and churn of a software product predicts the vendor revenue trajectory.

Aggregate adoption-status transitions (Active, Removed, Migrated) per ticker over time, align to the vendor reported revenue, and test lead and lag.

Methodology-stage. This is a stated hypothesis; no eval has been run or published, and we say so rather than imply a backtest exists.

Ground truth

What is correctThe vendor subsequently reported revenue or net-new logo growth would be the ground truth; the migration records are the cleanest displacement signal to grade against.
How it is establishedProposed: align aggregated adoption and migration transitions per ticker to realized vendor revenue. No validation has been run, and no agreement figure exists.

How it is built

  1. 01

    Licensed collection

    Direct contractual licensing from a venture-data platform with deeper cap-table, technographic, and investor-network granularity than the common databases. Delivered via platform API; no web scraping.

  2. 02

    Five-layer structure

    Fundraising and valuation, cap table and equity, investor network, talent and hiring, and syndicate and SPV layers.

  3. 03

    Technographic-to-ticker mapping

    The proprietary value-add: each company tracked software stack is mapped to the corresponding public ticker (parent ticker for acquired products), across 200+ public tickers, maintained as products are released, renamed, or acquired.

  4. 04

    Point-in-time

    Fundraising events carry announcement dates and technographic snapshots are timestamped, so the record reflects the state known at each point in time.

  5. 05

    Quality checks

    Funding is cross-referenced against public announcements, technographic data is validated against known product capabilities, ticker mapping is reviewed against filings for corporate actions, and company records are de-duplicated.

05RequestReplies usually within one working day

Request a sample

We send real records in the format you would receive, with the field list and where each record came from. Access for evaluation is limited and covered by a mutual NDA.

ProductStartup Technographics

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