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Custom data observability & quality platforms that eliminate annual cost of silent data failures

Build intelligent monitoring systems with automated anomaly detection, real-time validation, and AI-powered root cause analysis that prevent data downtime before it impacts business decisions and AI model performance.

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Data observability & quality platforms

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Challenges Xenoss eliminates with data observability & quality platforms

 

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Silent data failures causing millions of annual losses without detection

Data appears healthy but contains subtle corruption, schema drift, or quality degradation that goes unnoticed for weeks. Traditional rule-based monitoring can’t detect unknown anomalies, allowing bad data to corrupt downstream analytics, AI models, and business decisions.

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Manual data quality monitoring that doesn’t scale with enterprise complexity

Teams spend 80% of their time writing custom SQL checks and manually investigating data issues instead of building strategic solutions. Manual processes break down as data volumes grow, creating reactive firefighting rather than proactive system health management.

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Lack of real-time anomaly detection for AI and ML model performance

AI models degrade silently due to data drift, schema changes, and quality issues that traditional monitoring tools can’t detect. Without continuous model input validation, enterprises deploy biased or inaccurate AI systems that make costly decisions based on corrupted data.

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Inability to trace data lineage and identify root causes during incidents

When data quality issues occur, teams waste days manually searching through complex pipelines to find the source. Without automated lineage tracking and impact analysis, incidents cascade through downstream systems before teams understand affected components.

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False positive alerts overwhelming data engineering teams

Generic monitoring tools generate thousands of meaningless alerts that drown out real issues. Teams lose trust in monitoring systems and ignore critical alerts while spending excessive time investigating false alarms instead of genuine quality problems.

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Data observability gaps across distributed cloud and hybrid environments

Enterprise data spans multiple clouds, on-premise systems, and edge locations with inconsistent monitoring coverage. Teams lack unified visibility into data health across distributed architectures, creating blind spots where quality issues propagate undetected.

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Regulatory compliance violations due to data governance failures

Poor data quality leads to GDPR, HIPAA, and industry compliance breaches when inaccurate or incomplete data reaches regulated systems. Without automated data validation and audit trails, enterprises face regulatory fines and legal exposure from compliance failures.

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Reactive incident response delaying business-critical data availability

Data quality issues are discovered only after they impact dashboards, reports, or customer-facing applications. Without proactive monitoring and automated remediation, teams spend hours restoring data availability while business operations suffer from delayed insights.

Custom data observability & quality platform engineering for enterprise environments

Synthetic data generation pipelines

AI-powered anomaly detection engines with machine learning models

We develop intelligent monitoring systems that learn normal data patterns and automatically detect unknown anomalies, schema drift, and quality degradation. Our ML algorithms identify silent failures that traditional rule-based systems miss, preventing data corruption before it impacts business operations.

API-native process automation

Real-time data lineage tracking and impact analysis platforms

We create comprehensive data lineage systems that automatically map data flows across complex enterprise architectures. Our platforms provide instant root cause analysis and downstream impact assessment when quality issues occur, reducing incident response time from days to minutes.

Data quality and availability

Automated data quality validation and testing frameworks

We build intelligent validation systems that automatically generate data quality checks based on data patterns and business rules. Our frameworks include continuous testing pipelines, automated regression detection, and comprehensive quality scorecards for enterprise data assets.

Multi-Cloud strategy implementation

Enterprise-scale observability platforms for distributed environments

We engineer unified monitoring systems that provide complete visibility across multi-cloud, hybrid, and edge environments. Our platforms handle petabyte-scale data monitoring with consistent quality metrics, alerting, and governance across distributed enterprise architectures.

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Intelligent alerting systems that eliminate false positive noise

We develop context-aware alerting platforms that use machine learning to distinguish between genuine quality issues and normal data variations. Our systems reduce alert fatigue by 95% while ensuring critical data incidents are detected and escalated immediately.

SageMaker Migration & Optimization

Compliance automation and audit trail generation systems

We create automated compliance frameworks that ensure data quality meets GDPR, HIPAA, and industry regulatory requirements. Our systems generate comprehensive audit trails, automated compliance reporting, and real-time policy violation detection for regulated environments.

Patient data integration

Self-healing data quality and automated remediation workflows

We build proactive data quality systems that automatically detect, diagnose, and resolve common quality issues without human intervention. Our platforms include automated data cleansing, schema adaptation, and quality restoration workflows for continuous system health.

Human-AI collaboration by design

Data observability APIs and integration frameworks

We develop comprehensive API layers and integration frameworks that connect data observability with existing enterprise tools and workflows. Our systems integrate with CI/CD pipelines, data catalogs, and business intelligence platforms for seamless quality management.

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Implementing human-in-the-loop data quality gates for enterprise AI pipelines

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Tech stack for enterprise data observability & quality

Trusted by AI & data-driven companies

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  • adstream logo
  • Blizzard logo
  • Voodoo logo
  • ironSource logo
  • openX logo
  • telephonica logo
  • kochava logo
  • viewster logo
  • Moloco logo
  • Sizmek logo
  • Venatus logo
  • DataSeat logo
  • Return logo
  • Lifesight logo
  • aki technologies logo
  • Inmar logo
  • Verve group logo
  • Smartly logo
  • Toshiba logo
  • entravision
  • Triffecta
  • ARTIFACT
  • ViVV

Why Xenoss is trusted to build enterprise-grade data observability & quality platforms

We solve the complex monitoring challenges that prevent enterprises from achieving reliable, trustworthy data at scale.

