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New Relic Acquires SignifAI

New Relic has acquired SignifAI, an event intelligence company specializing in artificial intelligence (AI) and machine learning (ML).

New Relic intends to bring SignifAI’s technology to market, offering modern software teams advanced technology to predict and address performance issues, so they can deliver exceptional customer experiences.

SignifAI’s open data platform integrates with modern DevOps solutions to provide richer insight to software teams so they can detect issues early, reduce alert noise, and deliver highly available and reliable software at scale. The terms of the deal were not disclosed.

“To deliver reliable software at scale, DevOps teams need to leverage machine learning to help them predict and detect issues early and reduce alert fatigue,” said Lew Cirne, CEO and founder. “What’s really exciting about SignifAI’s open platform is that it sits above a customer’s existing set of monitoring tools. With more than 60 integrations ranging from open source and commercial monitoring tools to popular services found in many DevOps toolchains, SignifAI automates correlation and enriches incident context so that software teams can get answers quickly during incidents and ultimately reduce mean time to resolution. This technology aligns with our current platform offering and we believe it provides us a unique advantage to solve an important problem for our customers.”

As modern systems become increasingly complex, the incident response process has become more complex, too. With microservice architectures, containers, and serverless technologies, companies face issues of cascading failures and alert noise. SignifAI delivers AI and ML-powered correlations for Software Engineering teams, so they receive:

- Faster mean time to resolution (MTTR) with automatic correlation, aggregation and prioritization of alerts to help teams focus on what matters most.

- Automated predictive insights and recommended solutions to resolve issues faster.

- Efficient root cause analysis, with automatically enriched issues containing all the relevant logs, events and metrics that teams need, regardless of the timeframe.

“We started SignifAI to help DevOps teams see and make sense of their operational data, from alerts to change events, regardless of source,” said Guy Fighel, who served as CTO and co-founder of SignifAI. “The team at New Relic shares our vision for bringing machine intelligence capabilities to businesses building and operating modern software and we are thrilled to join forces to accelerate and execute on our joint vision for customers.”

Founded in 2016, SignifAI was started by a team of technologists who wanted to solve for the alert noise and fatigue that they faced in previous technical roles. With deep background and expertise in site reliability engineering (SRE), the team has been dedicated to using intelligence to drive operations excellence. The SignifAI team will continue to work from offices in Sunnyvale, California and Tel Aviv, Israel.

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New Relic Acquires SignifAI

New Relic has acquired SignifAI, an event intelligence company specializing in artificial intelligence (AI) and machine learning (ML).

New Relic intends to bring SignifAI’s technology to market, offering modern software teams advanced technology to predict and address performance issues, so they can deliver exceptional customer experiences.

SignifAI’s open data platform integrates with modern DevOps solutions to provide richer insight to software teams so they can detect issues early, reduce alert noise, and deliver highly available and reliable software at scale. The terms of the deal were not disclosed.

“To deliver reliable software at scale, DevOps teams need to leverage machine learning to help them predict and detect issues early and reduce alert fatigue,” said Lew Cirne, CEO and founder. “What’s really exciting about SignifAI’s open platform is that it sits above a customer’s existing set of monitoring tools. With more than 60 integrations ranging from open source and commercial monitoring tools to popular services found in many DevOps toolchains, SignifAI automates correlation and enriches incident context so that software teams can get answers quickly during incidents and ultimately reduce mean time to resolution. This technology aligns with our current platform offering and we believe it provides us a unique advantage to solve an important problem for our customers.”

As modern systems become increasingly complex, the incident response process has become more complex, too. With microservice architectures, containers, and serverless technologies, companies face issues of cascading failures and alert noise. SignifAI delivers AI and ML-powered correlations for Software Engineering teams, so they receive:

- Faster mean time to resolution (MTTR) with automatic correlation, aggregation and prioritization of alerts to help teams focus on what matters most.

- Automated predictive insights and recommended solutions to resolve issues faster.

- Efficient root cause analysis, with automatically enriched issues containing all the relevant logs, events and metrics that teams need, regardless of the timeframe.

“We started SignifAI to help DevOps teams see and make sense of their operational data, from alerts to change events, regardless of source,” said Guy Fighel, who served as CTO and co-founder of SignifAI. “The team at New Relic shares our vision for bringing machine intelligence capabilities to businesses building and operating modern software and we are thrilled to join forces to accelerate and execute on our joint vision for customers.”

Founded in 2016, SignifAI was started by a team of technologists who wanted to solve for the alert noise and fatigue that they faced in previous technical roles. With deep background and expertise in site reliability engineering (SRE), the team has been dedicated to using intelligence to drive operations excellence. The SignifAI team will continue to work from offices in Sunnyvale, California and Tel Aviv, Israel.

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

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
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In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

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) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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