Highlights:

  • The company provides a command-line data transformation tool called dbt, which uses SQL to help business users convert raw data into structured datasets for analysis.
  • With the recent funding, Lightdash revealed the launch of an AI-powered assistant aimed at helping non-technical users.

London-based business intelligence startup, formally known as Telescope Technology Ltd., or Lightdash, has secured USD 11 million in an early-stage funding round.

Accel led the recent Series A round. It included contributions from new investors Operator Partners and Shopify Ventures, as well as existing supporters from the company’s seed round two years ago, such as Y Combinator and several angel investors.

The company positions its platform as an open-source alternative to Google LLC’s Looker. It features a command-line data transformation tool called dbt, which utilizes Structured Query Language (SQL) to enable business users to convert raw data into structured, analysis-ready datasets.

The startup was initially known as Hubble and primarily focused on testing data warehouse environments to identify data quality issues. It later recognized that this feature would be more effective when integrated with a BI tool, leading to its rebranding as Lightdash in 2021.

Organizations use BI tools like Lightdash to combine and analyze diverse data sets, uncover insights, identify trends, and make future predictions. While most BI platforms require SQL expertise, Lightdash also supports non-technical users with its visual editing tool, allowing them to merge datasets and derive insights independently easily.

Following its latest funding round, Lightdash introduced an AI-powered assistant designed to support non-technical users. This assistant enables them to ask questions about their data in natural language and receive curated insights tailored to their specific tasks.

For example, finance teams can leverage an AI analyst that has access only to data relevant to their work, explained Lightdash founder and CEO Hamzah Chaudhary in an interview, “They can interact with their AI analyst in natural language, drastically shortening their time to insights, whether as a chart, spreadsheet, or a dashboard.”

Through its AI tool, Lightdash prioritizes data security, recognizing that many businesses are cautious about allowing generative AI models access to their valuable datasets. To address these security concerns, Lightdash’s AI analyst operates under the same application programming interface (API) as the company’s standard BI product. As a result, companies already using its tools won’t face any additional security risks.

Additionally, Chaudhary noted that the AI requires access only to the metadata, not the actual data. He added, “Customers have complete control over what information they want to share with the LLMs.”

Regarding large language models (LLMs), customers will have various options to choose from, including OpenAI’s GPT models, Anthropic PBC’s Claude, and more. Chaudhary mentioned that they can also utilize their own proprietary models if available.

With the introduction of the new AI analyst, Chaudhary aims to ignite a new phase of growth for Lightdash, which has already seen its revenue increase by more than seven times over the past 12 months from an undisclosed base. Its clientele includes well-known companies like enterprise resource planning software leader Workday Inc., among others, Chaudhary noted.

The funds will be used to grow Lightdash’s team, which currently has only 13 employees across its offices in the U.S. and Europe. Additionally, the capital will help speed up the development of new product features, including additional AI tools.