Who are Riverbed?

When enterprise IT teams talk about their biggest operational headaches, two themes come up consistently: the sheer volume of alerts generated by modern infrastructure, and the time it takes to find the root cause when something goes wrong. Riverbed was built to solve exactly these problems. For over twenty years the company has been helping organisations understand, optimise and manage the performance of their networks and applications. Today it has repositioned itself at the forefront of AIOps and observability, combining decades of data collection expertise with a new generation of AI-powered analysis and automation.

Founded in 2002 and headquartered in Redwood City, California, Riverbed operates in 88 countries and counts 95% of the Fortune 100 among its customer base. With 102% year-on-year growth in observability bookings in Q1 2025, the company is executing a significant platform transformation - and it is one that enterprise IT leaders evaluating their monitoring and observability strategies should be paying close attention to.

Viewpoint Analysis is a Technology Matchmaker. We help businesses to find and select new and exciting enterprise technology - and we help IT vendors to drive awareness and customer understanding. In this blog, we'll get a close look at Riverbed.

Who Are Riverbed?

Riverbed was founded in 2002 by Jerry Kennelly and David Donatelli, originally as a pioneer in WAN optimisation - the technology that made applications run faster over slow or congested wide-area networks. That heritage gave Riverbed something genuinely valuable: twenty-plus years of experience collecting, processing and analysing real IT performance data at enterprise scale, across networks, applications, endpoints and infrastructure.

Dave Donatelli serves as CEO today and has been instrumental in repositioning the company around AIOps and observability. The business is privately held, backed by Vector Capital, and operates across more than 88 countries with thousands of active enterprise customers. Its product portfolio has evolved significantly from its WAN optimisation roots, now encompassing a unified observability and AIOps platform alongside a revitalised acceleration business that has seen renewed relevance in the AI era.

In 2025 and into 2026, Riverbed has been on an active innovation sprint. The company reported 102% year-on-year growth in observability bookings in Q1 2025 and 92% year-on-year growth across the first half of 2025 as a whole. GigaOm named Riverbed an Outperformer in its 2025 Radar for AIOps Solutions for the second consecutive year, recognising it in the Innovation/Platform Play quadrant - a recognition of both the pace of product development and the breadth of the platform vision.

What Do Riverbed Do?

Riverbed operates across two closely related areas: observability and acceleration. The observability business is now the primary growth driver and the focus of the company's AI investment. The acceleration business - rooted in Riverbed's original WAN optimisation heritage - has seen a significant revival as enterprises grapple with moving large volumes of data efficiently for AI workloads.

The Riverbed Platform is an open, AI-powered observability solution designed to give enterprise IT teams full-stack visibility across networks, applications, endpoints, cloud infrastructure and unified communications. Rather than requiring multiple separate monitoring tools - one for the network, one for applications, one for endpoints - Riverbed consolidates these into a single platform through its Riverbed Unified Agent, which collects full-fidelity telemetry across the entire IT estate in real time.

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The AI engine at the centre of the platform combines four distinct AI capabilities: Causal AI, which identifies the root cause of issues by correlating patterns across the full data set; Predictive AI, which uses real-time and historical telemetry to forecast problems before they affect users; Generative AI through Riverbed IQ Assist, which delivers instant context-rich insights and remediation recommendations in plain language; and Agentic AI, which automates remediation workflows without requiring manual intervention. Customers are executing over 64 million AI-driven remediations annually through the platform.

The acceleration portfolio, built around the iconic SteelHead product line, has been refreshed with the launch of the SteelHead 90 series and a new Data Express Service - a SaaS offering specifically designed to accelerate AI data movement between enterprise locations. At a time when AI initiatives are creating significant data transfer bottlenecks, Riverbed's ability to reduce data transfer volumes by up to 90% and cut cloud egress costs by 50-75% has made this a commercially relevant capability again.

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What Markets Do Riverbed Serve?

Riverbed's primary market is large enterprise. The company counts 95% of the Fortune 100 as customers and operates across more than 88 countries, with particularly strong penetration in sectors where network performance and application reliability are business-critical: financial services, healthcare, government, manufacturing, energy and utilities, and professional services.

Within these sectors, Riverbed typically serves IT operations teams, network operations centres, and IT service management functions. The buying team for a Riverbed deployment usually includes CIOs, IT Directors, Network Operations leads, and increasingly Chief Digital Officers and Chief AI Officers as the observability and AI acceleration use cases grow in strategic importance. It is not a departmental tool - it is infrastructure that underpins the performance of everything a modern enterprise IT team is responsible for delivering.

