Dataiku Continues to Support the Multi-LLM Approach with LLM Mesh Expansion

Dataiku, the Universal AI Platform, is announcing the expansion of its LLM Mesh ecosystem, securely connecting enterprises to thousands of large language model (LLM) gateways. This release is also paired with the announcement of LLM Registry, an effort to close the governance gap between LLM management and regulatory readiness, according to Dataiku.

The proliferation of all things AI has catapulted many companies into the highly competitive, constantly evolving world of LLM implementation. Dataiku’s LLM Mesh acts as a vehicle for organizations to adopt a multi-LLM approach—a method of seamlessly changing the underlying model of generative AI (GenAI) applications. Instead of investing in a sole model—which may prove inadequate as new models emerge on the scene—Dataiku’s LLM mesh acts as a secure API gateway that helps enterprises adapt to the rapidly evolving AI space, according to the company. 

“Our goal is to help our customers future-proof their GenAI strategies and avoid obsolescence—that said, we provide a balanced approach to developing AI applications, while removing the risk of anchoring a strategy to a single AI provider,” said Florian Douetteau, co-founder and CEO, Dataiku. “The LLM Mesh gives organizations secure access to literally thousands of diverse models for any GenAI use case they’re looking to implement today for a true multi-LLM strategy.” 

Dataiku’s infrastructure-independent approach decouples the GenAI application from the service layer while delivering cost, usage, hallucination, and personally identifiable information (PII) guardrails. This empowers enterprises with the flexibility and choice necessary to keep pace with the continuously changing AI ecosystem, according to the company. 

Now, Dataiku’s LLM mesh supports a wide variety of LLM providers, including 15 of the major cloud and AI vendors—such as Amazon Web Services (AWS), Databricks, Google Cloud, Snowflake (Arctic), and more. By adopting a multi-LLM approach, organizations can implement cost and performance management processes while forwarding privacy and security best practices. 

Additionally, the LLM Registry serves to help CIOs and their teams qualify, document, and determine which LLMs suit their unique needs and use cases. 

“IDC anticipates a future marked by a variety of model types, each suited to different tasks and scenarios,” said Nancy Gohring, IDC senior research director, AI. “Enterprises are likely to use many models of different sizes and modes, and should ensure they have the ability to quickly evaluate and swap models as new models come to market and use cases evolve.”

To learn more about Dataiku’s LLM Mesh, please visit https://www.dataiku.com/.