NeuBird.ai

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

Up to 30% of your IT budget goes to observability. And roughly 90% of the data you're storing is junk. Our Co-Founder and CEO Gou Rao breaks down why the old model is broken and what comes next: agents that connect directly to live telemetry streams and resolve issues in real time, without hoarding data. We launched Falcon and Sentinel mode to make that a reality today. 🎥 Watch the full video here: youtu.be/AKB79C26yIM?si…

A Prometheus memory alert fires in PagerDuty. Normally that means jumping between kubectl, Grafana, GitHub, and log tails. Using NeuBird, what would take an engineer a couple of hours to piece together, gets done in just under 5 minutes. Watch this demo by Grant Griffiths to see how easy it is to get remediation steps in just minutes: youtu.be/tY0_S2dSrbo?si…

Today marks a new chapter for NeuBird AI as we expand beyond incident response to massively improve how enterprise teams run entire production environments. As our newly released 2026 State of Production Reliability and AI Adoption research shows, the timing couldn’t be better for enterprises. This independent survey of 1,000+ SRE, DevOps and IT operations professionals confirms what we've heard for years from engineers who tell us the gap between what teams are dealing with and what their tools can handle has become a reliability risk. Powered by NeuBird AI Falcon, our production ops agent ships with four new capabilities that solve this: - Preventive insights that surface risks before they fire alerts - Advanced Context Map for real-time visibility into infrastructure dependencies and health - NeuBird Desktop, which invokes the agent directly from CLI for instant root cause analysis - FalconClaw that offers an enterprise-grade production operations skills hub (OpenClaw-compatible) With this release, teams are moving from reactive firefighting to a model of continuous prevention, rapid resolution, and autonomous optimization. In the process, they’re realizing a 78% reduction in alert noise and over 200 engineering hours saved per month. We’ve also scored $19.3M in new funding to help drive this shift and fuel our continuous innovation. We’re incredibly grateful to Xora Innovation for believing in our mission and joining us on this journey as well as to our existing investors, Mayfield, StepStone Group, Prosperity7 Ventures and M12, Microsoft's Venture Fund, who continue to support us and our vision. Catch a first glimpse of the NeuBird AI autonomous production operations agent in the short video below and then explore the announcements and survey report here: Autonomous Production Operations Agent Release: tinyurl.com/3dp93sj2 Funding announcement: tinyurl.com/33nmkxuf 2026 State of Production Reliability and AI Adoption Report: tinyurl.com/bd2jpws8

The NeuBird flock is heading to HumanX! Watch below to hear from Alicia, Andrew, and our engineering team about what’s coming and why we’re excited to be there 👀

We’re excited to announce that NeuBird AI will be attending HumanX SF, and our team will be there in full force! Whether you want to see NeuBird AI in action at Booth 202, catch our lightning talk, or try to beat our engineers at arcade games in the Retro Lounge, we’ve got you covered. Plus, stop by for the best swag and giveaways 🎉 We're also hosting an exclusive executive reception. Seating is limited! Check out our full agenda now 👉 tinyurl.com/2p4c8m7p

Telemetry dashboards are obsolete. It assumes that humans will still be the reasoning engine to correlate pretty graphs to find the root cause. Yet, many tools still leverage this core business model of indexing and visualizing countless 'what if' data points in their vendor-locked platform. True speed and scale in the AI-era requires providing actionability: automatic detection, triage, diagnosis, and response. This comes from precisely and efficiently reading only the relevant information from your infrastructure, exactly when it is needed. You can't provide that kind of a revolutionary product when your bottom line is maintained by hoarding data. tinyurl.com/y729pstx

In this short clip we show how NeuBird AI works with your Azure tenant to automatically respond to alerts and deliver root cause analysis. With read-only access, NeuBird AI ingests signals from four data sources, collapses noisy alerts into a single investigation, and runs adaptive chain-of-thought analysis across your environment. In less than three minutes you’ll see how it delivers a clear timeline, supporting evidence, and remediation guidance. Check out the short video below and see it live in your Azure environment with a free trial here: tinyurl.com/2s48adex

The real cost of downtime goes far beyond dollars. It's 65% of engineers burned out, prolonged investigations, and tool sprawl that extends MTTR. Here's a closer look at downtime's cascading effects and how agentic AI breaks the cycle.

What impact does agentic AI have on incident management? Join NeuBird AI’s Grant Griffiths in this DZone webinar on March 18 as he outlines how an agentic AI approach to incident response can autonomously reason across logs, metrics, traces, and change events to surface root causes faster and with greater control. Through live examples, you’ll learn how agentic systems improve visibility across complex, distributed services, enable governance through human-in-the-loop autonomy, and reduce cost and MTTR by eliminating manual investigation work. Learn more and join us by registering here: tinyurl.com/57kfy99a

Yes, you can build a "Demo AI SRE" in weeks that will explain your logs, summarize dashboards, suggest plausible root causes. But when a true production incident hits with inconsistent schemas from 15 different tools, partial traces, and 1TB of logs from hundreds of services, the difference between a demo and a production-grade system becomes painfully obvious. In this detailed post, NeuBird AI Technical Marketing Engineer, Andrew Lee, details a structured framework to help teams evaluate AI SRE tools beyond the demo. It outlines the criteria you should use if you’re running a POC or comparing vendors, including: - The six engineering challenges that determine production readiness - The questions you should be asking vendors - The key accuracy and efficiency metrics to evaluate - The baseline measurements to establish during your POC Andrew also provides a breakdown of what a true production-grade AI SRE agent requires architecturally. See the full technical framework here: tinyurl.com/bdh55m2c

Today's teams are running more workloads across increasingly complex stacks with headcount that hasn't kept pace. We’ve added more tools, which has led to more alerts, but not more engineers. At the same time, teams are expected to innovate faster, support app modernization and AI initiatives, reduce firefighting, and still maintain reliability across hybrid and multi-cloud environments. Looking at this complete picture, you can see why yesterday’s incident management approaches are breaking. For years, the industry has tackled the problem in pieces with alert triage, root cause analysis, and workflow automation. Each helps in isolation, but incident response still remains largely manual, time-consuming, and tedious. As NeuBird’s new President and COO, Venkat Ramakrishnan explains, modern infrastructure demands a different approach. In today’s distributed environments, effective incident management requires all three capabilities working together as a single, integrated system: - Automated alert triage and noise reduction - Automated, evidence-backed root cause analysis - End-to-end incident workflow automation In the post, Venkat breaks down the current landscape, how NeuBird brings this trifecta together, and why he describes NeuBird’s approach to agentic incident resolution as a “ChatGPT moment” for infrastructure and reliability engineering. tinyurl.com/chatGPTmoment #AgenticAI #AISRE #SiteReliabilityEngineering #IncidentManagement