TECHNOGRAPHIC DATA
Venture Intelligence
Private company technographics mapped to public market tickers. See what startups adopt before the market prices it in.
See the data
Representative records in the exact shape we deliver. Real provenance and full slices are shared under license.
Company with full tech-stack to ticker mapping
Representative. The tech_stack to tech_stack_tickers pairing is the core signal.
{
"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.
{
"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>"
}Record shape
Every field, its type, whether it can be null, and a representative value.
| 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 |
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.
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.
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.
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.
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.
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.
Request access.
Restricted-scope evaluation access for qualified teams. We share real samples, full schema, and provenance under a mutual NDA.