These Ex-Cisco Execs Want to End 2 A.M. IT Emergencies—for Good

Ciroos.AI emerged from stealth mode with $21 million in funding and a promise to fix one of technology's most persistent problems: the dreaded middle-of-the-night emergency call.

The startup's AI-powered "SRE Teammate" cuts incident response time by 90 percent. What used to take hours now takes minutes. What used to wake entire teams at 2 AM might not wake anyone at all.

Energy Impact Partners led the Series A round. The company plans to use the funding to hire engineers and expand sales operations.

Three former Cisco executives founded Ciroos in February. CEO Ronak Desai previously ran Cisco's AppDynamics observability unit. CTO Amit Patel and Chief Product Officer Ananda Rajagopal also came from Cisco's networking and cloud divisions. The trio holds 84 patents across AI, observability, and distributed systems.

The Problem Gets Worse

Modern enterprise systems span dozens of applications, hundreds of tools, and multiple cloud environments. When something breaks, site reliability engineers scramble across dashboards, logs, and monitoring systems to find the root cause.

Desai saw this firsthand at Cisco. Customers complained about managing hundreds of tools without connected insights. Teams spent hours correlating data across network, security, and application domains. Some problems lurked undetected for months.

"On average, it takes about two hours to investigate and figure out where the problem is," Desai said. "At times, we've seen it take days."

The cognitive load overwhelms human operators. War room calls drag on. Engineers dive through dashboard after dashboard. Sleep becomes a luxury.

Multi-Agent Architecture

Ciroos built its solution around multi-agent AI systems. Different agents specialize in network equipment, security tools, cloud services, and applications. They work together to correlate data and identify problems.

The system uses the Model Context Protocol and Agent-to-Agent architectures. It integrates with existing tools from Datadog, Prometheus, Jira, and Slack rather than replacing them.

"Can I have a network agent which has expertise on your Nexus equipment? Can I have an agent with expertise around your security domains? Can I build capability with expertise on your cloud services?" Desai explained. "That's where it becomes important, because you have so many different tools."

The AI starts investigating anomalies before human experts get paged. It uses reasoning models to understand cross-domain interactions and separate real problems from false alarms.

Beyond Chat Interfaces

Ciroos positions itself differently from observability vendors adding AI chat features. Instead of providing natural language interfaces over existing APIs, the company built a reasoning engine that mimics human decision-making.

"Our system doesn't just provide a UI on top of APIs," Desai said. "It correlates live and historical data, connects across systems and can recommend or even execute actions such as restarting services or rolling back deployments."

The platform supports semi-automated responses like triggering Git-based rollbacks. It also offers "autopilot" mode for full automation where customers feel comfortable with autonomous fixes.

Competition With Manual Labor

Desai frames the main competition as manual labor, not existing monitoring tools. The company integrates with the observability ecosystem rather than disrupting it.

"We do not compete with any of the observability tools," he said. "We are competing with manual labor and the toil SREs have. They are looking at hundreds of dashboards and trying to figure everything out and the cognitive load is too much for humans."

The approach wouldn't have worked with earlier AI models. Recent advances in reasoning capabilities made cross-domain correlation possible at enterprise scale.

Timing and Technology

The company's timing aligns with broader enterprise AI adoption. As organizations deploy more AI agents, operational complexity increases. Traditional monitoring approaches struggle to keep pace.

Ciroos leverages whatever new model advances emerge. The platform's extensible architecture adapts to new technologies and integrates with customer-developed agents.

"Out of the box, we built agent-to-agent capability where we can hook into an agent that the customer has deployed or developed on their own," Desai said.

Go-to-Market Strategy

The startup focuses on direct enterprise sales. It experiments with value-based pricing rather than traditional volume-based models common in observability.

Desai emphasizes partner relationships, drawing from his Cisco background. "Coming from Cisco, partners are close to my heart," he said. The company actively recruits channel partners.

Early customers work with Ciroos to build out the platform's multi-domain knowledge. The company invites other early adopters while preparing for broader launch.

Return on Investment

Desai jokes that sleep is the best measure of uptime for SREs. The real ROI comes from eliminating manual work that humans shouldn't handle.

Cutting investigation windows from hours to minutes transforms operations. Teams avoid lengthy war room calls. Engineers spend less time diving through dashboards. Organizations reduce the human cost of maintaining complex systems.

"We're really looking to avoid that manual toil and the tasks which we do not want our human SREs to do," Desai said.

Market Opportunity

The observability market continues growing as enterprises adopt cloud-native architectures. Organizations typically use 50 different monitoring and incident response tools. Each adds complexity without solving the correlation problem.

Ciroos addresses gaps that traditional observability vendors miss. Instead of adding more data sources, it makes sense of existing information. Instead of more dashboards, it provides automated analysis.

The approach recognizes that modern IT operations exceed human cognitive limits. No amount of training or tooling can help a single engineer correlate hundreds of data streams in real time during a critical outage.

What Comes Next

Ciroos builds toward general availability while expanding its agent capabilities. The company focuses on problems that matter to large enterprises rather than trying to solve everything at once.

The founders understand enterprise software cycles. They've seen technologies promise to revolutionize operations only to create new problems. Their approach emphasizes augmenting human teams rather than replacing them.

"The goal is to reduce human toil from SREs so that we can give them the sleep and time back and build a scalable system," Desai said.

The company's success will depend on execution rather than technology alone. Enterprise customers need proof that AI can handle their most critical systems. Trust builds slowly in operations, where mistakes cost millions.

But the problem is real. The technology seems ready. And the team has credentials that open enterprise doors.

Why this matters:

• Modern IT complexity has outpaced human ability to manage it effectively – Ciroos represents a shift from adding more monitoring tools to actually making sense of the data we already collect.
• This signals the maturation of AI from chatbots to mission-critical infrastructure management, where getting it wrong costs millions and getting it right saves careers.