Social Media

Light
Dark

Data transformation startup Prophecy lands $35M investment

Prophecy, a platform designed for companies seeking to revolutionize their data processes through low-code development, has just announced its successful completion of a Series B funding round, securing $35 million. The round was led by Insight Partners and SignalFire, and notable participation came from J.P. Morgan, Singtel Innov8, Databricks Ventures, and Dallas Venture Capital. With this infusion of capital, Prophecy’s total raised funds now amount to $67 million, which will be instrumental in advancing the Prophecy platform and bolstering customer acquisition endeavors, as stated by the co-founder and CEO, Raj Bains, in an email interview with TechCrunch.

Bains emphasized that despite temporary disruptions in software purchasing due to the pandemic and economic slowdown, enterprise spending has remained robust. Prophecy’s revenue has been doubling every two quarters, demonstrating the company’s resilience and robust market position. Bains, who had previously worked at Microsoft and Nvidia, identified a long-standing bottleneck in data transformation, prompting him to launch Prophecy. He noted that many existing data transformation platforms were ill-suited for contemporary AI and analytics projects.

Recent surveys have affirmed the challenges faced by organizations that build their own data pipelines. Notably, these efforts consume significant resources, with a median of 12 data engineers dedicating 44% of their time at an average cost of $520,000. Data engineers also reported being stretched to their limits, with 84% expressing their workload exceeded capacity, and 34% indicating that data integration, collection, and transformation required more than half of their workday.

Prophecy offers a unique solution termed “visual development” combined with code. The platform features a user-friendly drag-and-drop interface for constructing code-based data pipelines that come with reliability guarantees. It also introduces “packages” – reusable components containing business logic, operational logic, and code. Prophecy is available as both a fully managed cloud service and an on-premises solution. It includes a tool called Data Copilot, which leverages large language models and organization-specific knowledge graphs to streamline data transformations. Data Copilot constructs data transformation pipelines based on natural language prompts, eliminating the need for manual code or drag-and-drop editing.

Bains stressed that “Prophecy enables self-service data transformation for a broader class of users, especially non-coding data teams in the lines of business.” It converts visual pipelines into open-source code using languages such as PySpark, Scala, or SQL, ensuring that customers are not locked into proprietary systems and can adhere to best software practices.

In the competitive landscape, Prophecy faces rivals like Coalesce, Informatica, Talend, Incorta, and Etleap. Nonetheless, the market for data integration appears promising, with Grand View Research projecting a 12.3% growth from 2023 to 2030, following its $11.91 billion valuation in 2022.

Bains claimed that Prophecy already serves “thousands” of users across “multiple” Fortune 500 companies, including those in the banking, healthcare, and tech sectors. The company has experienced a remarkable 400% year-over-year revenue growth since its Series A funding round in January. Bains noted that Prophecy typically caters to customers willing to invest significantly in software licenses, with some of the largest clients exceeding a million dollars. This approach aids in delivering analytics- and AI-ready data more swiftly to empower data-driven decision-making, a priority for many chief data officers.

As part of the recent investment, Herb Cunitz, former president of Hortonworks, will join Prophecy as a board member, and Elena Zislin, a managing director at J.P. Morgan, will serve as a board observer.

Leave a Reply

Your email address will not be published. Required fields are marked *