Eliminated the millions of annual cost of poor data quality with AI-powered anomaly detection

Engineered intelligent observability platforms for Fortune 500 companies that detect unknown data anomalies, schema drift, and quality degradation using machine learning algorithms. Our AI-powered systems identify silent failures that traditional rule-based monitoring misses, preventing massive financial losses from corrupted data.

Built enterprise-scale observability platforms handling petabyte data volumes

Developed comprehensive monitoring systems that provide unified visibility across multi-cloud, hybrid, and edge environments. Our platforms handle petabyte-scale data monitoring with sub-second anomaly detection, real-time lineage tracking, and automated incident response for mission-critical operations.

Mastered real-time data lineage tracking and automated root cause analysis

Created sophisticated lineage platforms that automatically map data flows across complex enterprise architectures and provide instant impact analysis when quality issues occur. Our automated root cause analysis eliminates manual investigation overhead and prevents incident escalation.

Eliminated 95% of false positive alerts through context-aware monitoring

Engineered intelligent alerting platforms that use advanced ML algorithms to understand normal data patterns and eliminate alert noise. Our context-aware systems reduce monitoring fatigue while ensuring critical data incidents are detected immediately.

Implemented automated compliance frameworks for regulated industries

Built comprehensive compliance automation platforms with real-time policy violation detection, automated audit trail generation, and regulatory reporting systems. Our frameworks ensure data quality meets strict regulatory requirements while providing complete compliance visibility.

Developed self-healing data quality systems with automated remediation

Created intelligent data quality systems that automatically identify anomalies, perform root cause analysis, and execute remediation workflows. Our self-healing platforms include automated data cleansing, schema adaptation, and quality restoration maintaining 24/7 system health.

Engineered unified observability APIs integrating with enterprise tool ecosystems

Built extensive API layers and integration platforms that seamlessly connect data observability with CI/CD pipelines, data catalogs, business intelligence tools, and enterprise workflows. Our integration frameworks enable complete observability adoption without disrupting operations.

Delivered production observability systems processing millions of events per second

Deployed observability systems handling real-time monitoring of millions of data events with consistent performance and reliability. Our platforms maintain sub-second anomaly detection and alerting while processing complex quality validations across distributed enterprise architectures.

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Build intelligent data observability platforms with automated quality management

Continuous monitoring and automated incident response

Featured projects

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Alex Belyansky

Director of Engineering, INMAR

It was a great pleasure working with the Xenoss team. The project was complex and challenging - a rich media editor supporting animation, timeline editing, special effects, undo/redo functionality, and other unique features not commonly found. The project was time-boxed for 3 months. It was a ground-up development incorporating niche technologies that required extensive research and prototyping. Not only did the team deliver a fully working MVP on time, but they also exceeded the requirements in several key instances. The architecture was thoroughly designed, and the UX was executed according to the specifications. I'm very grateful for this experience and highly recommend Xenoss.

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Ben Dzamba

VP of Product, Powerlinks

Before turning to Xenoss, we had a demand-side platform that was costly and not scalable. Having access to a wealth of experience on the Xenoss team related to our domain of real-time bidding, we’ve cut costs and now have a much more efficient, reliable DSP for our customers. I’d gladly recommend Xenoss as a technology partner. I’ve found the team to be very professional and diligent, ensuring that our needs and expectations are met through every step of the development process.

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Brandon Keenan

CMO, ViVV LABS

We loaded a huge client into the ViVV Labs Platform today—with the incredible support of the Xenoss team. We’ve done this a number of times already, and it’s worked flawlessly every time, but this one was different. It was a key client for our business. If you want to experience what it’s like to pull your walled garden data effortlessly and apply data science to your spend to potentially save 30–40%, partner with Xenoss.

David Philippson

David Philippson

CEO & Co-Founder, Dataseat

We were looking for an experienced vendor to develop a performance-based media buying solution from scratch. One of the main reasons why we chose Xenoss was their extensive domain knowledge. It allowed us to save time and effort at the initial stages and dive right in product development. The team’s been very professional and responsive to our needs and was able to deliver the MVP under just several months. Later on, they’ve transformed it into a fully featured platform for in-game advertising, which already proved highly scalable and able to manage high load. I’ve been truly happy with their work, high quality standards, and communication.

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Edward Lyon

Head of Product, Smartly

Our business has grown since we started working with Xenoss by an enormous amount and much of that has to do with the software that they’re developing. The most impressive aspect of our collaboration is that the Xenoss team keeps on solving challenges we put in front of them and these are challenges that anecdotally, other businesses have tried solving but are not successful.

Matt Cannon about Xenoss

Matt Cannon

COO, Venatus

We've been a client of Xenoss for a year now and find them an excellent technology partner. Highly skilled and knowledgeable with the ability to rapidly adapt to our needs. We intend to double the size of our current team with them in 2021.

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Oli Marlow Thomas

Founder and CIO Smartly.io

At some point in our business journey, we had a frustrating experience with our product, from barely managing its instability to fixing errors on the fly. Xenoss team helped us build a well-balanced tech organization and deliver the MVP within a very short timeline. It let us timely onboard huge clients such as Adidas, Tesco, Uber, and keep up our growth pace. I’m glad we’ve been working with such a highly-productive team. I particularly appreciate their ability to hire extremely fast and to generate great product ideas and improvements.