Raidu provides an AI accountability layer that sits inside a company's cloud infrastructure to enforce governance policies on large language model interactions in real time. The platform intercepts every user prompt and model response, applies runtime policy checks, and cryptographically signs the evidence for audit trails. It addresses the growing need for compliance with regulations like the EU AI Act and HIPAA AI Rule.
Funding
Funding not disclosed
Founders
Product
Problem
Security and compliance teams cannot approve AI tools that process sensitive data because there is no way to prove what those models actually did with the information. This has led to widespread bans on AI tools in enterprises, but these bans are ineffective since employees use AI on personal accounts with company data, creating shadow AI with zero audit trail.
Solution
Raidu provides an AI accountability layer that sits inside a company's cloud infrastructure and intercepts every interaction with AI models at runtime. The platform enforces governance policies before and after inference, as well as before and after external API calls, ensuring that all AI activity complies with regulatory requirements. Every interaction is cryptographically signed with RSA-4096 encryption and stored in write-once-read-many (WORM) storage for 10 years, creating an immutable evidence trail. The system achieves 99.2% PII detection accuracy with less than 100 ms overhead per checkpoint, making it practical for real-time enterprise use.
Target Audience
Primary customers are enterprise security, compliance, and IT teams at Fortune 500 companies and regulated industries such as banking, healthcare, and insurance that need to safely deploy AI tools while meeting regulatory requirements.
Features
- Runtime policy enforcement that intercepts user inputs, pre-inference prompts, pre-tool external API calls, post-tool responses, and agent outputs
- Cryptographic evidence signing using RSA-4096 with 10-year WORM retention for tamper-proof audit trails
- 99.2% PII detection accuracy with sub-100ms per-checkpoint overhead for seamless integration
- Compliance coverage for EU AI Act, HIPAA AI Rule, Colorado SB 24-205, NYDFS Circular Letter No. 7, SR 11-7, GDPR, DPDPA, PIPL, LGPD, POPIA, ISO/IEC 42001, NIST AI RMF 1.0, and OMB M-24-10
- Internal prompt library management with version control to standardize and enforce compliant AI interactions across the organization