58

Out of 100

N/A

Post-money

$17.5M

All rounds

58/100

2020

50-200 employees

March 2026

Bureau is an identity intelligence and fraud prevention platform that uses AI to aggregate and analyze device signals, behavioral biometrics, network metadata, and identity attributes to assess fraud risk and make real-time allow/block decisions for financial transactions, account creation, and login events. The platform offers risk APIs that integrate into payment, lending, and neobank workflows

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R

Ranjan R

Founder & CEO

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StageSeries A
Employees50-200
Country🇮🇳 India

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Series A · No public funding round data available yet.

Frequently Asked Questions

What is Bureau's valuation?
Bureau's valuation is not publicly disclosed.
Who invested in Bureau?
Investor information for Bureau is not publicly available at this time.
When did Bureau last raise funding?
No public funding round data is currently available for Bureau.
How many employees does Bureau have?
Bureau has approximately 50-200 employees.
What does Bureau do?
Bureau is an identity intelligence and fraud prevention platform that uses AI to aggregate and analyze device signals, behavioral biometrics, network metadata, and identity attributes to assess fraud risk and make real-time allow/block decisions for financial transactions, account creation, and login events. The platform offers risk APIs that integrate into payment, lending, and neobank workflows without adding friction for legitimate users.\n\nThe company raised approximately $17.5M in Series A funding from investors including Quona Capital and Village Global, and serves fintech companies, digital lenders, and payment processors in India and Southeast Asia. Bureau's consortium model shares fraud signals across its network of customers, creating a data network effect where each new integration improves fraud detection accuracy for all participants.\n\nOnline fraud losses in India have grown substantially alongside the digital payments boom, creating strong commercial incentives for effective fraud prevention infrastructure. Bureau's AI-native fraud intelligence approach, combined with its consortium data model, positions it as a serious alternative to rule-based fraud systems that cannot adapt to evolving fraud patterns at scale.