WisdomAI Raises $23M to Deliver Accurate AI Data Analytics Without Hallucinations

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California, May 2025WisdomAI, a generative AI data analytics startup, has raised $23 million in a massive seed round led by Coatue Ventures, with participation from Madrona, GTM Capital, The Anthology Fund, U First Capital and Latitude Capital.

Founded by Soham Mazumdar, co-founder of Rubrik who departed the company in 2023, WisdomAI delivers a next-generation data intelligence platform capable of working with structured, unstructured, and even “dirty” data — data with errors or inconsistencies.

The platform enables business users to ask complex questions like “How am I going to close my quarter?” and get back accurate, actionable answers — such as pending deals and their specific blockers — all within seconds and without relying on data analysts.

“You can get the CRO to literally see all the way down to this last level of detail through our platform with five keystrokes,” Mazumdar told TechCrunch, “instead of a process involving five people and hours of time.”

What sets WisdomAI apart in a crowded space of AI-powered analytics tools is its focus on accuracy and its approach to avoiding hallucinations. Instead of relying on GenAI to generate final answers, the platform uses it only to generate the queries. If the AI fails, it produces a query that doesn’t return data — not a fabricated answer.

“GenAI can hallucinate,” Mazumdar said. “What we use it for is to write little programs that retrieve data from existing systems.”

The platform works across popular data systems like Snowflake, Google BigQuery, Amazon Redshift, Databricks, and Postgres, learning query syntax through logs and metadata.

WisdomAI already counts ConocoPhillips, Cisco, and Descope among its early customers. An oil and gas company, for instance, uses the system to answer production questions based on documents and telemetry data from field equipment.

Despite the rise of AI-native business intelligence tools, WisdomAI stands out for the pedigree of its founding team and its proven accuracy, even when operating on messy enterprise data.

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