Data observability startup Acceldata today announced that it raised $10 million in an extension to its Series C round, bringing its total raised to over $100 million.
New investor Prosperty7 Ventures was the sole contributor to the tranche, according to Acceldata co-founder and CEO Rohit Choudhary, which will be put toward go-to-market efforts, mergers and acquisitions, R&D (particularly in Canada, where Acceldata recently opened offices) and geographic expansion.
“In the last five years, customers have added petabytes of data across their hybrid cloud infrastructures,” Choudhary told TechCrunch in an email interview. “This has created a massive need for real-time observability solutions to manage their data, and we’re huge beneficiaries of the long-term investments into data infrastructure, AI and analytics.”
Data observability tools, or tools that enable companies to understand, diagnose and manage data health across multiple IT tools throughout the data lifecycle, continue to be one of the buzziest tech trends in big data. Last year, in the span of a single week, VCs poured hundreds of millions of dollars into three vendors — Cribl, Monte Carlo and Coralogix — developing tooling for data observability. How’s that for enthusiasm?
Acceldata’s founding team — which was working at Hortonworks, InMobi, 247.ai and Zalando before coming together to form the startup in 2018 — arrived at the conclusion that successful observability follows from tools that support experimentation and measure progress “consistently.”
“The world’s most valuable companies are data-driven,” Choudhary said. “These companies know that, to succeed with complex data systems, they need to understand what’s happening inside their data pipelines. Unfortunately, the vast majority of enterprises lack the bandwidth and expertise to build advanced in-house data observability systems … As a result, they suffer from suboptimal operational capabilities and poor return on data investments.”
Acceldata’s platform aims to ease the barrier to entry, monitoring data pipelines and infrastructure and helping investigate and remediate data quality issues as they crop up. That’s par for the course when it comes to data observability. But Choudhary claims that Acceldata is differentiated in that it’s one of the few products on the market that monitors an organization’s entire data supply chain, including the sources of data, data enrichment and data consumption (as well as the associated costs).
For example, Acceldata can be used to catch incomplete or incorrect data in AI model training data sets — a key use case considering that unreliable models often impact things like customer churn and revenue forecasts.
“Data leaders today are unable to deal with operational challenges such as performance consistency, data reliability, cost and user experience,” Choudhary said. “In order to handle all these, they need to apply AI and automation to achieve the right level of visibility, which reduces the time needed to spend fixing issues with their systems. Data observability allows data leaders to refocus their best engineering talent on activating more data for new business use cases.”
While Acceldata competes against heavyweights like Sifflet, Observe and Manta in an observability tools and platforms market that could be worth $4.1 billion by 2028 (up from $2.4 billion in 2023), it’s making moves to maintain what Choudhary describes as a position of strength.
Recently, Acceldata acquired AI platform Bewgle, whose founders will lead the AI team at Acceldata and work to expand the company’s AI-focused observability offerings. And Acceldata plans to grow its team, expanding from 216 full-time employees to 250 by the end of the year.
Choudhary claims that Acceldata, based in Campbell, California, now has over 150 customers, including Oracle, Dun & Bradstreet and Walmart’s PhonePe, and that its number of Fortune 500 clients doubled year-over-year this year.