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Powerful new capability enables AI agents to autonomously detect, prioritize, and resolve complex anomalies
CAMPBELL, Calif., April 29, 2025 (GLOBE NEWSWIRE) -- Acceldata, a leading provider of data observability and agentic data management solutions, today announced Adaptive AI Anomaly Detection, a cornerstone capability of its revolutionary xLake Reasoning Engine that automatically identifies hidden, multi-dimensional data anomalies before they disrupt business operations, establishing a new benchmark for autonomous data quality.
Traditional anomaly detection tools identify obvious, one-dimensional errors-like a misplaced zero in a sales figure that incorrectly turns millions into tens of millions. Acceldata Adaptive AI not only identifies one-dimensional errors, but also pinpoints new hidden anomalies across multiple data dimensions, reducing manual analysis that previously took weeks to minutes. It brings business-level clarity to anomaly detection, not just data-level alerts.
"With Adaptive AI Anomaly Detection integrated into our xLake Reasoning Engine, Acceldata is pioneering the future with agentic data management,” said Rohit Choudhary, CEO of Acceldata. "By equipping intelligent agents with advanced capabilities to autonomously detect, prioritize, and resolve complex anomalies, we enable enterprises to uncover hidden patterns and risks that conventional approaches simply miss. It will detect problems before they cause significant business impact”
Key Features of Adaptive AI Anomaly Detection
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- Multi-Dimensional Detection: Simultaneously evaluates anomalies across multiple attributes such as Sales, Product ID, Region, and Time.
- Intelligent Sampling: Prioritizes high-risk data segments, optimizing both performance and resource utilization.
- Autonomous Pattern Recognition: Detects unique patterns that static rule-based systems cannot, adapting continuously without manual tuning.
that data quality issues alone cost enterprises up to $15 million per year, yet most tools in use today detect less than a third of data anomalies. Acceldata's Adaptive AI Anomaly Detection changes that equation by empowering autonomous agents to detect and remediate anomalies without the need for human intervention. These agents surface insights at the business level or use case level rather than merely flagging raw data spikes, allowing organizations to address root causes more effectively. As a result, resolution times shrink from weeks to hours, dramatically improving operational agility and data reliability.
Agentic Data Management Use Cases Enabled by Adaptive AI Anomaly Detection:
Acceldata collects extensive metadata across the data estate and monitors signals from data, pipelines, infrastructure, users, and costs. When combined with multi-variate anomaly detection, this forms a powerful foundation for autonomous agents to uncover complex interdependencies that traditional tools often miss. These agents can then take real-time action-solving use cases like business-impact forecasting and compliance alerts, marking a major shift from reactive monitoring to intelligent, agent-driven remediation.
- Data Quality Enhancement: Automatically detect hidden and compound anomalies across multiple data fields, ensuring accurate, reliable, and trusted datasets.
- Root-Cause Correlation: Link infrastructure failures with pipeline breakdowns and data spikes to pinpoint root causes.
- Cost Spike Diagnosis: Trace budget overruns to specific workloads, users, inefficient queries or processes across systems.
- Compliance Breach Alerts: Detect unusual access patterns by correlating user identity, location, and data sensitivity.
- Business Impact Forecasting: Connect upstream data issues with downstream analytics to prevent decision-making errors.
- SLA Violation Prevention: Identify early signals of delays by correlating processing times, data volumes, and resource constraints.
Join Acceldata at Autonomous 25
Acceldata is hosting Autonomous 25, the premier user conference where data leaders and AI innovators come together to shape the future of agentic AI on May 19-20, 2025 in San Francisco. Featuring keynote addresses from AI luminaries such as Cassie Kozyrkov, former chief decision scientist at Google, the event will explore how the next wave of AI is reshaping business models, operating structures, and the future of enterprise decision-making to usher in an era of intelligent autonomy across every domain. Click here to register.
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About Acceldata
Founded in 2018, Campbell, CA-based Acceldata is a leading provider of data observability and agentic data management solutions, empowering organizations to gain actionable insights into their data infrastructure. With advanced AI technology, Acceldata offers unparalleled visibility into data pipelines, enabling organizations to optimize performance. Acceldata's solutions have been embraced by global customers, such as Dun & Bradstreet, PubMatic, PhonePe (Walmart), HCSC, and many more. Acceldata investors include Insight Partners, March Capital, Industry Ventures, Lightspeed, Sorenson Ventures, Sanabil, and Emergent Ventures. Contact us to learn about the benefits of agentic data management.
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Amy McDowell
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