In an era where every business is vying for a competitive edge, Mark Hay and Ethan Ding are on a mission to make every corporate decision a data-driven one. With their platform, TextQL, they aim to revolutionize the way companies interact with their data, leveraging large language models like OpenAI’s ChatGPT and GPT-4.
The Problem with Traditional Data Management
Hay, TextQL’s CTO, highlighted the challenges faced by data leaders in an email interview with TechCrunch. "Data leaders have spent 15 years being sold a false promise… Half the Fortune 500 chief data officers are allergic to the word ‘self service’ at this point." He emphasized that traditional data management methods have failed to deliver on their promises, leaving businesses struggling with productivity issues.
The Rise of Data Scientists and Business Teams
According to Hay, 400,000 data scientists spend an estimated 40% or more of their time pulling one-off data requests. Meanwhile, business teams use words that are represented differently in their databases, resulting in months of lost productivity arguing over numbers. This scenario is all too familiar for many companies, and it’s clear that a new approach is needed.
The Genesis of TextQL
Hay and Ding, who met during the pandemic, decided to tackle this problem head-on. Both engineers had previously worked on notable projects: Hay was an engineer on Facebook’s machine learning team, while Ding was a member of Bessemer Venture Partners’ data team. They were confident that they could devise a better solution.
How TextQL Works
TextQL uses a data model to map a company’s database to the ‘nouns’ representing a customer’s business in their language. This means that users can ask questions like "Can you show me a list of orders that were very late?" or "Calculate the distribution centers with the highest concentration?" The platform connects to business intelligence tools and points users to existing dashboards when a question has already been asked.
Automation Component
In addition to answering questions, TextQL’s automation component can take certain actions. For example, it can send an email to managers about specified data. This capability enables enterprises to streamline their operations and make more informed decisions in real-time.
Competing with Established Vendors
Hay believes that TextQL is competing against vendors like Palantir and C3.ai. However, he’s confident that the platform’s unique approach will set it apart from its competitors.
Traction and Funding
TextQL has secured six-figure annual recurring revenue and claims to have several years’ worth of runway. The company has a ~10-person team, comprising previously venture-backed veteran founders. It has raised $4.1 million across pre-seed and seed rounds, sco-led by Neo and DCM with participation from Unshackled Ventures, Worklife Ventures, PageOne Ventures, FirstHand Ventures, and Indicator Fund.
Market Opportunity
The economic environment may be challenging for many businesses, but Hay argues that TextQL’s software is particularly well-positioned to help companies do more with less. As he puts it, "In an economic environment where everyone’s trying to do more with less, we’re able to give enterprise operators superpowers in one platform."
Conclusion
Mark Hay and Ethan Ding are ambitious entrepreneurs who have set their sights on transforming the way businesses interact with data. With TextQL, they’re offering a promising solution to the age-old problem of data management. As the AI landscape continues to evolve, it’s likely that innovative platforms like TextQL will play an increasingly important role in shaping the future of business decision-making.
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