As software systems become more distributed and AI accelerates the pace of development, engineering teams face a growing challenge: keeping applications reliable without letting monitoring costs and operational complexity spiral out of control. Traditional observability tools provide visibility into what is happening across infrastructure, but identifying the cause of an incident and resolving it can still require significant manual effort.
A new generation of founders is working to change that equation. From AI agents that investigate production incidents to platforms that make telemetry more affordable and actionable, these five leaders are building tools designed to help engineering teams understand their systems, respond to problems, and maintain reliability at scale.
Spiros Xanthos — Founder and CEO of Resolve AI
Spiros Xanthos has spent much of his career building technologies that help engineering teams understand and operate complex software systems. Before founding Resolve AI with Mayank Agarwal, he helped build Omnition, which was acquired by Splunk, and worked on the development of OpenTelemetry, an open-source standard for collecting and exchanging telemetry data. He later led Splunk’s observability business, bringing extensive experience in production systems to his next venture.
Resolve AI applies AI agents to the operational work that begins after software is deployed. Its platform can investigate alerts, correlate information across code, infrastructure, and observability tools, and help resolve production incidents. The goal is to reduce the time engineers spend diagnosing failures and handling repetitive operational tasks. As AI coding tools accelerate software development, Xanthos is focused on the next challenge: helping organizations operate the growing volume and complexity of software they ship.
Nishant Modak — Founder and CEO of Last9
Nishant Modak is a software entrepreneur focused on helping engineering teams build and operate reliable systems. As a three-time founder with 18 years of experience in software products for development and engineering teams, he has seen how difficult it can become to monitor infrastructure as applications grow. He co-founded Last9 to make observability more accessible at scale, with an emphasis on connecting operational data to the decisions engineers need to make when systems behave unexpectedly.
Last9 unifies telemetry, including logs, metrics, and traces, to give engineering teams a more complete picture of application behavior. The company has also expanded into AI-native operations through an agent SDK that allows teams to build operational agents capable of supporting detection, investigation, and remediation. By connecting high-cardinality telemetry with AI-driven workflows, Modak is helping move observability beyond dashboards and alerts toward systems that can provide useful context and assist with troubleshooting.
Kiran Gollu — Co-founder and CEO of Oodle AI
Kiran Gollu brings experience from some of the technology industry’s most demanding infrastructure environments. Before co-founding Oodle AI with Vijay Karthik, he worked on foundational services at Amazon, including S3 and DynamoDB, and led cloud platform engineering at Rubrik. He also previously founded Neptune.io, a Y Combinator-backed observability startup. His background has shaped his focus on helping engineering teams manage increasingly complex systems without allowing infrastructure overhead to become a major obstacle to growth.
Oodle AI is building a serverless, fully managed observability platform designed to reduce the cost and operational burden of monitoring modern applications. It brings together capabilities for collecting and analyzing telemetry while using a cloud-native architecture to make large volumes of data more economical to store and investigate. The platform also emphasizes AI-assisted debugging, giving engineers ways to investigate incidents without maintaining extensive monitoring infrastructure themselves. Gollu’s approach reflects a broader effort to make reliable operations more accessible to companies that need scale without enterprise-level complexity.
Jad Naous — Founder and CEO of Grepr
Jad Naous founded Grepr after years of experience in the observability industry, including work with organizations associated with AppDynamics, New Relic, and Imply. As AI accelerates software development, he has identified a growing imbalance: engineering teams can produce more code and deploy changes faster, but the volume of telemetry required to monitor those systems can grow alongside them. That creates pressure on both infrastructure reliability and budgets, particularly for organizations that must decide which logs and metrics to retain.
Grepr focuses on reducing observability costs while helping engineering teams preserve the data needed to investigate production problems. Its platform uses intelligent telemetry processing to reduce unnecessary data volume, with the company reporting an average telemetry reduction of 90%. This approach aims to give organizations greater control over the cost of monitoring without forcing engineers to discard information that could become important during an incident. Naous is addressing a fundamental infrastructure challenge: making comprehensive visibility more sustainable as software systems become increasingly complex.
Prabhat Sharma — Founder and CEO of OpenObserve
Prabhat Sharma founded OpenObserve in 2022 after recognizing the cost and complexity facing teams that need to monitor distributed applications. Traditional observability environments can involve multiple products for logs, metrics, and traces, creating fragmented workflows and expensive storage requirements. Sharma set out to make observability more accessible through a cloud-native, open-source platform that combines these data types in one environment. His focus is on giving organizations a practical way to gain visibility into their systems without taking on unnecessary operational and financial overhead.
OpenObserve has since expanded its capabilities beyond traditional telemetry analysis. Its platform includes AI-oriented features such as an autonomous AI site reliability engineering (SRE) capability, anomaly detection, and monitoring for large language model applications. In April 2026, the company announced a $10 million Series A led by Nexus Venture Partners and Dell Technologies Capital alongside the launch of its Observability 3.0 capabilities. Sharma’s vision is to combine accessible infrastructure monitoring with AI-driven analysis, helping engineering teams move more quickly from detecting unusual behavior to understanding and addressing its cause.
Making Software Operations More Efficient
As development cycles accelerate, reliability has become an increasingly important part of the software engineering equation. Teams need to identify problems quickly, understand the relationships between services, and control the costs associated with collecting and analyzing operational data. These challenges are pushing observability beyond its traditional role as a monitoring function.
The companies led by these founders reflect several approaches to that shift, from autonomous incident investigation to more economical telemetry management and AI-assisted troubleshooting. Their long-term opportunity lies in helping organizations operate increasingly complex systems with greater speed, clarity, and confidence. As AI-generated code becomes more common, the infrastructure supporting reliable software operations is likely to become an even more consequential part of the technology stack.
