Company profile
Center for Data Innovation
Live profile
Private Washington, District of Columbia, United States 1-10 www.datainnovation.org/ · Data Visualization · Innovation Management. Key People. Photo of Daniel ...
1-10
Astro
Public pricing page
AI Classification
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Tech Stack
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Center for Data Innovation is one of 2,673 B2B companies in the Kustiq directory.
Center for Data Innovation sits among 12 govtech vendor companies in our GovTech directory.
Similar profiles: Drizzle Team, Derrick, Apiable, and Loops.
Both sit in the 1-10 headcount band. See Center for Data Innovation vs Drizzle Team side by side.
Both sit in the 1-10 headcount band. See Center for Data Innovation vs Derrick side by side.
Both sit in the 1-10 headcount band. See Center for Data Innovation vs Apiable side by side.
How Center for Data Innovation compares with other GovTech Vendor companies
Center for Data Innovation is one of 12 GovTech Vendor companies profiled in the Kustiq GovTech directory, which holds 36 GovTech companies in total. Every number below is computed from those profiles.
Center for Data Innovation sits in the 1-10 headcount band. 0% of the 5 segment peers with a known team size are smaller. 20% of those peers share the same band.
The most common tech detections across the 7 peers with a visible stack are Google Analytics (29%), WordPress (29%), and jQuery (29%). Center for Data Innovation lists none of them.
Benchmarks are recomputed from live directory data, so they move as profiles refresh. Counts cover Kustiq-profiled companies, not the whole market.
How this profile was built
- Live web rendering via Browserless headless Chrome, not a stale cached scrape.
- Search intelligence via Serper API across the company site, LinkedIn, press, and GitHub.
- Claude only picks the buckets. It never decides facts.
- 12-factor churn engine. Deterministic score, zero LLM at scoring time.
- SMTP RCPT TO handshake on every contact, at delivery time on full profiles (paid plan).
This profile was built from 5 rendered pages of datainnovation.org and search coverage across the live web on .
Read the full methodology in our LLM-readable reference or compare against the deterministic-vs-AI framework.
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