Prophecy's AI Platform Wins InfoWorld's 2025 Tech of the Year Award

PALO ALTO, CA – January 06, 2026 – Foundry's InfoWorld has named Prophecy a winner in its prestigious 2025 Technology of the Year Awards, recognizing the company for its leadership and innovation in the crucial 'Data management: pipelines' category. The award highlights a significant industry shift towards AI-augmented tools that are fundamentally reshaping how enterprises prepare and analyze data.

The InfoWorld awards celebrate the most impactful and innovative products across software development, DevOps, data management, and AI/ML. This year's selections underscore the growing influence of artificial intelligence in practical business applications.

"Artificial intelligence is reshaping products across the technology landscape, often in surprising ways," said Doug Dineley, Executive Editor at InfoWorld. "Our 2025 Technology of the Year Award winners are the products at the leading edge of innovation — the ones putting the power of AI to practical use for enterprises."

For Prophecy, the award serves as a powerful validation of its mission to democratize data preparation through a cloud-native platform that uses AI agents to assist users at every step. "We're excited to be named an InfoWorld Technology of the Year 2025 Winner," said Raj Bains, Prophecy Founder & CEO. "It reflects what our team has done to bring AI agents to make data prep & analysis faster and more productive, providing an alternative to primarily desktop-based products such as Alteryx."

Redefining Data Pipelines with AI Agents

At the heart of Prophecy's award-winning platform are its sophisticated AI agents, designed to function as collaborative partners for data professionals. These agents are not merely automating simple tasks; they are integrated into the entire data workflow, from initial discovery to final deployment. This approach transforms the traditionally complex and time-consuming process of building data pipelines into a more intuitive and efficient experience.

The platform operates on a "Generate → Refine → Deploy" model, where human expertise and AI efficiency work in tandem. Users can describe their data needs in natural language, and the AI agents can generate complete data pipelines, suggest transformations, and even write the underlying code. This functionality extends across a spectrum of tasks that historically created bottlenecks for data teams.

For instance, the AI agents assist with data discovery by allowing users to search and explore datasets within their cloud data warehouse using simple text queries. When building pipelines, users can either generate a full workflow from a single description or add transformations incrementally with AI-powered suggestions. The system provides live previews of data transformations, allowing users to validate changes on the fly. Beyond generation, the AI also helps optimize pipelines by identifying redundant steps and improving overall readability and performance. Crucially, it automates the often-neglected tasks of generating documentation, creating data quality tests, and assisting with version control, ensuring that the resulting pipelines are robust and maintainable.

This deep integration of AI allows data teams to move from spending up to 80% of their time on manual data preparation to focusing on higher-value analysis and insight generation. The result is a dramatic acceleration in project timelines, enabling organizations to deliver clean, trusted data for analytics and AI initiatives faster than ever before.

Bridging the Analyst-Engineer Divide

One of the most significant challenges in enterprise data management has been the operational and technical gap between data analysts and data engineers. Analysts, who possess deep business context, have often been limited by desktop tools that do not scale, while data engineers, who manage production systems, must frequently rewrite the analysts' work from scratch to meet enterprise standards for performance and governance. This disconnect creates inefficiency, delays, and friction.

Prophecy directly addresses this long-standing problem by creating a unified platform that serves both roles. It effectively "breaks the tool boundary" by empowering data analysts to independently build sophisticated data workflows using a visual, AI-assisted interface. These workflows are not simple prototypes; they are built on a foundation of open, high-performance code that is ready for production.

When an analyst builds a pipeline visually, the platform simultaneously generates clean, standardized Spark code. This code is immediately accessible to data engineers, who can review, refine, and deploy it directly to the cloud data platform without a time-consuming rewrite. This unified environment fosters a new level of collaboration, where analysts and engineers can work on the same projects using interfaces tailored to their skills—visual for analysts, code for engineers—while the underlying asset remains consistent.

This approach democratizes data pipeline development without sacrificing control. Central data platform teams can define governance rules and compliance guardrails within Prophecy, ensuring that all user-generated workflows adhere to enterprise standards. This allows business teams to achieve self-service autonomy in a secure and governed framework, accelerating their ability to derive insights from data while freeing up engineering resources to focus on more complex architectural challenges.

A Cloud-Native Challenge to Legacy Systems

Prophecy's recognition also highlights a broader market trend: the migration from legacy, on-premise or desktop-based tools to modern, cloud-native solutions. For years, tools like Alteryx, originally developed for Windows desktops, were the standard for business user data preparation. However, as enterprises increasingly standardize their data infrastructure on powerful cloud data platforms like Databricks, Snowflake, and BigQuery, they require tools that can operate natively within these ecosystems.

Prophecy was built from the ground up as a cloud-native solution. This architecture provides inherent advantages in scalability, performance, and governance. Unlike desktop tools that may require data to be moved out of the central cloud platform for processing, Prophecy runs its workloads directly on the customer's cloud data platform. This not only improves performance but also enhances security and simplifies governance, as data never leaves the managed environment. Its deep integration with platforms like the Databricks Lakehouse allows organizations to leverage existing security models, such as Unity Catalog permissions, and enforce cost and cluster management policies seamlessly.

This modern approach positions Prophecy as a compelling alternative for companies looking to modernize their data stack. The company even offers an AI-powered "Migration Copilot" designed to automate the conversion of workflows from legacy systems like Alteryx. This tool can translate workflows that would take weeks to migrate manually in a matter of minutes, significantly lowering the barrier for organizations to transition to a more scalable, governable, and cost-effective cloud-native data preparation process.

Industry Validation and Market Disruption

The InfoWorld Technology of the Year award is more than just a company milestone; it serves as a key market signal. In the highly competitive data management landscape, such recognition provides strong validation of a company's technological vision and its execution. It indicates that Prophecy's AI-driven, collaborative approach is not just innovative in theory but is delivering tangible value in real-world enterprise environments.

The market for data pipeline tools is crowded with solutions ranging from open-source frameworks like Apache Airflow to established enterprise platforms. However, Prophecy's unique focus on combining generative AI, a visual interface, and a code-based backend on a single cloud-native platform sets it apart. It directly addresses the dual needs of modern data teams: the business's demand for speed and agility, and IT's requirement for governance and scalability.

As organizations race to deploy AI and machine learning models, the efficiency and reliability of their data pipelines have become a critical determinant of success. The manual, fragmented processes of the past are no longer sufficient. By leveraging AI to automate and streamline data preparation, platforms like Prophecy are enabling companies to build the robust data foundations necessary to power next-generation analytics. This award from a respected industry voice like InfoWorld solidifies the company's position as a key innovator and a disruptive force in the evolution of enterprise data management.