LightdashBusiness Intelligence (BI) platform, an open-source alternative to Google Looker, is revealing a brand new product that enables corporations to train “AI analysts” for individual teams’ applications, enabling anyone in the corporate to query aggregate business data.

To help, the four-year-old startup also announced Tuesday that it has raised $11 million in a Series A funding round led by Accel.

Lightdash is built for an open-source command-line data transformation tool called db (data authoring tool) that relies on SQL and helps corporations transform raw data into structured, analysis-ready datasets. At the time, the corporate was often known as Hubble has accomplished Y Combinator’s (YC) S20 series.with particular emphasis on testing corporations’ data warehouses to discover data quality issues. As it turned out, these metrics were essentially the most useful in BI tools, hence the co-founder and CEO Hamzah Chaudhary switched product and brand to Lightdash in 2021.

In context, “business analytics” describes the technique of combining and integrating disparate sets of knowledge to derive insights, discover trends, and predict future outcomes. The Lightdash platform serves as each front-end and back-end, so people inexperienced in SQL, similar to marketing or finance teams, can access the visual component through the interface. More technical users can use the backend to create customized workflows and define all of the business logic needed for business reporting purposes.

This ties in with the newest launch of Lightdash, a feature that can enable any team member to ask natural language questions on company data and receive “curated insights” relevant to their department.

“For example, the finance team will have an AI analyst who will only have access to the data, metrics and content that is relevant to them,” Chaudhary explained to TechCrunch via email. “They can interact with their AI analyst in natural language, dramatically reducing the time it takes to get insights in the form of a chart, spreadsheet or dashboard.”

One obstacle to enterprises fully implementing generative AI is the thorny issue of knowledge security; corporations are cautious about sharing confidential company data. However, Chaudhary claims that the corporate’s AI analyst is powered by the identical Lightdash API that’s used in its standard productmeaning corporations already comfortable with Lightdash credentials don’t expose themselves to any additional risk through the use of its AI.

“Data permissions and management is one of the key obstacles preventing larger companies from implementing these tools, and with Lightdash’s AI analyst, these manufacturing capabilities are available right out of the box,” Chaudhary said. “It’s value recognizing; “It’s not a completely new query engine for customer data, it’s actually a completely new way of interacting with our existing query engine.”

Additionally, an AI analyst largely doesn’t need access to actual customer data, Chaudhary added, because he relies on metadata similar to the title and outline of the metric for many of his evaluation. “Clients have full control over what information they want to share with LLM,” he said.

Moreover, Chaudhary says customers can select their preferred LLM provider, including the likes of OpenAI and Anthropic, while still having the ability to use their very own model, which should allay any lingering concerns about opening up access to the corporate’s sensitive data.

In the cloud

Since announcing industrial launch and $8.4 million in seed funding two years ago, Lightdash has launched a hosted cloud service for its basic open source productwith additional features including security tools. Chaudhary says greater than 5,000 teams currently use the open source product on their very own, though it’s often a place to begin before upgrading to the complete feature set available in a industrial version.

“Larger teams have successfully used the OSS product to perform proofs of concept without being bogged down by information and procurement reviews,” Chaudhary said. “This allows companies to decouple the purchasing process from Lightdash testing, dramatically lowering the barrier to trialing the tool and building internal Lightdash champions before moving to a cloud product. Lightdash OSS also provides hobbyists and smaller teams with an easy introduction to BI as it provides a complete set of features to help you get started. As teams grow, they prefer a cloud platform for managed deployment, additional features, and better performance and security.”

Chaudhary claims to have increased its revenue sevenfold in the last 12 months, and its clients include: $60 billion enterprise software company Workday, in addition to Beauty Pie, Hypebeast and Morning Brew.

Currently, Lightdash says its global team has 13 employees split between Europe and the United States, and with the infusion of fresh money, the corporate said it intends to expand its team and product by incorporating latest features along the lines of what it’s currently rolling out in its AI Analysts.

In addition to lead sponsor Accel, Lightdash’s Series A round included participation from Operator Partners, Shopify Ventures, Y Combinator and a handful of angel investors.