Riverbed announced the company’s first Agentic AI-powered solution, Riverbed Aternity Self-Service, empowering employees to initiate self-service requests that triage, diagnose, and resolve issues autonomously.
Aternity Self-Service optimizes IT support and dramatically reduces service desk costs, boosting employee and IT productivity by delivering automated remediation, fewer tickets, faster resolutions, and a zero-touch digital support experience.
Riverbed Aternity Self-Service applies Agentic AI to handle end-to-end issue resolution. Once a problem is detected, the AI agent executes triage, runs endpoint and network diagnostics, applies fixes, and validates resolution with human oversight controls as needed. If the issue persists, it automatically generates a fully contextualized ticket for higher-level support, bypassing Level 1 triage entirely. For example, if an employee experiences a crash with a unified communications (UC) application such as MS Teams or Zoom, the Aternity Self-Service agent runs diagnostics, identifies the service issue, restarts affected processes, and confirms the UC tool is back online. Employees return to work in minutes rather than hours, and IT avoids time-consuming manual triage and escalations.
Key benefits of Aternity Self-Service include:
- Autonomous Issue Resolution: Automatically resolves common IT issues, reducing ticket volume and lowering mean time to resolution (MTTR).
- Open Skills Architecture: Leverages modular AI skills with endpoint telemetry and network analytics for deeper insights and precise fixes.
- Smarter Ticket Escalation: Creates actionable, context-rich tickets for unresolved issues, saving time, and minimizing repeated escalations.
- Seamless Ecosystem Integration: Deploys quickly into Microsoft Teams and other enterprise systems, enabling employees to resolve issues where they work.
“Aternity Self-Service delivers on the promise of Agentic AI by taking the employee frustration out of support and turning it into an IT productivity booster,” said Richard Tworek, Chief Technology Officer at Riverbed. “By leveraging Riverbed’s first new Agentic AI solution, employees can resolve common IT issues without waiting for the traditional ticket handling process to complete. The self-service agent runs diagnostics, applies fixes, records the analysis and the work done in a ticket for record-keeping and auditing, and gets the employee back to work in minutes rather than hours. This reduces ticket volume, speeds resolution, and frees IT teams to focus on higher-value projects that drive real business impact. With Riverbed, organizations can deliver a smarter, smoother, and truly seamless digital experience for every employee.”
Riverbed’s approach to Agentic AI ensures governed autonomy, multi-agent collaboration, and human oversight, delivering measurable impact while maintaining trust and control. Companies gain a scalable, future-ready IT environment where employees spend less time waiting for support, while the IT teams can focus on more strategic projects.
Riverbed Aternity Self-Service is in limited availability now.
The Latest
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...