NeuBird.ai

Most root cause analyses don't stop because engineers stop looking. They stop because the answer lives in a layer nobody is watching. In his latest blog, Rael Mussell explains why incomplete visibility leads to incomplete root cause analysis and how full stack context can help teams find answers faster. Read the full blog: neubird.ai/blog/incomplet…

Every generation of infrastructure promises transformation. The question is: Are we changing the technology… or the way we work? 👇

MTTR tells you how fast your team recovers. But it does not tell you whether your customers were protected in the first place. For too long, teams have treated faster recovery as the goal. But the real win is preventing incidents before they reach customers. That means moving from a recovery posture to a prevention posture. Less time in war rooms. Fewer pages. More engineering time back on the roadmap. Read the full blog: lnkd.in/gCN4TaJm

Production has outgrown human understanding. That was one of the key messages from our President & COO, Venkat Ramakrishnan, during his conversation with theCUBE at the New York Stock Exchange. As infrastructure grows more complex and AI accelerates software delivery, operations teams are being asked to manage environments at a scale that simply wasn't possible a few years ago. At NeuBird AI, we're helping organizations move from reactive operations to autonomous operations with AI agents that can detect, diagnose, and resolve production issues in real time. The future of production operations won't be built by adding more dashboards, alerts, or people to the problem. It will be built by autonomous systems that can understand, reason, and act at machine speed. Watch the full interview here: thecube.net/events/nyse/mo…

We are honored to be recognized as a 2026 CODiE Award Finalist. The CODiE Awards are the technology industry's premier peer-reviewed awards program, recognizing innovation and excellence across software, AI, and enterprise technology. This reflects our mission to help enterprises move beyond reactive operations and toward autonomous production operations powered by AI. Onward and upward 🚀

Your coding agent wasn't built for production operations. It was built for your editor. Over-scoped access. Token-burning searches. Scripts you approve without reading. Fine for iterating code. Dangerous for live incidents. The Production Operations Agent is purpose-built for managing the production environment. Learn more about how the Prod Ops Agent can help your team: neubird.ai/platform

Most "AI for incidents" tools just answer questions. But production incidents aren't questions. They're workflows. Who gets paged? Is the ticket updated? Did recovery actually happen — or just look like it? The NeuBird AI Production Ops Agent handles all of it: investigation, coordination, paging, ITSM updates, Slack monitoring, and remediation confirmation. Not a chatbot for your war room. Autonomous production operations. Read more: neubird.ai/blog/it-takes-…

Cost visibility is not the same as cost optimization. Most AWS tools show trends. Few tell you what action to take. We put together a practical guide that shows you where cloud waste actually hides and how leading teams cut costs across EC2, S3, and EKS. Download the guide 👉 neubird.ai/resources/guid…

Claude Fable 5 is Anthropic's most powerful model yet. But production reliability isn't a model problem. It's a context problem. The teams that win won't be the ones using the biggest model. They'll be the ones putting the right context in front of it. Read our latest take: neubird.ai/blog/fable-5/

You can buy an $80,000 car that's already engineered, tested, and calibrated. Or you can buy the engine, transmission, wheels, electronics, frame and bunch of other things to build it yourself. We know from decades of industrial evolution that the latter is not viable, even when spending 5-10x compared to the factory version. DIY AI SRE agents follow the same math. The model is one part. You still need context engineering, data pipelines, domain-specific evals, security controls, feedback loops, and constant tuning. Each piece adds cost. Each integration adds complexity. Each shortcut adds risk. By the time it's actually production-ready, the "cheaper" build is slower to ship and less reliable than what you were trying to avoid paying for. New blog from our founder on why build-vs-buy in AI SRE comes down to cost, speed, and accuracy, and why you can't optimize one without paying for the other two. neubird.ai/blog/cost-of-d…

