{"slug": "the-intelligent-layer-in-enterprise-data", "title": "The Intelligent Layer In Enterprise Data", "summary": "TextQL, a New York-based AI data platform founded in 2022 by Ethan Ding and Mark Hay, builds AI agents that enable enterprises to query data across all existing systems. The company aims to serve as an intelligent layer for enterprise data management.", "body_md": "[Open Source CEO by Bill Kerr](../)- Posts\n- The Intelligent Layer In Enterprise Data\n\n# The Intelligent Layer In Enterprise Data\n\n## An interview with Ethan Ding, Co-Founder & CEO at TextQL. ⚓\n\n👋 Howdy to the 6,778 new legends who joined since our last edition! You are now part of a 449,330-strong tribe outperforming the competition together.\n\n**LATEST POSTS** 📚\n\nIf you’re new, not yet a subscriber, or just plain missed it, here are some of our recent editions.\n\n🎳 [Brand Expansion = Loading](https://www.opensourceceo.com/p/brand-expansion). We've reached a point where we can take a breath and think about what should come next.\n\n🧬 [Enhancement, AI Doctors & The Future Of Health](https://www.opensourceceo.com/p/max-marchione-interview). An interview with Max Marchione, Founder at Superpower.\n\n🔥 [How To (Attempt To) Send One Million Outbound Emails Per Day](https://www.opensourceceo.com/p/million-outbound-emails). Our wild plan to send world record levels of outbound.\n\n**PARTNERS **💫\n\n\"Show me every deal where the champion's gone quiet and draft a re-engagement email for each one.\"\n\n\"What objections keep coming up across my calls?\"\n\n\"Compare our closed-won to closed-lost—what's different?\"\n\nLightfield is an [AI-native CRM that lets you ask anything about your business](https://lightfield.app/product/ai-pipeline-generation?utm_source=newsletter&utm_medium=paid&utm_campaign=open_source&utm_content=primary_6-4-2026).\n\nYou have a list of tools you wish existed at your company. 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Anyway, let’s jump into today’s interview.\n\n**INTERVIEW 🎙️**\n\n# Ethan Ding, Co-Founder & CEO at TextQL\n\n[Ethan Ding](https://www.linkedin.com/in/theethanding/?utm_source=www.opensourceceo.com&utm_medium=referral&utm_campaign=the-intelligent-layer-in-enterprise-data) is the Co-Founder & CEO of [TextQL](https://textql.com/?utm_source=www.opensourceceo.com&utm_medium=referral&utm_campaign=the-intelligent-layer-in-enterprise-data), a New York-based AI data platform he started in 2022 with Co-Founder & CTO Mark Hay. TextQL builds AI agents that let enterprises query their data across every existing system, without migrating anything. The AI agent, called ‘Ana’, connects directly to a company's BI tools, warehouses, and documentation, and lets anyone ask plain-language questions and get answers in seconds rather than days. Customers include Amazon, Dropbox, Scale AI, and Blackstone. In April 2026, TextQL raised $17M in strategic investment led by Blackstone’s early-stage investment arm, bringing total disclosed funding to $21.1M. Before TextQL, Ethan held data and research roles at Bessemer Venture Partners and Contrary VC. He writes a newsletter on AI cost curves and enterprise infrastructure that has been cited by Ben Thompson, Reid Hoffman, and TBPN.\n\nEthan.\n\nEthan describes his entire career as one long, barely-controlled frustration with the status quo. The first two years of TextQL were, by his own account, a disaster: wrong product, churned customers, models that didn't work, a full rebuild. What kept them going wasn't a plan so much as an inability to accept that the problem wasn't solvable. The company that came out the other side has a blunt thesis: every enterprise has messy data, nobody has fixed it in 20 years, and the agents that can finally navigate that mess without demanding a migration first are going to eat the incumbents. Ethan has opinions about that, and he is not shy about sharing them.\n\n# What’s the problem you are trying to solve, and why?\n\nThe problem we're trying to solve is that it takes people a long time to get access to their data. They hear: our data is not ready, it's garbage in, garbage out, we haven't cleaned it up or moved it into one system. Every single system in the ecosystem wants you to migrate into their own system (whether it's a BI tool, whether it's a data warehouse). We want to be very clear with our messaging that we are agnostic to all the other systems. Our goal is to make it so that you can query from all those places without having to migrate, without having to do anything, as is.