A leading healthcare enterprise had scaled AI across the business with dozens of models in production and a fast-growing wave of generative AI applications. As adoption accelerated, the organization faced a familiar problem: AI sprawl. Models were being developed and deployed across multiple platforms and teams, which made it difficult to maintain consistent governance, monitoring, and security controls.
To reduce operational and reputational risk without slowing development, the organization partnered with Fiddler AI to implement a unified AI Observability and Security platform, providing a single pane of glass for visibility, oversight, and governance across the LLM and ML lifecycle.
By closing the governance gap with centralized oversight and runtime protections, the organization achieved:
As AI programs scale, sprawl increases complexity and risk. This healthcare organization’s approach shows how teams can move faster by pairing innovation with operational discipline: centralized visibility, enforceable protections, and governance that spans both predictive and generative AI.
As the portfolio grew, models and applications became distributed across the enterprise. This fragmentation made it harder to maintain consistent governance and answer core operational questions:
The organization needed transparency across the full AI lifecycle, while minimizing the risk of:
The organization implemented Fiddler as a centralized AI Observability and Security layer across its portfolio, including GenAI applications built on Google Gemini. This approach enabled the team to: