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Numerify Releases Change Risk Prediction Solution

Numerify announced the release of its Change Risk Prediction solution, aimed at helping organizations reduce their IT Change Management costs and risks while increasing change velocity, and therefore agility.

The new solution is part of Numerify's broader IT Business Analytics portfolio that spans the Infrastructure and Operations (I&O), Application Development / DevOps, and IT leadership and strategy functions.

"As IT landscapes become more complex, large organizations are challenged to balance more frequent changes in production with the risk of service disruptions. Our new solution helps them manage change risk by blending data across their entire landscape and applying Artificial Intelligence (AI) to deliver actionable insights," said Srikant Gokulnatha, Co-Founder and Chief Product Officer at Numerify. "Based on our work through scores of deployments across Fortune 500 leaders, we have now packaged our best practices to deliver these insights even faster," said Gokulnatha.

The solution integrates data from a range of IT sources including development, build, test, deployment, IT Service Management, and Application Performance Management systems to create a unified view of all change-related problems and incidents. Numerify's Machine Learning (ML) models then process this data to predict both failure rates for specific changes and uncover systemic causes of change failure, including signals from both upstream code development and downstream performance monitoring applications. The Numerify Change Risk Prediction solution also provides a complementary descriptive analytics view, enabling IT executives to use an analytical lens to rapidly come up with a strategy to eliminate these systemic causes of change failure.

Organizations that have adopted Numerify's Change Risk Prediction solution, experience the following benefits:

- Increased overall efficiency: By reducing Mean-Time-to-Resolution (MTTR) of change-related incidents, and reducing rework and recovery costs, IT organizations can decrease the total costs of their Change Management function.

- Accelerated agility: By reducing change lead times and increasing change frequency, IT organizations can not only deliver a better customer experience but also expedite their journey to Agile and DevOps adoption.

- Reduced risk: By accurately predicting the causes of change risk as well as systemic causes of change failure, IT organizations can mitigate risk while focusing their attention on the riskiest changes.

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Numerify Releases Change Risk Prediction Solution

Numerify announced the release of its Change Risk Prediction solution, aimed at helping organizations reduce their IT Change Management costs and risks while increasing change velocity, and therefore agility.

The new solution is part of Numerify's broader IT Business Analytics portfolio that spans the Infrastructure and Operations (I&O), Application Development / DevOps, and IT leadership and strategy functions.

"As IT landscapes become more complex, large organizations are challenged to balance more frequent changes in production with the risk of service disruptions. Our new solution helps them manage change risk by blending data across their entire landscape and applying Artificial Intelligence (AI) to deliver actionable insights," said Srikant Gokulnatha, Co-Founder and Chief Product Officer at Numerify. "Based on our work through scores of deployments across Fortune 500 leaders, we have now packaged our best practices to deliver these insights even faster," said Gokulnatha.

The solution integrates data from a range of IT sources including development, build, test, deployment, IT Service Management, and Application Performance Management systems to create a unified view of all change-related problems and incidents. Numerify's Machine Learning (ML) models then process this data to predict both failure rates for specific changes and uncover systemic causes of change failure, including signals from both upstream code development and downstream performance monitoring applications. The Numerify Change Risk Prediction solution also provides a complementary descriptive analytics view, enabling IT executives to use an analytical lens to rapidly come up with a strategy to eliminate these systemic causes of change failure.

Organizations that have adopted Numerify's Change Risk Prediction solution, experience the following benefits:

- Increased overall efficiency: By reducing Mean-Time-to-Resolution (MTTR) of change-related incidents, and reducing rework and recovery costs, IT organizations can decrease the total costs of their Change Management function.

- Accelerated agility: By reducing change lead times and increasing change frequency, IT organizations can not only deliver a better customer experience but also expedite their journey to Agile and DevOps adoption.

- Reduced risk: By accurately predicting the causes of change risk as well as systemic causes of change failure, IT organizations can mitigate risk while focusing their attention on the riskiest changes.

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IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

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In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

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