Use cases
OUTLIERS IN APP METRICS
Detect customer experience issues
We build advanced solutions that collect thousands of application metrics, leveraging machine learning models to detect anomalies in real time. These algorithms detect unexpected drops and spikes in traffic, conversion rates, session durations, and other mission-critical IT metrics. React quickly to issues affecting user experience and minimize service disruptions with near real-time anomaly detection.
OUTLIERS IN SYSTEM METRICS
Detect stability issues
Monitor vast amounts of system metrics in data centers and clouds with advanced outlier detection solutions. Correlate metrics and identify complex anomalous patterns and outliers involving multiple metrics, allowing you to detect issues that single-metric analysis would miss.
ANALYTICS AND INVESTIGATION
Perform root cause analysis in seconds
Experience faster and more convenient incident investigation with tools that emphasize operational efficiency. Analyze metric dependencies and automatically identify segments related to current incidents in the full volume of data. Enable your IT operations teams to quickly perform root cause analysis and troubleshoot issues.
OUTLIERS IN DATA
Detect data quality issues
Integrate models and algorithms into your data processing pipelines and data lakes to continuously monitor data quality. Automatically prevent corrupted or suspicious data from propagating into downstream data processing jobs and analytical reports. Process massive data volumes and integrate with big data platforms and public cloud services like Spark, AWS EMR, and Google Dataproc using algorithms specifically designed for data quality applications in IT environments.
ANOMALY DETECTION FOR SECURITY
Detect security breaches
Solve various fintech, e-commerce, and technology security-related problems such as intrusion detection, unauthorized access attempts, and data breach prevention. Achieve maximum efficiency in protecting your IT infrastructure by combining supervised and unsupervised anomaly detection algorithms with short-term and long-term security monitoring models.
Our clients
RETAIL
HI-TECH
MANUFACTURING
FINANCE & INSURANCE
HEALTHCARE
How our anomaly detection solutions work
Industries
We develop anomaly detection solutions for several industries including retail, ecommerce, manufacturing, technology, and video games
Retail
Optimize retail operations by monitoring point-of-sale and inventory systems for unusual patterns. Flag potential fraud in transaction data, alert to unexpected stock fluctuations, and detect abnormal e-commerce traffic. This helps prevent system errors, stockouts, and website performance issues, ensuring smooth operations and customer experiences.
Manufacturing
Enhance IT operations by monitoring ERP systems and production management software. Identify anomalies in data flows between systems, predicting potential integration failures. Detect unusual patterns in inventory or order data to prevent disruptions, and optimize network performance by identifying irregular server loads, ensuring reliable access to critical manufacturing applications.
Technology
Anomaly detection is vital for tech, media, and telecom IT, optimizing network infrastructures and cloud services. Identify unusual traffic in content delivery systems to prevent outages, detect anomalies in server performance for proactive maintenance, and spot irregular patterns in telecom networks to prevent service degradation and security breaches.
Wealth management
Anomaly detection optimizes wealth management IT by monitoring portfolio software and financial tools. Identify unusual trading patterns or account activities to alert potential security breaches, detect anomalies in client reporting data aggregation, and spot irregular patterns in market data feeds to maintain real-time financial information integrity.
Insurance
For insurance, anomaly detection enhances policy management and claims processing. Identify unusual claims patterns to flag potential fraud, detect anomalies in risk assessment calculations for accurate pricing, and spot unusual customer behavior in CRM systems to optimize performance and prevent data breaches.
Pharma
Anomaly detection in pharma IT enhances quality control and compliance. It monitors manufacturing processes, flagging deviations in critical parameters to prevent batch failures. In clinical trials, it identifies unusual patterns in patient data, uncovering potential adverse reactions. For drug safety, it analyzes post-market data to detect rare side effects.
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Accelerate your journey to AI
We provide flexible engagement options to design and build an automated anomaly detection solution for your company. Contact us today to start with a workshop, discovery, or proof-of-concept (POC).
Workshop
We offer free half-day workshops with our top experts in application modernization to discuss your stream processing strategy, challenges, modernization opportunities, and industry best practices.
Discovery
If you’re at the application modernization and cloud migration strategy development stage, we can start with a 2–3 week discovery phase to perform an analysis of your existing application portfolio, create a target architecture, and build a modernization roadmap.
Proof of concept
If you’ve already identified a specific use case for application modernization, we can start with a 4–8 week proof-of-concept project to modernize a few key applications to deliver tangible results for your company.
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