Hidden Anomalies Are Costing You Millions—And You Won’t See Them Coming but Agents do
Data is at the heart of every enterprise decision, yet most businesses don’t realize how often it silently fails them. Beneath the surface of financial models, supply chains, and AI-driven insights, data anomalies creep in undetected—until it’s too late.
And the cost? It’s staggering.
- Gartner estimates poor data quality costs organizations an average of $12.9–15 million per year.
- Harvard Business Review reports that knowledge workers spend 50% of their time fixing bad data instead of driving business value.
It’s Time for Data to Defend Itself
At Acceldata, we're shaping a future where data evolves beyond a passive asset to become a proactive intelligence—actively monitoring, learning, and autonomously ensuring business continuity. We call this Agentic Data Management (ADM), a transformative approach driven by intelligent agents working together, powered by the advanced cognitive capabilities of our xLake Reasoning Engine.
Think of the xLake Reasoning Engine as a contextual memory of your data operations, intelligently orchestrating various agents to autonomously handle tasks across your data ecosystem - ranging from routine maintenance to complex anomaly resolution. These agents not only act independently but also engage in seamless communication with each other, exchanging critical insights to preemptively address potential disruptions.
With xLake’s exabyte-scale AI-driven processing power, your AI agent can now understand the context, measure potential business impacts, prioritizes responses, and activates self-healing capabilities within your data pipelines. This means fewer disruptions, increased reliability, and significantly reduced risk.
Meet Adaptive AI Anomaly Detection: The AI That Catches Data Issues Before They Catch You
From schema drift in financial transactions to misreported stock levels in retail, Acceldata Agentic DM can leverage multi-variate AI detection capabilities to proactively identify, prioritize, and surface critical data anomalies before they disrupt business operations.
Intelligent Sampling: AI autonomously identifies high-risk segments, reducing monitoring costs while improving precision.
Multi-Dimensional AI Detection: Unlike traditional tools, Auto Anomalies correlates patterns across multiple columns, timestamps, and segments, exposing hidden issues that single-metric monitoring misses.
Adaptive Learning & Prioritization: Auto Anomalies eliminates manual threshold settings, automatically learning from data patterns to surface the most critical anomalies first.
Powered by xLake Reasoning Engine for Enterprise-Scale AI
xLake is more than a data processor—it’s the AI brain of your data ecosystem.
It is an exabyte-scale, AI-aware data processing engine that operates seamlessly across hyperscalers, data clouds, and on-prem environments. Designed to handle the complexities of modern data ecosystems, xLake is an intelligent orchestration layer that continuously learns from data patterns, detects anomalies, and optimizes workflows in real time. Detecting and remediation of anomalies is the core capability within xLake, bringing advanced multi-variate anomaly detection and self-learning capabilities to enterprise data observability.
Picture this: your transaction streams start experiencing unexpected anomalies. Immediately, detection agents pick up on this irregularity and alert diagnostic agents, who swiftly assess and identify the underlying causes. Without delay, remediation agents autonomously deploy targeted fixes, while recommendation agents proactively advise on preventive measures for the future. Together, these intelligent agents seamlessly manage your entire data stack at scale, enabling your team to focus on strategic initiatives rather than routine operational firefighting.
"Acceldata has revolutionized our data quality management, reducing processing times from weeks to hours. This efficiency enables us to proactively address data issues, ensuring our clients receive the most reliable information possible."
— Vice President of Data Quality Insights, Global Data Provider
What does that mean for AI Model & Data Architects
For years, you’ve relied on manual checks, static rules, and siloed monitoring, yet data issues still slip through. Reactive detection means errors are found only after the damage is done, while single-metric monitoring overlooks multi-dimensional anomalies that impact entire datasets. Despite spending millions on data quality efforts, businesses continue to suffer from undetected failures, regulatory risks, and financial losses—with 68% of data issues going unnoticed until it’s too late.
These silent failures manifest in real-world chaos:
Ready to Make Your Data Work for You?
This is more than just anomaly detection. This is the next frontier of AI-driven data observability—one where your data doesn’t just inform but also acts. Acceldata is empowering enterprises to build intelligent, self-governing data ecosystems that redefine reliability and resilience.
At Acceldata, we are shaping the future of autonomous AI for data intelligence. Join us in this journey, and let’s build the next generation of data-driven enterprises together.
Because the best way to fix a data issue is to stop it before it ever happens.
Acceldata Agentic DM, currently in private beta, launches with 10+ Agents. Apply here to join the private beta waitlist. Watch the unveiling of Agentic DM at Autonomous 25 (the premier Data Management Conference for the AI Era) and see how your enterprise can benefit from it.
.webp)
.webp)
.webp)