Credo AI Unveils Generative AI Vendor Registry: Driving AI Transparency and Risk Management at Scale

Credo AI, a global leader in AI governance software, announces the launch of the GenAI Vendor Registry, a new layer of intelligence that helps companies greenlight entire AI vendors for fast and scalable AI adoption.

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“Vendor-specific governance is crucial in today’s AI landscape, where the complexities of interdependencies between data, models, applications, and tools demand a more comprehensive approach”

The GenAI Vendor Registry launches with pre-populated data for leading AI vendors and developers, including OpenAI, Microsoft, IBM, GitHub, Salesforce, Anthropic, Databricks, Codeium, Glean, AskSage, and Meta. The registry enables enterprises to easily consolidate risk and compliance data and provides Responsible AI (RAI) benchmarks for specific vendors.

“Vendor-specific governance is crucial in today’s AI landscape, where the complexities of interdependencies between data, models, applications, and tools demand a more comprehensive approach,” said Navrina Singh, CEO and Founder of Credo AI. “With the Generative AI Vendor Registry, we’re giving governance teams the tools they need to make fast, informed, and scalable AI decisions. Launching with transparency reports and risk posture of vendors like OpenAI, Microsoft, and Salesforce pre-populated in the registry, we’re ensuring that organizations can quickly and safely adopt generative AI across various use cases.”

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Centralized AI Governance and Compliance

As AI regulations like the EU’s AI Act require increased transparency and accountability, the GenAI Vendor Registry helps enterprises meet those requirements quickly and at scale. By consolidating vendor-specific risks and RAI metrics, the registry allows stakeholders—from executives to auditors—to make go/no-go decisions quickly and effectively.

For example, when a company decides to work with OpenAI and its GPT-4 model, the registry provides all relevant transparency, risk, and RAI information, facilitating the swift approval of additional use cases with that vendor. This centralized approach helps enterprises maintain control over their AI usage, minimizing the risks associated with unapproved “shadow AI”.

Should a vendor’s metrics not meet the required standards, governance leads can easily recommend alternative p*********** vendors, ensuring AI deployments are safe and compliant.

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