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Sauce Labs Releases Sauce AI for Insights

Sauce Labs announced Sauce AI for Insights, a suite of AI-powered data and analytics capabilities that helps engineering teams analyze, understand, and act on real-time test execution and runtime data to deliver quality releases at speed - while offering enterprise-grade rigorous security and compliance controls.

Sauce AI for Insights converts one of the most critical bottlenecks in modern software development into a strategic advantage: the overwhelming volume of test data that slows decision-making and delays releases now accelerates developer productivity and engineering efficiency.

Sauce AI for Insights provides instant, context-aware answers complete with visualizations and direct links to relevant test data as anyone - from executives, developers, or QA-asks their questions in natural language. This not only surfaces data and connections that are hard, if not sometimes impossible, to find manually, it also saves hundreds of expensive engineering hours per month per team.

"We've been running testing infrastructure for 17 years, and here's what we've learned: the problem isn't generating test data-we're drowning in it," said Prince Kohli, CEO at Sauce Labs. "The problem is that interpreting that data has become specialized knowledge. You need to know where to look, how to correlate patterns, and which failures matter. AI changes that equation completely. For the first time, the data can explain itself. That's not a feature-that's a fundamental shift in who can make quality decisions."

Sauce AI for Insights transforms testing data into what engineering teams actually need: Quality Intelligence. Instead of spending hours analyzing logs and dashboards, teams get instant, AI-powered answers about software quality that accelerate releases and reduce defects. It delivers three transformative business outcomes:

  • Boosted Engineering Efficiency: Teams eliminate data overload and manual analysis, reclaiming hundreds of hours previously spent chasing down root causes. With no setup or configuration required, users get instant access to AI-driven insights that cut through the noise and surface what matters most.
  • Accelerated Velocity of Innovation: Real-time issue identification, intelligent failure analysis, and natural language queries enable teams to move from insight to action in seconds rather than hours. Engineering teams can identify critical issues like flaky tests, newly failing builds, and cross-device patterns instantly, accelerating release cycles and time-to-market.
  • Strengthened Risk and Compliance Management: Comprehensive quality metrics, proactive defect prevention, and consistent monitoring across the entire SDLC reduce escaped defects and rework costs while ensuring regulatory compliance and application stability.

"Our beta customers showed us the full impact: their C-suite gained visibility into quality metrics that drive business decisions, while their engineering teams gained deeper diagnostic power to fix issues in minutes instead of hours," said Shubha Govil, Chief Product Officer at Sauce Labs. "What excites me most isn't that we built AI agents for testing-it's that we've democratized quality intelligence across every level of the organization. For the first time, everyone from executives to junior developers can now participate in quality conversations that once required specialized expertise."

Sauce AI for Insights delivers:

  • Real-Time Analytics: Insights will use the latest information available to the user, providing relevant, up-to-the-moment information about builds, devices, and test performance.
  • Conversational AI Interface: Natural language queries make it much easier to ask relevant and intuitive questions, eliminating the need to translate to SQL, custom scripts, or manual dashboard navigation. Users simply ask questions and receive immediate, context-aware responses.
  • Role-Based Insights: The AI agent tailors responses based on who's asking- developers get detailed root cause analysis and direct links to failing test cases while QA managers receive strategic, release-readiness insights.
  • Rich, Visual Outputs: Every response includes dynamically generated charts, data tables, and clickable links to relevant test artifacts, making insights immediately actionable.
  • Transparent and Trustworthy: Every insight includes clear attribution showing exactly how data was gathered and processed, with links to source data for validation.

Organizations using Sauce AI for Insights in beta testing have reported dramatic improvements:

  • 99% faster identification of root causes
  • Debugging time reduced from hours to minutes
  • Hundreds of engineering hours reclaimed per team per month
  • Significant acceleration in release readiness assessments
  • Democratization of quality insights across technical and non-technical team members
  • Improved collaboration between QA, development, and leadership teams

The solution supports diverse use cases across the testing lifecycle, including automated build analysis and failure pattern detection, device coverage optimization, visual testing health assessment, flaky test identification, cross-device failure correlation, and release readiness analysis.

"Everyone talks about AI replacing jobs," added Kohli. "What we're seeing is the opposite: AI is revealing how much time we've been wasting on work that shouldn't exist in the first place. When you watch an engineer spend three hours digging through logs for something that should take three minutes, that's not a job-that's a broken process. We're not replacing people; we're finally giving them the tools to do the job they were actually hired to do."

Sauce AI for Insights is now available as an add-on capability within the Sauce Labs platform for existing customers.

