Lightrun Secures $70M for AI-Powered Code Debugging Platform

Lightrun grabs $70M using AI to debug code in production | TechCrunch

AI-based coding has exploded in popularity on the promise that it will make developers' jobs faster and easier. But it's also resulted in something else: a vast increase in lines of code, and thus the likelihood of bugs resulting in crashes or other mishaps. Today, an Israeli startup called Lightrun -- which has built an observability platform to identify and debug (remediate) code before those problems arise -- is announcing a Series B of $70 million. The funding underscores the not just the gap in the market for tools like these, but also Lightrun's traction in meeting that demand. New backer Accel is co-leading the round alongside previous investor Insight Partners, with participation from Citi, Glilot Capital, GTM Capital, and Sorenson Capital. Lightrun has now raised $110 million to date, including a Series A led by Insight we covered in 2021. The startup is not disclosing valuation, but there are some strong signs that it's doing well. First, there are its customers. Citi is a strategic backer and is one of an impressive list of big-name clients that also includes ADP, AT&T, ICE/NYSE, Inditex, Microsoft, Priceline, Salesforce, and SAP. Second, there is the product and the company's timing for how it fits into the current market landscape. Back in July 2024, Lightrun announced a new AI-based debugging tool to use within organizations' integrated developer environments (IDEs), appropriately called the Runtime Autonomous AI Debugger. Although the company's platform was already delivering impressive results, this was the product that really spoke to the current predicament many enterprises are facing: AI is leading to a lot more coding and a lot more problems, and Lightrun had built an AI tool to address that. The company said that revenues have grown 4.5X since it was launched, and that is what got investors knocking. Andrei Brasoveanu, the Accel partner who led the investment for the firm, said that he'd had his eye on Lightrun (observing, even) for years before this, and he finally took the plunge after that launch. "Everything came together last year," he said. "They saw acceleration in the enterprise, all because of AI." Timing is something that Ilan Peleg, the CEO who co-founded the company with CTO Leonid Blouvshtein, knows something about. Before turning his attention to further education and eventually building Lightrun, Peleg was a champion middle-distance runner, winning 4 national championships in Israel and ranked in the top 16 of all middle-distance runners across Europe. As Peleg sees it, there are dozens of companies building observability tools in the market today (some of the most prominent include the likes of Datadog and App Dynamics). But none have yet reached "the holy grail" of such work: not only being able to get a big picture of all the code that is being shipped in production, but to understand how it will interact with what is already being used, and how to anticipate where problems might arise. And to do so with minimal interruption and thus minimal cost to the organization. "Code is becoming cheap but bugs are expensive," he said. That problem, meanwhile, has reached "an inflection point," he said. "Developers now can ship more code than ever before," due to all the automation that is being used, thanks to AI. "But it's still a very manual process to fix it when things go wrong." Lightrun's breakthrough has been to build an observability toolset that can monitor code just as it is in the IDE and understand how it will behave alongside code that is actively in production. It is then able to automatically made adjustments to the code as it moves into production to continue operating without interruption and crashes. It does this by way of being able to create AI-based simulations to understand that behaviour, and then to fix the code before issues arise. "This is the part where we are unique," Peled said. There are a lot of options for how Lightrun might develop, given how close observability sits to other activities in organizations. One of those is building tools more specifically for cybersecurity teams, given the obvious security implications that arise out of bugs. Another is potentially building some of its tooling even closer to the point of code creation, to make finding and fixing possible bugs even more efficient. For now, the plan is to remain focused on building out its tools, talent and business specifically in the IDE, Peled said. "Everything that poses risk to resilience, we are mitigating," he said, although he didn't rule out more purpose-specific tooling in the future. As for code assistants, "these might be in our future," he said, "but even focusing and working only on the problem of software remediation once executed is complex and wide." It will be hard to anticipate, he said, what code creation will look like in the future. Today, with between 30% and 60% of all production issues estimated to come from code issues generated by both humans and machines, providing a way to observe and fix everything -- regardless of how it was created -- is what Lightrun is racing to fix.

