The startup develops artificial intelligence governance software that provides certifiable and tamper-proof auditing for organizations utilizing AI models. This technology ensures compliance with regulatory requirements, enabling businesses to implement AI solutions with confidence.
Funding
$12.6M 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.
Founders
Product
Problem
Organizations deploying AI models face challenges in ensuring compliance with evolving regulations, managing risks associated with AI-driven decisions, and maintaining transparency across complex AI ecosystems. Traditional auditing methods are often insufficient to provide the real-time visibility and tamper-proof records needed for effective AI governance.
Solution
Prove AI offers an AI governance platform that enables organizations to centralize the management of their AI models, ensure compliance, and mitigate risks. Built on distributed ledger technology, Prove AI provides a tamper-proof, auditable record of AI model training data, configurations, and outcomes. The platform facilitates real-time monitoring, proactive risk mitigation, and secure collaboration between AI developers, business stakeholders, and regulators. By providing a unified view of the AI lifecycle, Prove AI helps organizations accelerate AI deployments while maintaining trust, accountability, and control.
Target Audience
Prove AI targets enterprises across industries—including financial services, healthcare, and manufacturing—that are deploying AI models and require robust governance, risk management, and compliance capabilities.
Features
- Centralized AI model management with a unified view of AI assets and activities
- Tamper-proof audit trails using distributed ledger technology (DLT) for data integrity and provenance
- Real-time monitoring of AI model performance, data drift, and potential biases
- Automated compliance checks against industry regulations and internal policies
- Role-based access controls and secure data sharing for multi-party collaboration
- AI lifecycle management tools for version control, rollback, and model retraining
- Integration with existing MLOps tools and AI platforms via open APIs
- Proactive alerts and notifications for risk mitigation and incident response