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Sauce Labs Releases Sauce AI for Insights

Sauce Labs announced Sauce AI for Insights, a suite of AI-powered data and analytics capabilities that helps engineering teams analyze, understand, and act on real-time test execution and runtime data to deliver quality releases at speed - while offering enterprise-grade rigorous security and compliance controls.

Sauce AI for Insights converts one of the most critical bottlenecks in modern software development into a strategic advantage: the overwhelming volume of test data that slows decision-making and delays releases now accelerates developer productivity and engineering efficiency.

Sauce AI for Insights provides instant, context-aware answers complete with visualizations and direct links to relevant test data as anyone - from executives, developers, or QA-asks their questions in natural language. This not only surfaces data and connections that are hard, if not sometimes impossible, to find manually, it also saves hundreds of expensive engineering hours per month per team.

"We've been running testing infrastructure for 17 years, and here's what we've learned: the problem isn't generating test data-we're drowning in it," said Prince Kohli, CEO at Sauce Labs. "The problem is that interpreting that data has become specialized knowledge. You need to know where to look, how to correlate patterns, and which failures matter. AI changes that equation completely. For the first time, the data can explain itself. That's not a feature-that's a fundamental shift in who can make quality decisions."

Sauce AI for Insights transforms testing data into what engineering teams actually need: Quality Intelligence. Instead of spending hours analyzing logs and dashboards, teams get instant, AI-powered answers about software quality that accelerate releases and reduce defects. It delivers three transformative business outcomes:

  • Boosted Engineering Efficiency: Teams eliminate data overload and manual analysis, reclaiming hundreds of hours previously spent chasing down root causes. With no setup or configuration required, users get instant access to AI-driven insights that cut through the noise and surface what matters most.
  • Accelerated Velocity of Innovation: Real-time issue identification, intelligent failure analysis, and natural language queries enable teams to move from insight to action in seconds rather than hours. Engineering teams can identify critical issues like flaky tests, newly failing builds, and cross-device patterns instantly, accelerating release cycles and time-to-market.
  • Strengthened Risk and Compliance Management: Comprehensive quality metrics, proactive defect prevention, and consistent monitoring across the entire SDLC reduce escaped defects and rework costs while ensuring regulatory compliance and application stability.

"Our beta customers showed us the full impact: their C-suite gained visibility into quality metrics that drive business decisions, while their engineering teams gained deeper diagnostic power to fix issues in minutes instead of hours," said Shubha Govil, Chief Product Officer at Sauce Labs. "What excites me most isn't that we built AI agents for testing-it's that we've democratized quality intelligence across every level of the organization. For the first time, everyone from executives to junior developers can now participate in quality conversations that once required specialized expertise."

Sauce AI for Insights delivers:

  • Real-Time Analytics: Insights will use the latest information available to the user, providing relevant, up-to-the-moment information about builds, devices, and test performance.
  • Conversational AI Interface: Natural language queries make it much easier to ask relevant and intuitive questions, eliminating the need to translate to SQL, custom scripts, or manual dashboard navigation. Users simply ask questions and receive immediate, context-aware responses.
  • Role-Based Insights: The AI agent tailors responses based on who's asking- developers get detailed root cause analysis and direct links to failing test cases while QA managers receive strategic, release-readiness insights.
  • Rich, Visual Outputs: Every response includes dynamically generated charts, data tables, and clickable links to relevant test artifacts, making insights immediately actionable.
  • Transparent and Trustworthy: Every insight includes clear attribution showing exactly how data was gathered and processed, with links to source data for validation.

Organizations using Sauce AI for Insights in beta testing have reported dramatic improvements:

  • 99% faster identification of root causes
  • Debugging time reduced from hours to minutes
  • Hundreds of engineering hours reclaimed per team per month
  • Significant acceleration in release readiness assessments
  • Democratization of quality insights across technical and non-technical team members
  • Improved collaboration between QA, development, and leadership teams

The solution supports diverse use cases across the testing lifecycle, including automated build analysis and failure pattern detection, device coverage optimization, visual testing health assessment, flaky test identification, cross-device failure correlation, and release readiness analysis.

"Everyone talks about AI replacing jobs," added Kohli. "What we're seeing is the opposite: AI is revealing how much time we've been wasting on work that shouldn't exist in the first place. When you watch an engineer spend three hours digging through logs for something that should take three minutes, that's not a job-that's a broken process. We're not replacing people; we're finally giving them the tools to do the job they were actually hired to do."

Sauce AI for Insights is now available as an add-on capability within the Sauce Labs platform for existing customers.

The Latest

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...