Lightdash, the business intelligence (BI) platform and open source alternative to Google's Looker, has lifted the lid on a new product that will allow companies to train “AI analysts” specifically for individual team use cases. and allows anyone in your company to run queries. Aggregate business data.
To support this, the four-year-old startup also announced Tuesday that it has raised $11 million in a Series A round led by Accel.
Lightdash is built around an open source command-line-based data transformation tool called dbt (Data Construction Tools) that leverages SQL to help businesses transform raw data into structured, analyzable datasets. We will support you to do so. The company was known as Hubble when it graduated from Y Combinator's (YC) S20 batch, with a focus on running tests on enterprise data warehouses to identify data quality issues. As things progressed, we found that these metrics were most useful built into BI tools, which is why co-founder and CEO Hamzah Chaudhary pivoted his product and brand to Lightdash in 2021. That's why.
For context, “business intelligence” refers to the process of pooling and integrating disparate data sets to derive insights, identify trends, and predict future outcomes. The Lightdash platform acts as both a frontend and a backend, so even those with less SQL experience, such as marketing and finance teams, can access visual components through the interface. More technical users can dabble in the backend and build customized workflows and define all the business logic needed for business reporting purposes.
And this ties in with the latest release of Lightdash, a feature that allows anyone on a team to ask natural language questions about a company's proprietary data and receive “curated insights” relevant to their department. Masu.
“For example, finance teams have AI analysts who only have access to data, metrics, and content that are relevant to them,” Chaudhary explained to TechCrunch via email. “They can interact with AI analysts in natural language, significantly reducing the time to insights such as graphs, spreadsheets, and dashboards.”
Light Dash AI Analyst. Image credit: Light Dash
One of the hurdles for companies to fully embrace generative AI is the thorny issue of data security. Companies are cautious about allowing access to sensitive company data. However, Choudhary said that because the company's AI Analyst leverages the same Lightdash API used in its standard product, companies that are already comfortable with Lightdash security credentials can use its AI. It said it would not be exposed to any further risks.
“Data permissions and governance are one of the major hurdles for large enterprises to deploy these tools. With Lightdash's AI Analyst, you can take advantage of these operational capabilities right away. ” said Chaudhary. “This is important to realize: This is not a completely new query engine for customer data; it's actually a completely new way of interacting with existing query engines.”
Chaudhary also added that AI analysts rarely need access to a customer's actual data, as they rely on metadata such as metric titles and descriptions for much of their analysis. “Customers have complete control over the information they want to share with LLM,” he said.
Additionally, Chaudhary said customers can choose their preferred LLM provider, such as OpenAI or Anthropic, while also using their own models, allaying deep-rooted concerns about exposing access to a company's sensitive data. states that it is possible.
in the cloud
Since announcing its commercial launch and $8.4 million in seed funding two years ago, Lightdash has launched a hosted cloud service of its core open source product with additional features such as security tools. Chaudhary said more than 5,000 teams are currently running open source products themselves, often as a starting point before upgrading to the full feature set available in commercial versions.
“Large teams have successfully used OSS products to run proofs of concept without being hampered by information security or procurement reviews,” says Chaudhary. “This allows businesses to separate the purchasing process from the Lightdash trial, greatly reducing the barriers to trying out the tool and building an internal Lightdash following before moving to a cloud offering. Lightdash OSS It also provides a complete feature set to get started, making it easy to introduce BI to enthusiasts and small teams, with managed deployment, additional functionality, and performance benefits as your team scales up. They prefer cloud platforms for better security.”
In fact, Chaudhary said his company's customers include Workday, a $60 billion enterprise software company, as well as Beauty Pie, Hypebeast, Morning Brew, and others, and that the company's revenue has increased by 7.7 billion in the past year. It is said that it has grown twice as much.
Currently, Lightdash claims to have a global footprint of 13 employees split between Europe and the US, and the new funding injection will help the team and The company said it is aiming to expand its products. AI analyst.
In addition to lead backer Accel, Lightdash's Series A round included Operator Partners, Shopify Ventures, Y Combinator, and a handful of angel investors.