Enterprise AI has no shortage of copilots, chatbots, and dashboards. What it lacks, according to Commotion Inc., is an operating system that actually gets work done.
Backed by Tata Communications, the AI-native startup today introduced a new AI Operating System (AI OS) built in collaboration with NVIDIA. The platform integrates NVIDIA Nemotron™ open reasoning models and the NVIDIA Riva speech AI library to help enterprises move from AI experimentation to autonomous, production-grade execution.
The pitch is straightforward: stop asking AI for suggestions. Start letting it complete tasks.
From Insights to Intelligent Action
Many enterprises today run multiple AI copilots across departments—customer service, IT, HR, sales. But these systems often operate in silos, disconnected from one another and from the broader enterprise context.
The result? Insights without execution.
Commotion’s AI OS aims to solve that fragmentation by acting as a coordination layer. Instead of isolated AI tools, the system unifies enterprise data, orchestrates decisions across platforms, and deploys what it calls “AI workers” capable of executing end-to-end tasks.
Examples include:
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Handling customer service calls autonomously
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Resolving network issues without human intervention
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Improving airline and hospitality guest experiences
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Modernizing global contact centers
Murali Swaminathan, CEO of Commotion, described the core industry problem bluntly: enterprises don’t lack models or data—they lack connectivity and orchestration.
Without shared context and governance, AI remains a collection of experiments. With it, AI can shift from answering questions to executing business processes.
Built on NVIDIA’s Reasoning and Speech Stack
The AI OS integrates NVIDIA Nemotron reasoning models, designed to handle advanced inference and contextual understanding, alongside NVIDIA Riva for real-time speech recognition and synthesis.
That combination matters. Enterprises increasingly require AI systems that can reason across complex workflows and communicate naturally in voice-driven environments such as contact centers.
Vishal Dhupar, Managing Director, Asia South at NVIDIA, positioned the collaboration as enabling AI workers that understand context, make decisions, and execute tasks across industries—from telecom to aviation.
Unlike traditional chatbot deployments, the system emphasizes:
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Unified visibility into AI actions across systems
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Auditability and governance of decisions
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Real-time speech and reasoning
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Scalability across regions and languages
In short, this is less “smart assistant,” more “digital operator.”
Context Engineering as the Differentiator
At the heart of the platform is Commotion’s proprietary context engineering layer. This continuously maps enterprise data, workflows, and activity into a shared model that AI workers use to make decisions responsibly.
This addresses one of the biggest barriers to enterprise AI adoption: trust.
Leaders are hesitant to let AI drive operational decisions without traceability, policy enforcement, and centralized oversight. By embedding governance and visibility into the OS layer, Commotion is attempting to remove that hesitation.
The approach aligns with a growing enterprise demand for “operational AI”—systems that deliver measurable business outcomes rather than isolated productivity gains.
Early Results: ROI, Cost Reduction, Automation
Commotion shared early deployment metrics across industries:
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A global telecom provider autonomously resolves over 40% of operational issues, reducing resolution time by 35%.
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An international airline expects AI to handle 30% of inbound calls within the first year.
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An Indian automotive OEM reports 50% higher ROI, 30% lower cost per call, and 60% fewer calls through elastic scaling during peak hours.
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A global hospitality group is leveraging AI-led guest engagement to drive direct bookings and upselling.
These numbers, while early-stage, reflect a broader enterprise trend: AI budgets are shifting from experimentation to cost optimization and revenue acceleration.
Tata Communications: Infrastructure and Trust
Commotion’s platform is reinforced by a strategic investment from Tata Communications, whose secure global digital fabric infrastructure provides the backbone for enterprise-grade deployment.
A.S. Lakshminarayanan, MD & CEO of Tata Communications, framed the collaboration as solving a universal enterprise challenge: moving AI from demo environments to business-critical operations.
The backing also positions Commotion strongly in India and other high-growth markets, where AI adoption is accelerating alongside digital infrastructure modernization.
Aligning With India’s AI Vision
The announcement dovetails with the Government of India’s broader AI strategy, which emphasizes scalable, multilingual AI systems capable of serving diverse populations and industries.
Commotion, Tata Communications, and NVIDIA are working to ensure the platform operates across languages, locations, and complex infrastructure environments—critical factors in India’s enterprise landscape.
The Bigger Picture: The Rise of AI Operating Systems
The concept of an “AI OS” reflects a new category emerging in enterprise tech. As organizations deploy dozens of AI tools, the need for orchestration, governance, and unified execution grows.
Just as cloud platforms evolved into control planes for distributed infrastructure, AI operating systems may become the control layer for digital labor.
Commotion is positioning itself not as another model provider—but as the connective tissue that enables AI to function as a governed digital workforce.
That distinction could prove critical. Enterprises no longer want AI that merely analyzes. They want AI that acts—reliably, responsibly, and at scale.
If Commotion’s AI OS delivers on that promise, it won’t just reduce pilot fatigue. It could redefine how organizations operationalize AI across telecom, aviation, automotive, hospitality, and beyond.
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