Headquartered in San Francisco, Databricks, the data and AI company, has come out with new tools that will help enterprises scale AI agents beyond the pilot phase to successful production with greater confidence, including for high-value use cases.
While 85 percent of global enterprises now use Generative AI (GenAI), even the most advanced models struggle to deliver business-specific, accurate, and well-governed outputs, largely because they lack awareness of enterprise data.
“Many enterprises still struggle to deploy AI agents in high-value use cases due to concerns around accuracy, governance, and security. For these organisations, it’s confidence, not just technology, that presents the biggest hurdle to extracting the full data intelligence benefits of Generative AI,” said Craig Wiley, Senior Director of Product for AI/ML, Databricks. “The new tools address these challenges head-on, enabling businesses to move beyond pilots and into full-scale production with AI agents they can trust,” added Wiley.
Ian Cadieu, CTO of Altana, a customer of Databricks, opined, “Batch AI with AI Functions is streamlining our AI workflows. It’s allowing us to integrate large-scale AI inference with a simple SQL query—no infrastructure management needed. This will directly integrate into our pipelines cutting costs and reducing configuration burden. Since adopting it we’ve seen dramatic acceleration in our developer velocity when combining traditional ETL and data pipelining with AI inference workloads.”
Tools Introduced:
Centralised governance for all AI models: Integrate and manage both open source and commercial AI models all in one place with Mosaic AI Gateway support for custom LLM providers. The Mosaic AI Gateway provides unified governance, monitoring, and integration across all models.
Simplified integration into existing app workflows: AI/BI Genie Conversational API suite enables developers to embed natural language-based chatbots directly into custom-built apps or popular productivity tools like Microsoft Teams, Sharepoint, and Slack. With the Genie API, users can programmatically submit prompts and receive insights just as they would in the Genie user interface. The API is stateful, allowing it to retain context across multiple follow-up questions within a conversation thread.
Streamlined human-in-the-loop workflows: The upgraded Agent Evaluation Review App makes it easier for domain experts to provide targeted feedback, send traces for labelling, and customise evaluation criteria – all without needing spreadsheets or custom-built applications. By making it easier to collect structured feedback, teams can continuously refine AI agent performance and drive systematic accuracy improvements.
Provision-Less Batch Inference: While model selection, governance, and evaluation are critical to building high-quality agents, simplifying the experience is also important for companies wanting to scale this technology across their business. This tool offers a new way to run batch inference with Mosaic AI using a single SQL query, eliminating the need to provision infrastructure while enabling seamless unstructured data integration.
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