The launch of the LLM Mesh aims to make GenAI applications safe and scalable, offering a choice of providers, including Mistral AI, Cohere, Anthropic, Meta, and more. Credit: T Schneider / Shutterstock.

GlobalData attended Everyday AI, Dataiku’s annual conference held in London, UK, in November 2024. The product keynote saw the company’s UK sales engineering director Emma Irwin remember the company’s early role in addressing customers’ struggle with the usability of certain cloud databases such as Hadoop, that went mainstream back in 2013. At the time, Dataiku started as a user interface layered on top of both legacy and modern corporate databases.

Today, the company continues to help firms leverage ML technologies and accelerate capabilities to put projects into production and get out of the POC (proof of concept) rut. In October 2024, it launched LLM Guard Services, a suite of services to control generative AI (GenAI) rollouts from POC to production to address the lack of specific applications for managing LLMs. Features include the new Quality Guard, which has code-free evaluation metrics for large language models (LLMs). The tool offers statistical techniques and code-free model fine-tuning, both capabilities had been greatly anticipated by customers who had asked the company for these specific services.

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LLM Guard Services are integrated with Dataiku LLM Mesh, an LLM gateway for building and managing enterprise-grade GenAI applications. The company was agile and quick to react to the market when GenAI became a phenomenon in 2023. Its response was to launch the LLM Mesh, its enterprise backbone to make GenAI applications safe and scalable, offering a choice of providers, including Snowflake, NVIDIA, Pinecone, AI21 Labs, Azure OpenAI Service, Google Vertex AI, AWS Bedrock, Hugging Face, Mistral AI, Cohere, Anthropic, Mosaic ML, Meta, and more. The LLM Mesh enables organizations to address the concerns related to cost management and compliance inherent to the deployment of GenAI. It also enables choice and flexibility among the growing number of models and providers.

Dataiku covers the entire AI and analytics lifecycle, with an emphasis on governance and data as well as providing flexibility for the future, or so-called optionality. It can flexibly enable organizations to go from platforms such as Hadoop to cloud optionality to use LLMs (large language models). While Generative AI continues as a front-of-mind discussion point, Dataiku’s focus remains on the broad strategy of democratizing Big Data and analytics, believing that there is a whole host of technology components that need to be in place before it is possible to embed GenAI across the business.

Despite its strengths in providing advanced analytics and collaborative data science solutions, Dataiku must confront the inherent challenges of remaining a relatively niche player lacking immediate brand recognition in a very competitive market. Addressing this weakness will be critical for the company to enhance its market presence and continue to grow.

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