WisdomAI, the AI data analytics startup founded by Rubrik co-founder Soham Mazumdar, has raised $50 million in Series A funding led by Kleiner Perkins, with participation from NVentures, Nvidia’s venture capital arm.
The Series A follows a $23 million seed round led by Coatue Management six months earlier. The company provides AI-driven tools that allow enterprises to query and analyze structured, unstructured, and “dirty” data that is datasets that may contain errors or inconsistencies.
Users can ask questions in natural language, such as “How many customers are in my pipeline, and what is preventing them from closing this quarter?”
Queries, Not Answers
WisdomAI uses large language models only to write queries, not to generate answers. This ensures outputs come from actual data sources and prevents incorrect or fabricated responses.
Mazumdar described the system’s operation, “I have created an agent which is watching our product usage metrics, our ticket information … when something interesting happens.” The agent monitors operational data and alerts users when relevant changes occur.
The platform also includes an enterprise context layer that interprets customer data before executing queries. This allows it to handle imperfect or inconsistent datasets while maintaining accuracy.
Customer Growth and Platform Overview
Since its launch in late 2024, WisdomAI has grown from two enterprise clients to around 40, including Descope, ConocoPhillips, Cisco, and Patreon. Usage within these organizations has increased rapidly, with one client expanding from 10 users to 450 and several others doubling activity within months.
The platform integrates with data warehouses, spreadsheets, and CRM systems, allowing employees across departments to query and analyze structured, unstructured, and “dirty” data without relying on technical teams. Enterprises use it to monitor metrics, track sales pipelines, and analyze workflows.
WisdomAI focuses on query automation, monitoring, and real-time access to enterprise data. Its combination of LLM-assisted query writing and the enterprise context layer enables companies to manage complex datasets while maintaining accuracy and reducing dependence on engineering resources. The system consolidates information from multiple sources into a single interface, providing teams with visibility into enterprise data.
Real-Time Monitoring
In the last six months, WisdomAI introduced an agentic monitoring feature that alerts users when key metrics or data points change.
Mazumdar described its effect, “It alerts me when something interesting happens. It has always been a static report, but we are making it dynamic. We are making it proactive.”
The feature is quick to deploy. Mazumdar noted it took about five minutes to set up. It notifies users only when relevant changes occur, eliminating the need for manual or routine reporting.
The agent monitors multiple datasets, including usage trends and operational workflows, and integrates with the platform’s broader analytics framework to provide teams with actionable insights as events unfold.
WisdomAI continues to handle a mix of structured and unstructured data while providing automated query generation and monitoring. Users can access insights directly from their enterprise systems without needing engineering teams to prepare or clean the data.
