#120: #AIRadarDaily — e6data

There is a quiet, exhausting reality at the bottom of the modern data stack. Data is supposed to be the lifeblood of the enterprise, but actually using it has become an agonizing, expensive trap. As companies scale, they are inevitably forced into rigid, proprietary ecosystems that lock their data behind walled gardens. If you want to run fast analytics or power intelligent AI agents, you are forced to move the data, duplicate it, and pay exorbitant egress fees and compute costs just to access what is already yours. We have inadvertently built a system that financially penalizes companies for actually querying their own data.

It takes builders with profound infrastructure rigor and a quiet, resilient courage to look at this massive ecosystem lock-in and decide to completely dismantle it. That is exactly what Vishnu Vasanth, Srinath Prabhu, and Adishesh Kishore are doing with e6data.

Founded in 2020, the team isn’t just launching another marginal optimization tool or basic analytics dashboard. They are building a deeply intelligent, high-performance lakehouse compute engine that fundamentally unbundles the enterprise data stack.

The engineering under the hood is beautiful in its pragmatism. e6data allows you to query your data exactly where it already lives — whether on-premise, in the cloud, or in a hybrid setup — without migrating, copying, or moving a single row. It connects directly to open table formats like Iceberg and deploys an atomic, granularly scaling compute layer that executes queries entirely in place.

The true moat here is that this architecture was built natively for the agentic era. As AI agents and autonomous apps launch thousands of concurrent, complex queries, legacy data warehouses choke or generate millions in compute bills. e6data scales its compute per query rather than by the cluster, delivering up to 10x faster performance while slashing total infrastructure costs by 60%. It replaces vendor lock-in and egress anxiety with absolute architectural freedom.

The market? Fast-scaling enterprises, data-heavy SaaS platforms, and fintechs globally that desperately need to power real-time analytics and heavy AI workloads without their cloud bills destroying their margins.

Seeing founders of this caliber head-down, quietly architecting deep-tech infrastructure that directly challenges the biggest monopolies in the global data ecosystem is profoundly inspiring. They are shifting the paradigm from hoarding data to effortlessly acting on it, giving engineering teams their momentum back.

Let's celebrate the builders.

w/ Jay Ingle

#DataInfrastructure #DeepTech #ProductNation