Lightdash, an innovative open-source business intelligence (BI) platform and alternative to Google’s Looker, has announced a significant advancement in its offerings by unveiling a new feature that allows companies to train “AI analysts” tailored to the specific needs of individual teams. This enhancement will empower users across organizations to query and analyze aggregate business data effortlessly.

In conjunction with this launch, the four-year-old startup has raised $11 million in a Series A funding round led by Accel, underscoring its growth and potential in the BI space.

Originally known as Hubble, Lightdash graduated from Y Combinator’s S20 batch with a focus on improving data quality by running tests on data warehouses. However, as the company evolved, co-founder and CEO Hamzah Chaudhary pivoted the brand and product to Lightdash in 2021, recognizing the demand for integrated metrics within BI tools.

Lightdash is built on dbt (data build tool), a command-line tool that utilizes SQL for transforming raw data into structured, analysis-ready datasets. The platform serves both technical and non-technical users, allowing those with limited SQL experience, such as marketing or finance teams, to access data insights through a user-friendly interface. More advanced users can customize workflows and define the business logic necessary for reporting.

The latest feature enables users to ask natural language questions about their company’s data and receive “curated insights” relevant to their specific departments. “For example, the finance team will have an AI analyst that only has access to the data, metrics, and content that is relevant to them,” Chaudhary explained. This interaction can significantly reduce the time taken to obtain insights, presented in various formats such as charts or dashboards.

Data security remains a top concern for enterprises adopting generative AI. However, Chaudhary reassured that Lightdash’s AI Analyst operates on the same secure API as its standard product, ensuring that companies do not face additional risks. The AI largely relies on metadata rather than actual data, giving customers complete control over what information is shared with the AI.

Moreover, Lightdash allows clients to select their preferred LLM (large language model) provider, including options like OpenAI and Anthropic, or even use their own models, addressing concerns over sensitive data access.

Since its commercial launch and an initial seed funding of $8.4 million two years ago, Lightdash has introduced a hosted cloud service for its core open-source product, which is now utilized by over 5,000 teams. The platform has seen a seven-fold increase in revenue over the past year, with notable clients including Workday, Beauty Pie, Hypebeast, and Morning Brew.

With the fresh capital from its Series A funding, Lightdash aims to expand its team and enhance its product offerings, particularly the newly introduced AI analyst features. The funding round also saw participation from Operator Partners, Shopify Ventures, Y Combinator, and various angel investors.

As Lightdash continues to grow and innovate, it is poised to redefine how businesses approach data analysis and intelligence, making insights accessible to everyone in an organization.