The mantra of the modern tech industry was arguably invented by Facebook (before it was Meta): "move fast and break things."
But as enterprise infrastructure has become a dizzying maze of hybrid clouds, microservices, and ephemeral computing clusters "breakage" part of it has become a structural tax that many organizations can no longer afford. A two-year-old startup today NeuBird AI begins a large-scale attack against it "chaos tax," Falcon announced a $19.3 million funding round alongside the launch of its autonomous manufacturing operations agent.
The launch is not just a product update; is a philosophical loop. The industry has been in the spotlight for years "Incident response"— make fire engines faster and hoses bigger. NeuBird AI claims to be the only sustainable way forward "Incident prevention".
As Venkat Ramakrishnan, president and CEO of NeuBird AI, said in a recent interview: "Event management is very old school. Event resolution is very old school. Incident prevention is what will be enabled by AI".
By basing AI in a real-time enterprise context rather than just a broad language model, the company aims to advance site reliability engineering and move teams from a reactive to a predictive position.
The artificial intelligence divide: a reality check in automation
Accompanying the launch is NeuBird AI’s State of Manufacturing Reliability and AI Adoption Report for 2026, a survey of more than 1,000 professionals that shows there is a great disconnect between the boardroom and the server room.
While 74% of C-suite executives believe their organizations are actively using AI to manage incidents, only 39% of practitioners—engineers actually making calls at 2:00 a.m.—agree.
That’s 35 points "Divide AI" As management writes reviews for AI platforms, it suggests that the technology often fails to reach the front lines.
The reality for engineers remains manual and tedious: research shows that engineering teams spend an average of 40% of their time managing incidents rather than building new products.
NeuBird AI co-founder Gou Rao told VentureBeat that this is an ongoing operational reality: “Over the last 18 months we’ve been in production, this is not a marketing ploy. We’ve been able to concretely demonstrate a massive reduction in time to respond and resolve incidents.”
The consequences of this "hard work" it’s more than just losing productivity. Alert fatigue has shifted from a moral issue to a direct credibility risk.
According to the report, 83% of organizations have teams that occasionally ignore or dismiss alerts, and 44% of companies have experienced outages directly related to a suppressed or ignored alert in the past year. In many cases, systems are so noisy that customers detect failures before monitoring tools.
IIntroducing NeuBird AI Falcon
NeuBird AI’s answer to this systemic failure is the Falcon engine. While the company’s previous iteration, Hawkeye, focused on autonomous resolution, Falcon extends that capability to predictive intelligence. "When we launched NeuBird AI in 2023, the first version of the agent was called Hawkeye." Rao explains. "What we’ll be announcing next week at HumanX is a next-generation version of the agent, codenamed Falcon. Falcon is easily three times faster than Hawkeye and averages around 92% in confidence scores.".
This level of accuracy allows engineers to trust the agent’s output at face value. Falcon represents a significant leap over previous generative AI applications in the space, particularly its ability to predict failure. "Falcon is really good at predictive forecasting, so it can tell you what might go wrong," Rao says. "It’s pretty accurate in a 72-hour window, better in 48 hours, and really, really accurate in 24 hours.”
One of the notable features of the new release is the Advanced Context Map. Unlike static dashboards, this is a real-time view of infrastructure dependencies and service health. This allows teams to visualize them "blast radius" Propagation of a problem to the environment, which helps engineers understand not only what is broken, but also why it is failing in the context of its neighbors.
‘Minority Report’ for incident management
While many AI tools favor sleek web interfaces, NeuBird AI leans toward a developer’s native environment with NeuBird AI Desktop. This allows engineers to launch the production operations agent directly from the command line interface to investigate root causes and system dependencies.
"Falcon has a desktop mode that allows you to interact with a developer’s native tools," Rao noted. "We’re attracting more of a hands-on developer audience, especially as people move to Claude Desktop and Cursor. They complete the loop using production agents that talk to encoding agents.”
This integration a "multi-agent" a workflow where an engineer can use a NeuBird AI agent to diagnose the root cause in production and then hand that diagnosis off to a coding agent like Claude Code to implement a fix.
During the live demo, Rao demonstrated how to build the agent "Sentinel mode," constantly sweeping the cluster for risks. If it detects an anomaly like a projected 5% increase in AWS costs or a misconfigured Kubernetes pod, it can call in a dedicated engineer with domain expertise to fix it.
"It is like “Minority Report for Incident Management”," A financial services executive reportedly spoke to the team after the demo.
