Highlights:
- TextQL is the innovator behind a generative AI-powered data analyst, facilitating the connection of companies’ business intelligence tools with their current documentation and semantic layers.
- The startup aims to automate the entire enterprise data lifecycle by emulating the experience of collaborating with a human data analyst.
TextQL Inc., a startup focused on generative artificial intelligence, has successfully secured USD 4.1 million in funding through two distinct rounds, namely pre-seed and seed rounds. The company is developing a chatbot assistant resembling a data analyst for enterprise workers.
Neo and DCM co-led both funding rounds, with participation from various other supporters, including Unshackled Ventures, Worklife Ventures, PageOne Ventures, FirstHand Ventures, and Indicator Fund. Angel investors supporting the company include Tristan Handy, Chief Executive of dbt Labs Inc., Chris Prucha, Founder of Notion Inc., and Matt Kraning, Chief Technology Officer of Observe Inc.
TextQL is the developer of a generative AI-driven data analyst that facilitates the integration of companies’ business intelligence tools with their current documentation and semantic layers. The startup’s goal is to automate every phase in the lifecycle of enterprise data, achieving this by emulating the experience of collaborating with a human data analyst.
Ana, the generative AI data analyst, can be incorporated across an organization’s entire data stack. It connects with the BI tools in use, guiding users to relevant existing dashboards for previously asked questions. Ana also compiles documentation for the semantic layers of companies and has the capability to generate new code as needed. This process involves referencing documentation from enterprise data catalogs such as Alation and notes stored in Google Drive or Confluence.
Ethan Ding, the Co-founder and Chief Executive of TextQL, expressed the company’s ambition to achieve success in areas where other self-service data startups have encountered challenges. He clarified that TextQL is specifically crafted to replicate the hierarchical process of responses undertaken by a human analyst, functioning seamlessly throughout the complete data stack without necessitating any migration.
Ding explained, “It browses your BI tools, queries your semantic layer, reads your dbt documents, and asks for help when it doesn’t know what to do. This is the hardest unsolved problem at the intersection of enterprise data, AI and user experience – but the difficulty of the problem has attracted a ton of really incredible people to our team.”
The most recent iteration of Ana reportedly incorporates a dynamic metadata engine capable of indexing data from various sources, including Google Drive, Microsoft Office, Confluence, and Notion. It is also compatible with well-known BI tools like Tableau, Looker, and PowerBI, as well as data platforms such as dbt, Cube, and LookML. Additionally, Ana extends compatibility to messenger platforms like Slack.
The startup claims that its platform is currently in use by tens of thousands of employees across various industries, including healthcare, financial services, and media. However, specific customer names were not disclosed.
Hurst Lin, Co-founder and General Partner at DCM, highlighted that TextQL is significantly contributing to assisting non-technical workers in uncovering the information they require within their company’s extensive internal data. He said, “We’re excited about the work that TextQL is doing to help nontechnical workers across various industries and organizations access the critical data they need to make informed business decisions.”
With the recent injection of funds, TextQL plans to grow its team. The company aims to recruit additional software engineers and forward-deployed engineers to write code to process customer data and push it back to data stores. These new hires will join the data engineering and language model training teams. According to the startup, the expanded team is expected to enable the onboarding of 10 new customers in the upcoming quarter.
The company is strategizing additional integrations, aiming to enable a broader range of companies to utilize their preferred semantic layers, BI platforms, and data catalogs.
NEO CEO Ali Partovi expressed being impressed by TextQL’s ambitious vision and Ding’s technical leadership. He emphasized that AI has the potential to alleviate the burden on thousands of enterprise workers, freeing them from manual organization and sifting through data. “TextQL will unlock a massive surge in data usage where anybody in an organization can access data and get insights just by asking questions, instead of waiting for the engineers to construct queries.”