Anomalo, a leader in reinventing enterprise data quality, announced a significant enhancement to its innovative second product, Unstructured Data Monitoring, with the launch of Workflows. This major upgrade is now generally available, empowering organizations to efficiently manage and monitor vast volumes of unstructured data across data warehouses, data lakes, and cloud storage platforms.
Unstructured Data Monitoring enables enterprises to extract valuable insights and identify data quality issues from unstructured datasets such as documents, call transcripts, emails, messages, and order forms — resources traditionally difficult to analyze. With the introduction of Anomalo Workflows, the solution evolves beyond simple monitoring into a comprehensive hub for managing unstructured data quality and operational workflows.
Building on its pioneering AI-powered monitoring of unstructured text first announced in June last year, and expanded with new capabilities in November, Anomalo continues to advance its mission: delivering trusted data across all types and use cases.
Anomalo’s General Manager of Generative AI Products, Vicky Andonova, will present a detailed session on the Unstructured Data Monitoring product at the Snowflake Summit on Tuesday, June 3 at 3:30 p.m. Meanwhile, Nationwide will share insights on enterprise data governance and preparing for Generative AI initiatives at the Databricks Data + AI Summit on Thursday, June 12 at 12:20 p.m.
“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. You can think of our Unstructured Monitoring product and Anomalo Workflows as building blocks that can be assembled in thousands of configurations to achieve pretty much any customer use case for unstructured data quality or insights. Take one of our large retail customers who is trying to mine support tickets and call logs to understand why customers are unhappy. That kind of analysis wasn’t easily possible before Anomalo. Just as we redefined data quality for structured data, we’re now helping enterprises trust and extract value from unstructured data at a scale no other tool can match,” said Elliot Shmukler, co-founder and CEO of Anomalo.
Also Read: Hex Raises $70M to Transform Data Science With AI
Anomalo’s initial product leverages AI to automatically detect anomalies and issues in structured data, enabling teams to fix problems before making decisions, running operations, or powering AI and machine learning workflows. Trusted by customers across major industries, the solution serves six of the Fortune 50 companies and four of the world’s largest telecom providers.
Yet, structured data accounts for only about 20% of enterprise data. The remaining 80% — unstructured content like documents, transcripts, emails, and messages — is increasingly critical for driving success, especially as organizations embrace Generative AI workflows. Deploying retrieval-augmented generation (RAG) systems or customer-facing chatbots demands high-quality, domain-specific data fed to large language models (LLMs). However, companies often lack visibility and trust in their unstructured data, hindering timely delivery of production-ready AI applications.
Anomalo’s Unstructured Data Monitoring product empowers enterprises to curate and evaluate unstructured text across multiple quality dimensions, including document length, duplicates, topics, tone, language, abusive language, personally identifiable information (PII), and sentiment. This enables rapid assessment of document collections and identification of issues within individual documents, significantly reducing the time to prepare high-value unstructured data for analytics and AI use cases. Alongside 15 out-of-the-box quality checks, customers can create custom criteria and severity scores tailored to their specific document quality standards.
With the new Anomalo Workflows, customers can now:
-
Detect and remediate quality issues such as duplicates, errors, PII, and abusive language
-
Analyze large-scale unstructured content to uncover patterns and generate actionable insights
-
Transform unstructured data into structured formats optimized for downstream analytics and Gen AI workflows
-
Curate clean, reusable document sets for training or retrieval tasks
The platform offers unmatched scalability and speed — capable of analyzing over 100,000 documents in a single run and continuously monitoring new data, turning a previously manual, months-long task into a process that takes just minutes.
“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. Through our collaboration with Anomalo, we’ve started exploring how their Unstructured Data Monitoring can surface meaningful patterns in support tickets and guest feedback. We’re excited about the power to turn this data into actionable insights, strengthen our Gen AI initiatives and bring high-quality unstructured data into everything we build,” said Sid Stephens, data governance lead at one of the largest fast food chains in the US.