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Today, San Francisco-based Atlan, a startup working to bring some order to the “data chaos” that enterprises face, announced it has raised $105 million in a series C round of funding.
The investment takes the company’s valuation to more than $750 million. The funding has been led by Singapore’s sovereign wealth fund GIC and Meritech Capital, with participation from existing investors Salesforce Ventures and PeakXV Partners. Atlan said it will use the capital to further develop its product, which acts as a unified control plane to stitch disparate data infrastructure, right from data platforms like Databricks to CRMs such as Salesforce 360.
The company will also use some part of the funding to grow its footprint and meet the surging demand for data organization in the age of AI.
“Over the past year, boards have consistently asked CIOs and CDOs about their AI roadmaps, who have realized that the main hurdle isn’t AI models but the lack of AI-ready data—data enriched with business context, trust, and security. Atlan is addressing this by building the control plane for the data and AI stack, integrating trust and context into the digital fabric,” Prukalpa Sankar, co-founder of the company, said in a statement.
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Understanding Atlan’s approach to data handling
Today, data chaos is very real. Be it a large conglomerate or a young startup, every company is using dozens of tools across its stack and generating massive volumes of structured and unstructured data at different levels. Some of this information is stored across data platforms like Snowflake, while the rest remains siloed, waiting to be utilized. According to a Digitization of the World study, the growth has been such that 80% of the world’s data will be stored in enterprises by 2025.
Founded in 2020, Atlan stitches all this information in one place, producing a clear picture of the data assets with relevant context and collaboration options. Sankar, who started the company with Varun Banka as an internal project for their previous startup, describes it as a “home for data teams.”
“The base layer is what we call a ‘Metadata Lakehouse.’ We have native connectors with the common data tools & systems that allow us to quickly sync metadata with them… We can collect anything as metadata, including technical things like where data lives, social metadata on who is using it and how, operational metadata on how it moves and is processed until it reaches a consumer of data in something like a dashboard, and even compliance metadata like whether it contains sensitive information,” Sankar told VentureBeat.
On top of this base layer sits a trust layer that enables access management, analytics of the data estate and classification and tagging. It is paired with personalized modules for data discovery, business metrics glossary, data products & contracts and no-code data lineage. This helps data and business teams understand the information flowing across the enterprise and search and collaborate on it to fix problems.
“Data Engineers can have a visual, detailed lineage chart where they can foresee the impact downstream of changing something in a data system, and automatically push alerts to those business users who will be affected. Business teams can search for trusted data, and use data products that have been curated for someone in their role. Meanwhile, those responsible for governing data can write policies and connect them to data assets so they are automatically alerted only if an asset might be violating a policy they own,” she explained.
Significant growth in recent years
Despite being fairly young in the data infrastructure space, Atlan seems to have carved a niche for itself. The company has seen significant adoption at the enterprise level, especially since the rise of gen AI. Over the last two years, its revenues have ballooned more than seven times with multiple major customers coming on board. This includes notable industry names such as Cisco, Autodesk, Unilever, Ralph Lauren, FOX, News Corp, Nasdaq, NextGen, Plaid and HubSpot.
“While many new customers are coming to us to get their data AI-ready, we also see demand from other C-level business initiatives like democratizing use of data across business teams and delivering data products to customers. We have increasingly been brought in as not just a catalog/discovery solution, but a metadata control plane that enables everyone to better leverage data for these use cases,” Sankar noted.
Overall, the company claims its platform can cut the time spent by data practitioners on finding and understanding data by as much as 95%. When compared to other players in the same space such as Informatica, Collibra and Alation, Atlan claims to be winning three-quarters of the deals. It also noted that most of these players have a manual approach to collecting metadata while its proprietary platform focuses on automating the whole thing with a highly configurable rules-based automation tool and the industry’s first AI copilot for metadata creation.
As the next step, Atlan plans to build on this work and rope in more enterprises looking to bring order to their data chaos. Sankar says part of the funding will go towards supporting key product developments and integrations while the other part will boost operational expansion to meet the demand of the current market.
