Anomalo, a leader in enterprise data quality, has introduced Workflows to its Unstructured Data Monitoring product, which is now generally available. This innovation enables enterprises to manage and extract insights from vast volumes of unstructured data stored in data warehouses, data lakes, and cloud storage. By addressing data quality and providing actionable insights, Anomalo empowers organizations to trust and leverage unstructured data for Gen AI initiatives.
Anomalo’s Unstructured Data Monitoring product, first introduced with AI-powered text monitoring in June 2024, now includes Workflows, a hub for managing and monitoring unstructured data. This advancement moves beyond traditional data quality platforms, enabling enterprises to curate and evaluate unstructured text for characteristics like document length, duplicates, tone, and sentiment. With 15 out-of-the-box issue detectors and customizable options, businesses can ensure high-quality data for Gen AI workflows, such as RAG systems and chatbots.
Unstructured data, comprising 80% of enterprise data like documents, emails, and call transcripts, is critical for Gen AI success. Anomalo’s platform addresses the challenge of unknown data quality by analyzing large volumes of unstructured content to identify patterns and issues. “Everyone’s talking about unstructured data for Gen AI but the real breakthrough is solving for both quality and insights within this type of data,” said Elliot Shmukler, co-founder and CEO of Anomalo. The platform can process over 100,000 documents in a single run, transforming months-long manual tasks into a 10-minute process.
Anomalo’s Workflows enable enterprises to identify and correct quality issues, such as duplicates and abusive language, while curating clean document sets for analytics and Gen AI training. For instance, a major retail customer uses Anomalo to mine support tickets and call logs to understand customer dissatisfaction, a task previously unfeasible. “In the restaurant service industry, understanding and acting on guest experiences is critical and that means unlocking insights from the tens of thousands of unstructured comments we receive each month,” said Sid Stephens, data governance lead at one of the largest fast food chains in the US. This capability strengthens enterprise Gen AI initiatives by ensuring high-quality, domain-specific data.
Anomalo’s innovation is gaining attention, with Vicky Andonova, GM of Gen AI Products, presenting at the Snowflake Summit on June 3, 2025, and Nationwide discussing enterprise data governance at the Databricks Data + AI Summit on June 12, 2025. By redefining data quality for both structured and unstructured data, Anomalo empowers organizations across industries to trust their data and accelerate Gen AI adoption.
Anomalo’s Unstructured Data Monitoring with Workflows positions the company as a leader in data quality, enabling enterprises to unlock the full potential of their unstructured data for Gen AI and beyond. This solution ensures organizations can confidently deploy production-ready applications while maintaining data trust and operational efficiency.
Anomalo is reinventing enterprise data quality with an AI-powered data quality platform. Anomalo uses machine learning to replace traditional rules-based systems and automatically detect and alert teams about data quality issues across both structured and unstructured data. With seamless integrations across the entire data stack, Anomalo ensures customers can confidently operate with data and AI before data quality impacts downstream business decisions, customer-facing applications and machine learning models. Anomalo is backed by Databricks Ventures, Snowflake Ventures, SignalFire, Smith Point Capital, Norwest Venture Partners, Foundation Capital, Two Sigma Ventures, Village Global and First Round Capital.
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