Context engineering: the gateway to security
A key concern for enterprises implementing AI is security—ensuring that large language models don’t go away "crazy" or extract sensitive information. NeuBird AI solves this with a special approach "context engineering".
"The way we implement our agent is that the big language models never touch the data directly," Rao explains. "We become the gateway to how to enter the context.” This means that the model is the reasoning engine, but NeuBird AI is the mediator that covers the data.
In addition, the company has implemented strict safeguards on what an agent can actually execute. “We’ve created language that restricts and limits what the agent can do," Rao says. "It won’t work if something abnormal or something we don’t know comes up. We will not do it.”
This architectural choice allows NeuBird AI to remain model-agnostic. If a newer model from Anthropic or Google outperforms the current reasoning engine, NeuBird AI can simply disable it without requiring the customer to change their platform. "Customers don’t want to be locked into a certain way of thinking," Rao claims. "They want to connect to a platform where they can get the value of an agent system.”
change location "the army": change the expensive observation ability
One of the most radical claims made by NeuBird AI is that agent systems can reduce the amount of data businesses need to store in the first place. Currently, teams rely on massive storage platforms with complex query languages.
"People use very sophisticated monitoring tools like Datadog, Dynatrace and Sysdig." Rao says. "It’s the norm today, so it takes an army of people to solve the problem. What we’ve been able to demonstrate with agent systems is that we don’t need to store all that data in the first place”. Because the agent can reason between raw data sources, it can determine which signals are redundant and which are critical. According to Rao, this change “reduces human effort and effort, while also reducing your reliance on these tools like crazy.”
The practical effect of this "event avoidance" was recently featured on Deep Health. Rao recounts how his agents discovered a systemic problem that was not visible to traditional tools: “Our agent was able to go in and prevent a problem that would have caused a major production outage at this company, Deep Health. The client is completely on his own and happy with what he was able to do.”
FalconClaw: operationalizes ‘tribal knowledge’
One of the most persistent problems in IT operations is loss "tribal knowledge"— the hard-won experience of great engineers that exists only in their heads. NeuBird AI is trying to solve this with FalconClaw, an enterprise-grade skill center compatible with the OpenClaw ecosystem.
FalconClaw enables teams to capture best practices and critical steps "approved and relevant skills". The tech preview launched today with 15 initial skills working natively with NeuBird AI’s toolchain.
According to François Martel, field technical director of NeuBird AI, this turns hard-earned experience into a reusable asset that AI can automatically tap into.
This is an attempt to standardize how agents interact with the infrastructure, away from the owners "black box" systems towards a multi-agent world where different AI tools can share common operational skills.
Scaling the moat: funding and leadership
The $19.3 million round was led by Khora Innovation, a Temasek-backed firm with participation from Mayfield, M12, StepStone Group and Prosperity7 Ventures. This brings NeuBird AI’s total funding to approximately $64 million.
Investor interest is mainly driven by the pedigree of the founding team. Gou Rao and Vinod Jayaraman previously co-founded Portworx, which was acquired by Pure Storage, and Ocarina Networks, which was acquired by Dell. They recently strengthened their leadership with Venkat Ramakrishnan, another Pure Storage veteran, as president and COO.
For investors like Phil Inagaki of Chora, the value is in NeuBird AI "best results for accuracy, speed and token consumption". As cloud costs continue to rise, the AI agent’s ability to not only correct errors, but also optimize infrastructure capacity is growing. "should be" more a "it’s nice". NeuBird AI claims its agent can save enterprise teams more than 200 engineering hours per month.
The road to a “self-healing” infrastructure
As noted in the State of Production Reliability report, current incident management practices are: "is no longer sustainable". With 61% of organizations estimating that an hour of downtime costs $50,000 or more, the financial risks of staying in the jet loop are huge.
NeuBird AI’s launch of Falcon and FalconClaw represents a determined attempt to break this cycle. with an emphasis on prevention and "context engineering" Required to make AI viable for enterprise manufacturing, the company is positioning itself as a critical intelligence layer for the modern stack.
while "Divide AI" NeuBird AI remains a significant hurdle for the industry among managers and practitioners, with engineers betting that they see the value of the client-based, 92% accurate agent. "see corners" skepticism will fade. For site reliability engineers currently drowning in a flood of static signals, the arrival of a reliable AI teammate can’t come soon enough.
NeuBird AI Falcon is available starting today, organizations can sign up for a free trial here neubird.ai.