\n\nSource: [TextQL](https://textql.com/?utm_source=www.opensourceceo.com&utm_medium=referral&utm_campaign=the-intelligent-layer-in-enterprise-data).\n\n# What was the most difficult when going from zero to one?\n\nFor the first two years, the product just didn't work. The language models weren't there, the infrastructure wasn't there. We churned almost all our customers and had to constantly rebuild the product. It was a pretty extensive period of ‘are we going to make it? Is this product going to work? Is this space going to work out at all?’ There were a lot of losses to take along the way.\n\nI don't know if there was a specific day, but I remember one where we sat down in the office and it was just ‘everything is terrible’. We'd just churned a customer and then tore down the entire product from scratch and started whiteboarding. There were six of us. We all grabbed beers and went for a walk on the Brooklyn Bridge. We were just like: we're going to remember this as the worst time. And yeah, it's gone pretty well since then.\n\n# What is your main day-to-day job as CEO?\n\nRight now it's a lot of modeling the best behavior for the team. We have a lot of new salespeople and new forward-deployed engineers who don't yet have a strong intuition for how to pitch the product or position against others. This space is relatively immature (we're still growing it) and we're trying to figure out the right messaging.\n\nI can talk to any CIO and basically produce opportunity out of thin air, because I have 20 or 30 different soft points and a deep understanding of how their world works and how they're getting screwed over. But that knowledge is very hard to impart. Distilling it is the priority right now: figuring out how to scale the best people and get the product to a place where it's sustainable. | Mark and Ethan. |\n\nThe team is roughly split in three between sales, forward-deployed engineering, and regular engineering. Everyone on the non-engineering side rolls up to me, while everyone on the engineering side rolls up to my Co-Founder, Mark.\n\n# What’s your ideal ICP and how you identify them?\n\nOur ideal ICP is anyone with messy data, which is basically every large enterprise. The messier the data, the bigger the difference we can make. It was actually fairly recent that we landed on this messaging. If you tell someone you can build AI that accurately handles their stuff, they'll ask: how do you deal with things that make accuracy harder? And it's like: why don't we just go one level up? We built AI for people with extremely hard-to-make-sense-of data.\n\nThat framing just lands better. It feels like a more believable thing in the structural messaging of what you say. We have customers across six continents—five, actually, Antarctica doesn't really count—but by far the majority of our volume is in the United States.\n\n# How are you infusing AI operationally day-to-day?\n\nAlmost everyone on the team uses Claude. Every single person uses our internal agent for analytics too. It's kind of a requirement of the job. Our agent handles our CRM updates, scheduling, emailing, mailing list management, and all of our data integration work. All of our dashboards and all of our assets are built from the existing product. We basically eat our own cooking entirely.\n\n# How do you get the best out of yourself personally and professionally?\n\nGrowing up, I've always been extremely easily frustrated by the status quo; by things around me. It's basically dissatisfaction and rage boiling up inside. In terms of channeling it responsibly.\n\nShowing how you do it. |\n\nI'm extremely self-deprecating. I make a lot of jokes about how bad I am at my job and all the mistakes I make. I do my best to create a culture where people can tell me I'm wrong. I try to model the fact that I'm wrong all the time, and on the back of that, that shapes the kind of feedback I get, which I can actually work with.\n\n# Extra reading\n\n*And that’s it! You can follow Ethan on **LinkedIn**, his **newsletter**, or check out **TextQL** on their website to keep up with what they’re building!*\n\n**BRAIN FOOD** 🧠\n\n**TOOLS WE RECOMMEND 🛠️**\n\nEvery week, we highlight tools we like and those we actually use inside our business and give them an honest review. 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