Geographically, Riverbed has strong coverage across North America and Europe, with growing presence across Asia Pacific and the Middle East. The UK public sector, including the NHS, represents a notable concentration of customers, reflecting the platform's suitability for large, complex, distributed IT environments with demanding performance and compliance requirements.

What Makes Riverbed Different?

The most important differentiator is data fidelity. Riverbed collects full-fidelity, real telemetry data - not sampled or synthetic data - across every layer of the IT stack. This matters because AI models are only as good as the data they are trained on. Many observability vendors rely on sampled data or agent-based collection with significant gaps. Riverbed's twenty-plus years of investment in data collection, starting with WAN optimisation, means it captures a richer and more complete picture of IT performance than newer entrants can replicate quickly.

The combination of four AI types in a single platform is also genuinely distinctive. Most observability vendors offer one or two AI capabilities - anomaly detection, or generative AI summarisation. Riverbed's integration of Causal, Predictive, Generative and Agentic AI within a single platform means IT teams can move from detection to diagnosis to automated resolution within the same workflow, without switching between tools or contexts.

The platform's open architecture and commitment to OpenTelemetry standards is a practical differentiator for enterprise buyers. Riverbed integrates with third-party tools and data sources - including ITSM platforms such as ServiceNow - and ingests data from non-Riverbed sources into its Riverbed Data Store for unified analysis. This matters for organisations that are not starting from a blank slate and need an observability platform that works with their existing investments rather than replacing them.

Finally, the revival of the acceleration business creates a unique two-sided value proposition. Organisations using Riverbed for observability can also use the same vendor to solve AI data movement challenges - reducing the number of vendor relationships required to manage the demands of a modern, AI-driven IT environment.

Who Are Riverbed's Competitors?

The observability and AIOps market is competitive and fast-moving. Riverbed's primary competitors include Dynatrace, Datadog, New Relic, Splunk (now part of Cisco), SolarWinds and Nexthink, each of which offers varying combinations of infrastructure monitoring, application performance management, digital experience monitoring and AIOps capabilities.

Dynatrace is probably the most direct comparable at the enterprise end - an AI-powered full-stack observability platform with strong automation capabilities and deep cloud-native support. Datadog has grown rapidly on the back of cloud-native adoption and broad integration coverage, and is a common choice for organisations with developer-led IT operations. SolarWinds has a strong base in network monitoring, particularly in mid-market and hybrid infrastructure environments. Nexthink focuses specifically on digital employee experience, making it a more specialist competitor for the endpoint and DEX use cases that overlap with Riverbed's Aternity capability.

Where Riverbed is most differentiated is in the combination of network-level observability, endpoint digital experience management, AI-powered root cause analysis, and acceleration - a combination that no single competitor currently matches. The depth of network visibility in particular, rooted in Riverbed's original WAN expertise, is difficult for newer, cloud-native focused vendors to replicate in complex hybrid and on-premises environments.

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Who Are Riverbed's Customers?

Riverbed's customer base spans enterprise organisations across virtually every major industry vertical. The following examples are drawn from Riverbed's own published customer materials.

Intel, one of the world's largest semiconductor companies, uses Riverbed Aternity to monitor the digital experience of its global workforce. The scale and diversity of Intel's employee base makes a single consolidated view of device and application performance essential. Riverbed's ability to bring data from different devices and sources into one platform enables Intel's IT team to identify anomalies and resolve performance issues before they affect productivity across a demanding and highly technical workforce.

Tate and Lyle, the FTSE 250 global supplier of food and beverage ingredients, deployed Riverbed Aternity in 2021 to improve its employee digital experience and gain visibility into software licence usage. The platform gave the company a proactive capability to identify and resolve user issues before they escalated, while also enabling it to audit unused licences and reduce software spend - a combination of operational and commercial value that reflects the breadth of what observability data can deliver.

The Princess Alexandra Hospital NHS Trust, a UK healthcare provider, deployed Riverbed's AIOps platform to improve IT service desk efficiency and clinician productivity. Using Riverbed IQ Assist, the trust was able to resolve issues faster and automate IT remediations, freeing up IT resource to focus on delivering better clinical outcomes.

Kent Community Health NHS Foundation Trust deployed Riverbed Aternity for digital employee experience management, rolling out 6,200 licences across its workforce. The trust reported near-immediate value, with performance trends visible within hours of deployment, enabling its IT team to proactively troubleshoot issues affecting clinical staff.

