TECHNOGRAPHIC DATA

Startup Technographics

Private company technographics mapped to public market tickers. See what startups adopt before the market prices it in.

10M+ COMPANIESJSON · CSV · ParquetWeekly refresh

10M+

Companies

200+

Tickers mapped

Data layers

15+ yrs

Deal history

Download Package Contents Build process Verification Audit trail Use cases Delivery Request a sample

01Download

Inspect a real sample

Representative records in the delivery format, ready to inspect before licensing the full dataset.

Company with full tech-stack to ticker mapping

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

companies.jsonlrepresentative

{
  "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 dataset.

technographic.jsonlrepresentative

{
  "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>"
}

02Schema

Record shape

Every field, its type, whether it can be null, and a representative value.

company_id

required

Unique company identifier.

Type: string

Example comp_xx

name

required

Company name.

Type: string

Example <AI company>

sector

required

Primary sector.

Type: string

Example Artificial Intelligence

headcount

required

Current employee count.

Type: int

Example 500

headcount_growth_90d

nullable

Net headcount change over 90 days.

Type: int

Example 62

total_raised

nullable

Total funding to date; null when undisclosed.

Type: int
Unit: USD

Example 281000000

last_round_stage

nullable

Most recent funding stage.

Type: string

Example Series C

tech_stack

required

Products the company uses.

Type: string[]

Example ["AWS","Snowflake","Datadog"]

tech_stack_tickers

required

Public tickers mapped from the tech stack - the proprietary value-add.

Type: string[]

Example ["AMZN","SNOW","DDOG"]

technology

nullable

Technographic row: a specific product observed in use.

Type: string

Example CrowdStrike Falcon

adoption_status

nullable

Active, Removed, or Migrated.

Type: string

Example Migrated

migrated_from_ticker

nullable

Previous vendor ticker on a switch - the cleanest displacement signal.

Type: string

Example <prior vendor>

observation_date

nullable

Point-in-time stamp for the technographic observation.

Type: date

Example 2026-01-15

Field	Type	Constraint	Description
company_id	string	required	Unique company identifier. e.g. comp_xx
name	string	required	Company name. e.g. <AI company>
sector	string	required	Primary sector. e.g. Artificial Intelligence
headcount	int	required	Current employee count. e.g. 500
headcount_growth_90d	int	nullable	Net headcount change over 90 days. e.g. 62
total_raised	int · USD	nullable	Total funding to date; null when undisclosed. e.g. 281000000
last_round_stage	string	nullable	Most recent funding stage. e.g. Series C
tech_stack	string[]	required	Products the company uses. e.g. ["AWS","Snowflake","Datadog"]
tech_stack_tickers	string[]	required	Public tickers mapped from the tech stack - the proprietary value-add. e.g. ["AMZN","SNOW","DDOG"]
technology	string	nullable	Technographic row: a specific product observed in use. e.g. CrowdStrike Falcon
adoption_status	string	nullable	Active, Removed, or Migrated. e.g. Migrated
migrated_from_ticker	string	nullable	Previous vendor ticker on a switch - the cleanest displacement signal. e.g. <prior vendor>
observation_date	date	nullable	Point-in-time stamp for the technographic observation. e.g. 2026-01-15

03What's included

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.

04Methodology

How it is built

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.
02
Five-layer structure
Fundraising and valuation, cap table and equity, investor network, talent and hiring, and syndicate and SPV layers.
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.
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.
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.

05Evals

How we validate

What each evaluation measures and how it is run. Where no benchmark is published, we show the methodology and say so.

Technographic adoption as a vendor-revenue leading indicator

Measures

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

Method

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

Result

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

06Graders

Ground truth

What correct means for this data, and how it is established.

Ground truth

The 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 established

Proposed: align aggregated adoption and migration transitions per ticker to realized vendor revenue. No validation has been run, and no agreement figure exists.

07Application

Tech Stack as Signal

Startup adoption of enterprise SaaS is a leading indicator for vendor revenue. Track Snowflake, Datadog, and MongoDB adoption before quarterly earnings.

Private-to-Public Linkage

Map private company valuations and funding velocity to public market comps. Identify when private market sentiment diverges from public pricing.

Sector Momentum

Track fundraising velocity by sector to identify where venture capital is concentrating before it shows up in public market narratives.

08Environment & integration

How you load it

Delivery

S3, REST API

Formats

JSON, CSV, Parquet

Auth

Licensed for 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.

Cadence

Weekly refresh across all layers; major rounds can appear within days of announcement.

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