VMblog recently sat down with Payman Samadi, the CEO and Founder of Eino, to discuss their latest press release detailing the launch of their Agentic Network Observability Platform. Here is what they had to share about their new AI-native approach to enterprise networks.
VMblog: Before we get started, can you give VMblog readers a quick background on Eino and what it provides to the enterprise?
Payman Samadi: Eino is an innovator in AI-native network planning, design, and monitoring for enterprise networks. We provide the industry’s first vendor-neutral design and monitoring platform built specifically for the age of robotics, sensors, and autonomous systems. What’s interesting is that, as a leadership team, we don’t have a traditional telecom/networking pedigree. What we do have is a unique foundation in physics and AI. Our team’s heritage ranges from mmWave astrophysics in Antarctica to applied AI in Photonics, and that’s really reflected in the approach to AI networking that we’ve built.
We’re also very proud of the market momentum that this approach has produced. Since launching our wireless network design solution in August 2024, Eino has rapidly scaled to support over 40 major customers, including Global Systems Integrators and OEMs such as NTT DATA, Celona, and Boingo. What’s more, our solution has been utilized in more than 5,000 network designs and deployed in over 1,500 production networks.
VMblog: What is Eino announcing today?
Samadi: Today, Eino is announcing the follow-on to our AI native design platform, which is what we’re calling our Agentic Network Observability Platform. We believe this is a new class of solution that leverages Agentic AI and 3D digital twin technologies to quickly design and monitor any type of wireless network in real time.
The platform combines our innovative design solution with purpose-built monitoring and reasoning agents that work around the clock to detect problems, diagnose root causes, and recommend remedies. Some of the key features in this release include:
- Real-Time Monitoring of Multiple Wireless Technologies: A single-pane-of-glass view across private cellular, Wi-Fi, and DAS.
- Agentic AI Automation: Moving beyond threshold-based alerting to correlate physical space, predictive performance and real-time data to identify root causes, and provide actionable recommendations.
- 3D Digital Twin Visibility: Overlaying real-time user experience data onto a 3D digital twin of the physical environment to match performance against design intent.
VMblog: AIOps and AI-powered networks are experiencing a moment of deep interest right now. Why is this so popular with enterprises?
Samadi: Based on the feedback from our customers, this shift is largely driven by the explosive growth of physical AI in the enterprise. Connectivity is quickly becoming a limiting factor for these deployments. As enterprises implement AI throughout their infrastructure, they are unleashing a flood of new endpoints – drones, forklifts, autonomous mobile robots, cameras, tablets, and more.
The core issue is that most IT teams are trying to support these new network demand profiles using legacy tech stacks and approaches. Everything connected to the network has changed, but the way networks are planned, validated, and monitored has largely stayed the same. AI-powered networks and agentic platforms like ours solve these operational constraints, ensuring wireless connectivity can serve as the reliable nervous system for mission-critical operations.
VMblog: What do you see as the primary use cases for this solution?
Samadi: The primary use cases center around enterprises with multiple network technologies and mission-critical environments. Our solution is designed for managing Private 5G, Wi-Fi, IoT, FWA, or a combination of these in a single deployment.
Specific use cases include:
- Complex Industrial Environments: Deploying and managing networks in airports, refineries, maritime ports, and high-tech manufacturing facilities.
- Remote Troubleshooting and Optimization: Allowing network engineers to identify gaps, correlate events, and remotely solve problems before users notice—drastically reducing the need for expensive truck rolls.
- Deployment Validation: Using our 3D Digital Twin technology to validate that deployed coverage matches the original design intent instantly.
Ultimately, it enables enterprises and service providers to design, observe, and troubleshoot AI-native networks 90% faster than existing solutions.
VMblog: How does this news fit into Eino’s broader vision for wireless networks in the enterprise?
Samadi: This announcement is a major step in our vision to be the “shortest path” to Intelligent Connectivity to power the rapid expansion of enterprise networks. It is built on the three foundations of 1) unified platform across network lifecycle and technology, 2) 3D modeling of the environment, 3) Fully agentic workflows. While we established our leadership in wireless network design, adding Agentic Network Observability closes the gap between design and reality. As enterprises transition from legacy workflows to agentic network operations, Eino aims to serve as the intelligence running the “wireless nervous system.” We ensure a high-fidelity data pipeline that enables the real-time automation demanded by modern CIOs, keeping workloads running exactly where and when they are needed.
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About Payman Samadi, Founder and CEO, Eino
Payman Samadi is the CEO and Founder of Eino, a trailblazing company specializing in AI-native network planning, design, and monitoring. With over 15 years of combined industrial and academic experience in telecommunications, Payman is deeply passionate about autonomy, intelligent ecosystems, and making enterprise networking more accessible, reliable, and scalable. Under his leadership, Eino is pioneering the space of Agentic Network Observability.
A highly regarded expert in his field, Payman holds a Ph.D. in Photonics from McGill University, a Master’s degree in Digital Signal Processing from the University of Windsor, and a B.A.Sc. in Electrical and Electronics Engineering from Shahid Beheshti University. Throughout his career, he has co-authored over 50+ peer-reviewed articles across prominent research areas, including data center network architecture, software-defined networking (SDN), and big data analytics. Today, Payman continues to merge his rich foundation in deep engineering with frontier AI models, actively building the resilient “wireless nervous system” required to support the modern era of robotics, sensors, and enterprise AI.
