Secoda raises $14M to bring AI-driven, Google-like search to enterprise data
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Toronto-based Secoda, an AI-powered platform for data search, cataloging, lineage and documentation, today announced $14 million in a Series A round of funding. The company plans to use the capital to further develop its AI solutions and allow any enterprise user, regardless of their technical background, to search, understand and use company data — in an experience as easy as searching on Google.
The investment takes Secoda’s total fund-raise to $16 million and has been led by existing investor Craft Ventures, with participation from Abstract Ventures, YCombinator and Garage Capital. Notable data ecosystem leaders Jordan Tigani (CEO of MotherDuck), Scott Breitenother (CEO of Brooklyn Data) and Tristan Handy (CEO of dbt) also joined the round.
“It has become increasingly important that companies not only have a full understanding of the lineage of their data from disparate sources but also harness their data to make more efficient and informed decisions. Secoda has built a powerful AI-powered data copilot for companies to do just that,” Jeff Fluhr, co-founder and partner at Craft Ventures, said in a statement.
Solving the data problem
Today, the enterprise IT stack is a web of dozens of systems designed for different tasks. The arrangement is critical for the effective functioning of the organization, but it also leads to a disjointed data puzzle, where applications don’t communicate with each and data remains siloed.
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As a result, every time an employee needs to answer a question related to data, they are either searching high and low across complicated applications or nudging the data team on the shoulder and taking their attention away from other tasks.
“Questions that seem simple enough to answer end up feeling like a huge, frustrating game of broken telephone,” Etai Mizrahi, who witnessed similar challenges when working at Acadium, told VentureBeat.
To address this gap in knowledge access, Mizrahi worked with colleague Andrew McEwen and launched Secoda, an all-in-one platform for data management and search, in 2021.
![Secoda Search](https://venturebeat.com/wp-content/uploads/2023/09/search.jpg?w=800&is-pending-load=1#038;resize=1280%2C960&strip=all)
Secoda integrates with business intelligence and transformation tools as well as data warehouses — connecting to everything in a team’s fragmented tech stack — to create a single source of truth for company data.
Then, using a ChatGPT-powered assistant, the company allows users to write documentation (adding supplementary context to the metadata) and search their company’s newly unified data catalog with natural language queries.
“Secoda does not simply give you information, but gives you answers, much like Google…Our customers have been able to leverage the platform to reduce the volume of inbound data requests by over 40%, reduce onboarding times by 50%, and reduce time teams spend on documentation by 90% — huge time savings for data teams,” Mizrahi noted.
Road ahead
With this round of funding, Secoda plans to strengthen its engineering team and do more R&D to build out the platform, especially the AI bits. The company will also introduce Secoda Monitoring to help data teams ensure the data being consumed by them is high quality and accurate.
“With one click, users should be able to understand what assets are affected by changes and how to reduce data quality errors. Building monitoring into discovery tools will also allow companies to keep tabs on the operational efficiency of a data team – tracking costs generated by the many tools in a company’s tech stack and helping companies save costs,” Mizrahi explained.
Over the last year, Secoda’s customer base has grown fivefold, with over 100 million metadata resources (tables, dashboards, columns, queries, and more) under management. On the integrations side, the data search tool currently supports 36 popular data warehouses, business intelligence tools and productivity platforms, including Snowflake, dbt and Looker.
The company says it will continue to add more connectors on the basis of popularity and use demand.
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