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WisdomAI today announced Analytics Agents, empowering enterprise data teams with a platform to design, test, and deploy AI-powered agents that reason and act upon the data stack autonomously

Enterprise leaders have spent two years and hundreds of billions of dollars on AI [but] fewer than one in three companies report that their AI investments have generated meaningful, sustained business value... The real problem is context, specifically the absence of a durable, dynamic enterprise context layer sitting between the AI and the data. Until organizations understand what that means and build accordingly, model upgrades and infrastructure investment won’t close the gap.

WisdomAI, the leader in Agentic Analytics, announced today the launch of its Federated Agentic Intelligence Platform, a fundamental shift from passive data monitoring to autonomous enterprise execution.

The piece, written by Soham Mazumdar (CEO of WisdomAI), argues that instead of replacing data analysts, generative AI is elevating them into a crucial new role: the AI Context Engineer (ACE). While AI can write SQL and process data rapidly, it lacks the institutional, historical, and business-specific context (e.g., how a company uniquely defines metrics like "revenue" or "churn") required to produce accurate business intelligence. Analysts serve as the essential bridge, engineering and safeguarding the "context layer" that prevents AI hallucinations and ensures reliable, strategic decision-making.

While cloud optimization conversations often focus heavily on infrastructure and pricing mechanics (like Reserved Instances and autoscaling), they frequently miss one of the largest drivers of both cloud spend and environmental impact: enterprise data waste. Most organizations hold multiple copies of the same dataset across systems of record, analytics pipelines, and experimental environments. Much of this data has limited "time value"—critical during a product launch or AI experiment, but rarely accessed, validated, or deleted once that window closes. In the age of AI, where temporary pipelines and prototypes proliferate rapidly, manual accountability no longer scales. To achieve true GreenOps and FinOps discipline, enterprises must transition to automated visibility and liveness tracking to systematically archive or eliminate this dormant "zombie data."

Most enterprise AI today still operates in what can best be described as single-player mode. It helps individuals write emails, summarize documents, or generate answers based on the information immediately available to them. These tools can deliver real productivity gains, but they address only the simplest use cases.Enterprises, however, do not operate on individual context alone. They run on institutional context. In other words, the interconnected relationships among customers, systems, metrics, processes, ownership models, policies, and historical decisions that determine how the business actually functions.

WisdomAI sells to enterprise data teams, empowering them to deploy AI data analysts that automate analytics functions traditionally handled by human analysts. As a former Rubrik co-founder and Google search ranking engineer, Soham identified the analytics problem firsthand while scaling Rubrik from intuition-driven to data-driven operations. In this episode of Category Visionaries, shares how four Rubrik alumni are building a category-defining solution in the data analytics space, the tactical insights from targeting mid-market accounts to optimize deal velocity and onboarding experience, and how AI buying committees shifted from experimental budgets in 2024 to gatekeepers requiring departmental champions in 2025.

Soham Mazumdar, CEO and co founder of Wisdom AI, joins the show to talk about what it really takes to build again after major exits at Facebook and Rubrik. We get into the mindset shift required for a new startup, the danger of relying too much on past playbooks, and how to stay grounded when expectations rise.

WisdomAI, the company behind the most accurate AI Data Analyst for trusted business insights in the enterprise, today announced a $50 million Series A financing. Kleiner Perkins led the funding round, with participation from new investor NVentures (NVIDIA's venture capital arm) and existing investors Coatue, Latitude Capital, Madrona, GTM Capital, Menlo Ventures, and U First Capital.