Lightrun raises $70M to use AI for real-time enterprise software observability and remediation - SiliconANGLE

Lightrun raises $70M to use AI for real-time enterprise software observability and remediation Artificial intelligence-powered software observability startup Lightrun Inc. announced today it raised $70 million in Series B funding led by Accel and Insight Partners to build out its platform that helps developers catch and resolve issues while the software is running. Citi, Glilot Capital, GTM Capital, and Sorenson Capital also participated in the round. This funding brings the total raised by the company to $110 million following an $18 million Series A round led by GTM Capital in July. Founded in 2019, Lightrun provides a developer-centric observability platform that allows developers to add logs, metrics and snapshots directly to running applications without needing to recompile or release new versions. The company also offers an AI-based debugging tool that integrates into developer tools called the Runtime Autonomous AI Debugger. Traditionally, developers must catch most issues and bugs during development before code is deployed. However, as with most things, it's hard to tell how anything is going to work until it's actually in production where the plan comes together. As a result, most of the time developers only fix critical issues after something explodes in development and it's sent back to them after it's been reverted. What if something can be caught while it's happening and before it's a major issue? According to Lightrun, its platform allows developers to continue debugging and fixing software without leaving their editing software even after deploying. This means that if something does break in production, they're already in their favored environment. "In 2024, dramatic shifts in the software delivery life cycle -- from the exponential acceleration of software delivery by AI code assistants to the rising importance of resiliency -- have made the SDLC increasingly vulnerable," Ilan Peleg, chief executive of Lightrun, said. "Lightrun bridges this gap, ensuring that once code hits production, teams can move fast and stay reliable." The platform's AI tool automates the entire debugging journey from the initial ticket by pinpointing the initial issue in production and identifying it for the developer in their development environment. It also offers code suggestions on how it can be fixed. It uses generative AI models based on the company's context, observability, logging and telemetry that the developers can add to their software at runtime. The upshot is that if something does go wrong the AI tool can get the developer into the code, find the problem line, function or section quickly and have a suggestion on hand. This could be the difference between taking hours to pore over logs, then diving into code to find the specific culprit line and then finally developing a fix, testing it and deploying it or minutes to accept and refine a recommendation. "As autonomous software development becomes reality, we see the next frontier in autonomous remediation -- software that can fix itself autonomously," added Peleg. Lightrun continues to show significant growth, the company said. Since 2024, it has onboarded numerous Fortune 500 companies including Citigroup Inc., ADP Inc., AT&T Inc., Microsoft Corp., Salesforce Inc. and SAP SE. The company also doubled the size of its team, scaling to support the increasing demand. With the new funding, the company said it intends to move beyond traditional monitoring into full-scale remediation. The Autonomous Debugger has already proven it can redefine how developers and software reliability engineers and operations teams can handle issues in real-time. Lightrun said it intends to continue to scale the product and advance its capabilities to bring its autonomous capabilities to bear and shift the industry away from post-mortem observability to proactive and autonomous problem resolution.

Lightrun raises $70 million to fix your code before it breaks

Lightrun, an Israeli startup that has developed an AI-powered observability platform to identify and debug code in production, has secured $70 million in Series B funding. The round was co-led by Accel and Insight Partners, with participation from Citi, Glilot Capital, GTM Capital, and Sorenson Capital, bringing the total amount raised to $110 million. The funding underscores the growing demand for tools that can help developers manage the increasing complexity of code and mitigate the risk of bugs and crashes. Lightrun's customers include major companies such as ADP, AT&T, ICE/NYSE, Inditex, Microsoft, Priceline, Salesforce, and SAP, with Citi also participating as a strategic backer. Lightrun's platform uses AI to monitor code in integrated developer environments (IDEs) and simulate its behavior in production, allowing for automatic adjustments to be made to prevent issues. The company's Runtime Autonomous AI Debugger, launched in July 2024, has been a key factor in its growth, with revenues increasing 4.5 times since its launch. According to Ilan Peleg, Lightrun's CEO, the company's toolset is unique in its ability to monitor code in the IDE and understand how it will behave in production, allowing for minimal interruption and cost to the organization. "Code is becoming cheap but bugs are expensive," Peleg said, highlighting the growing need for effective debugging tools. Wallarm launches Agentic AI Protection to defend against prompt attacks With the new funding, Lightrun plans to continue building out its tools and talent, focusing on the IDE and mitigating risks to resilience. While the company has potential opportunities to expand into areas such as cybersecurity and code creation, its current focus remains on software remediation. As Andrei Brasoveanu, the Accel partner who led the investment, noted, "Everything came together last year. They saw acceleration in the enterprise, all because of AI." Lightrun's growth is a testament to the increasing importance of AI-powered debugging tools in the development landscape.