Robust Intelligence provides an automated platform that evaluates AI models and data for security and safety vulnerabilities, ensuring compliance with standards like NIST and OWASP. The solution enables enterprises to deploy AI applications rapidly while mitigating risks associated with integrity, privacy, and availability violations.
Funding
$30M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
TGFounders
Product
Problem
Enterprises face security and safety risks when developing AI-powered applications due to distributed AI teams, limited visibility for security teams, and the rapid evolution of AI threats. Keeping up with novel AI vulnerabilities requires domain expertise and collaboration, which is complicated by the variety of tools used across organizations.
Solution
Robust Intelligence offers an automated platform that protects enterprises from AI security and safety vulnerabilities by assessing and mitigating threats. The platform includes AI Validation, which automates the evaluation of AI models, data, and files for vulnerabilities, and AI Protection, which provides guardrails for AI applications in production against integrity, privacy, abuse, and availability violations. The platform uses proprietary algorithmic red teaming, a threat intelligence pipeline, and policy mappings to detect vulnerabilities and protect AI applications. This enables enterprises to deploy AI applications more quickly while meeting AI safety and security standards, including NIST, MITRE ATLAS, and OWASP LLM Top 10.
Target Audience
The primary customers are enterprises seeking to secure their AI applications and comply with AI security standards.
Features
- Automated evaluation of AI models, data, and files for security and safety vulnerabilities
- Guardrails for AI applications in production against integrity, privacy, abuse, and availability violations
- Proprietary algorithmic red teaming to generate examples of inputs that expose model and application vulnerabilities
- Threat intelligence pipeline for identifying novel, zero-day AI vulnerabilities
- Policy mappings to facilitate compliance with AI security standards like NIST, MITRE ATLAS, and OWASP LLM Top 10
- Automated threat intelligence platform updates to protect against evolving threats