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Selector Closes $33M in Funding

Selector announced Series A round for $28 million, bringing total funding to $33M.

The company was founded in 2019 by former Juniper Networks executives and industry veterans, Kannan Kothandaraman and Nitin Kumar. Selector Analytics provides hyper speed-to-value for operations with usable AIOps and zero-touch analytics across any and all data. This round of funding was led by Two Bear Capital, SineWave Ventures, and Atlantic Bridge. Comcast Ventures and Azure Capital Partners are also investors in the company. The new funds will be used to execute Selector’s go-to-market (GTM) strategy, invest in R&D, and expand its market reach in North America. The platform is already successfully deployed by multiple Fortune 500 customers.

This announcement marks the official launch of Selector Analytics, which normalizes clusters and correlates metrics, logs, configuration, events, and alerts from multi-cloud network, application, and security data sources. The platform delivers actionable insights through an intuitive user experience that enables operations to proactively diagnose and remediate issues. Unique to Selector Analytics is the ability to use popular collaboration tools such as Slack and Microsoft Teams, and get insights in seconds using natural language. Such Google-like simplicity eliminates hours of painstaking data hunting and gathering, enabling teams to improve mean time to repair (MTTR) while increasing efficiency, slashing operational overhead and eliminating downtime.

Two Bear Capital, SineWave Ventures and Atlantic Bridge invested in Selector because of the team’s extensive experience and deep domain expertise in networking, applications, and machine learning. The platform’s ability to ingest all manner of data from any data source and provide actionable observability is critical to teams working on multicloud infrastructures.

“At Selector, we have assembled a world-class team looking to transform the AIOps space. By merging networking, AIOps, and observability into a single platform, Selector is approaching the space uniquely. Our mission is to eliminate downtime and empower operations with tools to be more efficient and productive in their jobs,” said Kannan Kothandaraman, Co-Founder and CEO, Selector. “Our customers are having amazing success with the platform and are expanding to new problems they once thought unsolvable.”

Multicloud services are critical to the next phase of internet growth and the economy as a whole. The ability to rapidly triage complex cloud environments requires instant analysis across multiple domains, which is costly and time-consuming to achieve using manual methods for data aggregation and event correlation. Historically, operations teams have had to cross both organizational and tool boundaries to draw actionable insights using many static dashboards – a reactive, often ineffective approach. By contrast, Selector Analytics empowers operations teams to instantly detect anomalies in an environment of increasing complexity and criticality, and maximize the potential of multicloud.

“Existing monitoring solutions are single-domain, manual, and complex, making rapid event correlation and analysis tedious, frustrating, and often impossible,” said Nitin Kumar, Co-Founder and CTO of Selector. “Selector abstracts all of that complexity and enables automated remediation using elastic data ingestion, declarative transformations, and data-centric machine learning.”

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Selector Closes $33M in Funding

Selector announced Series A round for $28 million, bringing total funding to $33M.

The company was founded in 2019 by former Juniper Networks executives and industry veterans, Kannan Kothandaraman and Nitin Kumar. Selector Analytics provides hyper speed-to-value for operations with usable AIOps and zero-touch analytics across any and all data. This round of funding was led by Two Bear Capital, SineWave Ventures, and Atlantic Bridge. Comcast Ventures and Azure Capital Partners are also investors in the company. The new funds will be used to execute Selector’s go-to-market (GTM) strategy, invest in R&D, and expand its market reach in North America. The platform is already successfully deployed by multiple Fortune 500 customers.

This announcement marks the official launch of Selector Analytics, which normalizes clusters and correlates metrics, logs, configuration, events, and alerts from multi-cloud network, application, and security data sources. The platform delivers actionable insights through an intuitive user experience that enables operations to proactively diagnose and remediate issues. Unique to Selector Analytics is the ability to use popular collaboration tools such as Slack and Microsoft Teams, and get insights in seconds using natural language. Such Google-like simplicity eliminates hours of painstaking data hunting and gathering, enabling teams to improve mean time to repair (MTTR) while increasing efficiency, slashing operational overhead and eliminating downtime.

Two Bear Capital, SineWave Ventures and Atlantic Bridge invested in Selector because of the team’s extensive experience and deep domain expertise in networking, applications, and machine learning. The platform’s ability to ingest all manner of data from any data source and provide actionable observability is critical to teams working on multicloud infrastructures.

“At Selector, we have assembled a world-class team looking to transform the AIOps space. By merging networking, AIOps, and observability into a single platform, Selector is approaching the space uniquely. Our mission is to eliminate downtime and empower operations with tools to be more efficient and productive in their jobs,” said Kannan Kothandaraman, Co-Founder and CEO, Selector. “Our customers are having amazing success with the platform and are expanding to new problems they once thought unsolvable.”

Multicloud services are critical to the next phase of internet growth and the economy as a whole. The ability to rapidly triage complex cloud environments requires instant analysis across multiple domains, which is costly and time-consuming to achieve using manual methods for data aggregation and event correlation. Historically, operations teams have had to cross both organizational and tool boundaries to draw actionable insights using many static dashboards – a reactive, often ineffective approach. By contrast, Selector Analytics empowers operations teams to instantly detect anomalies in an environment of increasing complexity and criticality, and maximize the potential of multicloud.

“Existing monitoring solutions are single-domain, manual, and complex, making rapid event correlation and analysis tedious, frustrating, and often impossible,” said Nitin Kumar, Co-Founder and CTO of Selector. “Selector abstracts all of that complexity and enables automated remediation using elastic data ingestion, declarative transformations, and data-centric machine learning.”

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...