Dow, the global materials science company, uses Riverbed to cut through over 2,000 alerts daily, prioritising business-critical incident remediations and achieving a 7x improvement in mean time to resolution. The use case demonstrates Riverbed's value in large-scale, complex manufacturing and industrial IT environments where alert volumes would otherwise overwhelm IT operations teams.

How to Select AIOps and Observability Software

Selecting an observability or AIOps platform is one of the most consequential decisions an enterprise IT team can make. The right platform gives every part of the IT function - from the network operations centre to the service desk to the CIO - a shared, accurate and actionable view of IT performance. The wrong one creates another silo, more noise, and more cost.

Start by being clear about the primary problem you are trying to solve. Observability platforms vary significantly in their focus: some are strongest on network performance, others on application monitoring, others on digital employee experience, and others on cloud-native infrastructure. Understanding where your most acute pain sits will significantly shape which vendors deserve the closest attention.

Key evaluation criteria should include the breadth and depth of data collection across your specific environment (cloud, on-premises, hybrid, endpoint); the maturity and accuracy of AI-driven root cause analysis; the quality of automation and remediation capabilities; integration with your existing ITSM and workflow tools; the platform's approach to data security and compliance; total cost of ownership including licensing, implementation and ongoing management; and the vendor's track record in organisations of your size and sector.

AI capability in particular deserves careful scrutiny. Many vendors use the term AIOps loosely. Ask specifically: what type of AI is used, what data does it run on, how does it handle environments it has not seen before, and what evidence exists of it delivering measurable outcomes for customers similar to yours? The difference between AI that detects anomalies and AI that identifies root cause and automates remediation is significant - and it is worth understanding exactly where each vendor sits on that spectrum.

The Enterprise Software Selection Playbook 2026 from Viewpoint Analysis provides a structured framework for running a rigorous selection process from requirements definition through to final vendor decision - applicable to observability and AIOps platform evaluations.

You can also take a look at the 20 tips for selecting IT Operations Technology in our 'How to Select IT Operations Technology' guide.

Our Viewpoint: Is Riverbed Right for You?

Riverbed is a genuinely compelling option for large enterprise IT teams that need serious, full-stack observability with AI that goes beyond surface-level anomaly detection. The combination of exceptional data fidelity, four integrated AI types, and the operational heritage of twenty-plus years in network performance management gives it a depth of capability that is hard to replicate. The 102% observability bookings growth in Q1 2025 and two consecutive years as a GigaOm AIOps Outperformer are credible external validations of a platform that is executing well.

Riverbed is particularly well-suited to organisations with complex hybrid or on-premises IT environments, large distributed workforces, or a specific need for network-level observability that cloud-native focused vendors struggle to deliver. For organisations already using Riverbed for WAN optimisation or acceleration, the observability platform represents a natural and commercially efficient expansion of an existing relationship.

The honest consideration for prospective buyers is that the breadth of the platform - spanning network, application, endpoint, cloud and now AI data acceleration - means there is more to evaluate and potentially more to implement than with a narrower point solution. Buyers should be realistic about their implementation capacity and prioritise the use cases that will deliver the fastest and most demonstrable ROI. Starting focused and expanding is a sensible approach with a platform of this scope.

Next Steps: How Viewpoint Analysis Can Help

If this profile has prompted further interest in Riverbed or in the broader observability and AIOps market, here are the most relevant next steps.

💡💡 If you are considering Riverbed and want to take a quick look at the market, our Technology Matchmaker Service is a super-quick, low-cost approach to finding your shortlist. If you know Dragons' Den or Shark Tank - well, this is the IT equivalent. We bring a range of vendors to pitch their ideas to you and your team - you just sit back and listen to how they can help.

Or you may also like to:

Explore the AI and Transformation Technology Market

Our AI Technology Selection page covers the landscape of AI-powered enterprise technology, including observability, AIOps, and digital transformation platforms. A good starting point for mapping your options.

Build a Free Vendor Longlist with the Longlist Builder

Tell us your requirements and we generate an independent list of the key observability and AIOps vendors to consider alongside Riverbed. Free, unbiased and ready in minutes.

Read the Enterprise Software Selection Playbook 2026

A structured framework for running a rigorous technology selection process from requirements gathering through to final vendor decision. Useful when you need a process you can take to your IT leadership or procurement team.