AI in observability has a context problem. A recent study conducted by The Futurum Group and @TechstrongGroup for NeuBird AI found that while AI adoption is growing, most organizations still lack the operational context needed for AI to drive meaningful action. Key findings: • Teams are overwhelmed by alert noise and fragmented visibility • Root cause analysis is still too slow and manual • Only 12% of respondents said their AI tools have rich cross-system context • Configuration drift and infrastructure issues remain major production risks The future of observability isn’t just more AI. It’s AI with context. Read the full blog here: neubird.ai/blog/pulsemete…

Modern production environments move too fast for manual investigation. By the time engineers correlate logs, metrics, alerts, and recent changes across distributed systems, the impact is already growing. We’re helping change that. Built on @Azure and Foundry, our Production Ops Agent investigates incidents in real time, identifies likely root cause, and guides teams toward resolution faster using agentic AI. Instead of chasing dashboards and stitching together signals manually, engineering teams can focus on keeping systems reliable and building what’s next. Proud to be featured by @Microsoft for Startups as part of the future of AI-powered operations. Read the full story: msft.it/6049vpWDH

We are proud to announce that Daniel Day has joined the company as Chief Marketing Officer! Daniel is a seasoned marketing executive with deep experience building and defining categories in enterprise technology. He joins NeuBird at a pivotal moment: production operations agent emerging as one of the most consequential new categories in enterprise AI, and as NeuBird establishes itself as the company defining it. Daniel's conviction in this market is clear. He sees the structural shift from AI-assisted to AI-autonomous operations as a category creation moment on par with what Salesforce did to CRM or what GitHub Copilot did to software development. His mandate is to ensure NeuBird leads that conversation — with engineering teams, with analysts, and with the enterprise buyers making decisions right now. We're excited to have him leading that charge. Welcome, Daniel. Learn more about Daniel's vision here: neubird.ai/blog/the-categ…

What happens when AI moves beyond monitoring and starts resolving? Our customers are seeing faster incident resolution, less alert fatigue, and more time focused on building instead of firefighting. 🚀 Proud to partner with teams pushing production operations forward.

Looking for tools that automate root cause analysis (RCA)? Not all RCA tools are created equal. Some show you correlation. Some show you causation. Most stop before the fix. We broke down the full landscape: observability platforms, AIOps, and AI-native investigation tools, so you know what you're actually buying. Read more here: neubird.ai/blog/root-caus…

Did you know that you can get cloud spend optimizations from just one-click with NeuBird AI? It only takes a few minutes to get detailed explanations, cited sources, immediate action items, and leadership takeaways regarding cloud costs. That's just one of many things you can do with our Production Ops Agent. Check it out for yourself in our playground: neubird.ai/playground/ Just run "/cost" in the terminal and watch the magic happen.

Shipping faster is easy now. Understanding what breaks is not. In this video, Ranjitha explains where teams get stuck and why production ops is becoming the real bottleneck. Faster code, more complexity, more noise. Without the right context, resolution still takes too long. That is the gap we need to close. Watch the video 👉 youtu.be/9GjqXDdWSzs

Hitting ~92% accuracy in production ops AI isn’t about a smarter model. It’s about giving the model the right context, at the right time. Falcon by @neubird changed one thing: instead of feeding context, it discovers it. That shift made the difference. Read More: neubird.ai/blog/falcon-co…

We’re entering a new era where code is generated faster than ever. But speed in development has created a new bottleneck: operations. As our Co-Founder Vinod Jayaraman shares in this video, the real challenge today isn’t writing code, it’s understanding what happens in production. If you can generate code in seconds but still spend hours diagnosing and resolving incidents, there’s a clear gap. That’s the gap we need to solve. Watch the full video: youtu.be/AenGRsWv3bs

When is the last time a VMware cloud migration actually ended at cutover? Encryption settings that silently change, tags that get dropped, and complex cloud billing models that were never considered. The checklist may be all green, but the post-migration complexity is just beginning to take shape. NeuBird AI just released a new skill to help cover this gap: the Migration Monitor. It actively pairs VMware configurations to the migrated cloud workloads using signals. It compares infrastructure, endpoints, metrics, and database components to identify parities. And it surfaces tiered action plans that you need to take to cover your gaps. Watch the video to get started: youtu.be/Bz-xMjTN_rA