Blackstone Backs Startup TextQL to Revolutionize Data Analytics

TextQL's AI-powered platform aims to make data questions instantly answerable, disrupting the traditional analytics industry.

Apr. 17, 2026 at 9:28am

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Ethan Ding, the CEO and co-founder of TextQL, sees the last decade of SaaS as a historical anomaly, with software companies charging high margins for their products. Ding believes AI is about to dramatically change the analytics industry, making it possible for anyone to quickly get answers from their company's data. TextQL, which Ding co-founded in 2022 with Mark Hay, has just closed a $17 million strategic investment round led by Blackstone's early-stage investment arm. The startup is aiming to replace the slow, consultant-driven analytics process with a fast, natural language-based interface powered by AI.

Why it matters

TextQL's technology has the potential to democratize data analytics, making it accessible to a much wider range of employees rather than just specialized data teams. This could lead to a significant increase in the number of data-driven decisions being made across organizations. However, it also raises questions about how large AI labs like Anthropic might respond as the market for AI-powered analytics grows.

The details

TextQL uses AI agents to replace the traditional, consultant-driven analytics process. Ding believes this will increase the speed and accessibility of data insights by 'five to six orders of magnitude.' Rather than waiting weeks and spending thousands of dollars to get a chart, users will be able to ask questions in plain language and get instant answers. While Ding acknowledges the risk of large AI labs like Anthropic entering the market, he plans to focus on building TextQL in less competitive, low-liquidity verticals like financial services and healthcare first.

  • TextQL was co-founded by Ethan Ding and Mark Hay in 2022.
  • TextQL recently closed a $17 million strategic investment round led by Blackstone's early-stage investment arm.

The players

Ethan Ding

The CEO and co-founder of TextQL, who previously worked as a venture capital data junkie.

Mark Hay

The co-founder of TextQL, who co-founded the company with Ethan Ding in 2022.

Blackstone Innovations Investments

The early-stage investment arm of Blackstone, which led TextQL's $17 million strategic investment round.

John Stecher

The Chief Technology Officer of Blackstone, who believes large AI labs are not necessarily equipped to handle the enterprise data problem.

Anthropic

A large AI lab that Ethan Ding believes may try to enter the market for AI-powered analytics if it grows quickly enough.

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What they’re saying

“In 30 years, we're going to look back and say 'oh, remember that period of time where those crazy software companies were selling seats for 90 to 95% margins?' We'll look back on that the same way we look back on mercantilism. 'Remember when the East India Trading Company could move spice?'”

— Ethan Ding, CEO and Co-founder, TextQL

“Analytics is about to experience probably the most violent Jevons paradox anybody's seen in a very long time. Today, the cost of asking a question to seeing a chart that tells you what to do... is two weeks, a person, maybe $5,000–$10,000 of salary spent chasing those numbers down. With language models, with what we've built... you're looking at an increase of five to six orders of magnitude, all‑in.”

— Ethan Ding, CEO and Co-founder, TextQL

“The challenge enterprises are running into isn't model capability; it is making AI work reliably, securely, and cost-effectively on real, messy internal data with the right security, governance, and cost controls.”

— John Stecher, Chief Technology Officer, Blackstone

What’s next

TextQL plans to focus on building its platform in low-liquidity markets like financial services and healthcare before potentially expanding into more competitive verticals.

The takeaway

TextQL's AI-powered data analytics platform has the potential to dramatically increase the accessibility and speed of data insights across organizations, democratizing access to data-driven decision making. However, the startup will need to navigate the risk of larger AI labs entering the market as the demand for such technologies grows.