Car shopping data is rich but fragmented. Teams at Edmunds needed a way to turn their vast lakehouse into something more intelligent and connected. Their answer is Edmunds Mind, an AI-native, multi-agent ecosystem built on Databricks. By unifying data and automating expert workflows, Edmunds has moved from static dashboards to real-time, intelligent automation. Specialized agents like DataDave now deliver 95% analytic accuracy, driving faster insights, smarter pricing, and more personalized experiences for car buyers: https://lnkd.in/gQAWy_PR
Turning lakehouse data into operational intelligence is the next evolution of the modern data stack. Great case study from @Edmunds showing how real-time data can power smarter automotive experiences.
This is a great example of what happens when you turn a lakehouse into an operational intelligence layer instead of a reporting engine. Real-time agents, cleaner semantics, and automated expert workflows will outperform dashboards every time.
Architecting the Cognitive Enterprise This blueprint reveals a decisive inflection point where organizations evolve from data collectors into intelligence driven ecosystems. The shift from static dashboards to multi agent collaboration built on a unified lakehouse marks the beginning of true digital cognition in the enterprise. The future belongs to companies that architect systems which learn, reason, and act with autonomy. Multi agent AI operating on governed data transforms insight into continuous innovation, converting operations from reactive processes into proactive intelligence. The winners will be those who treat AI not as a tool but as an organizational operating system.
Really impressive, turning a massive lakehouse into an intelligent agent ecosystem is exactly where enterprise AI is heading. Love seeing real automation drive real outcomes like this. 👍
Great architecture. What caught my eye is how strongly the data layer is governed and structured for multi-agent workflows. As these systems grow, a key challenge I can see is on the identity side, making sure agents can take actions safely across systems while accessing data. Bridging data and identity layers feels like the next major step for agentic AI.
So agents upon agents upon agents upon agents upon data 😳 Have we lost all and absolutely every common sense ? And for what- to run simple queries on data? Everyone knows these multi step agents fail in a three level filtered sub query that needs 4 way joins to analyse business data. And when issues happen as they always do, it becomes impossible to understand where and why and how is it happening. What an utter disaster 😑 but guess as soon as we out genAI even abysmal failure of common sense appears as something super smart 😀