Agentic AI Moves Into the Enterprise Core as Airrived Emerges from Stealth
Enterprise technology has spent the past decade chasing automation, yet most organisations still rely on human glue to stitch together cybersecurity tools, IT workflows and operational platforms. That contradiction sits at the heart of a growing shift in enterprise technology. Rather than adding artificial intelligence as a feature, the industry is beginning to treat AI as infrastructure.
The emergence of Airrived, backed by $6.1 million in seed funding, lands squarely in that moment. The company positions itself as an operating layer for agentic intelligence across enterprise cybersecurity, IT and business operations. The investment round was led by Cannage Capital with participation from Plug and Play Ventures, Rebellion Ventures and Inner Loop Capital, alongside strategic investments from Manoj Apte, Mahendra Ramsinghani and Saqib E. Awan.
While funding announcements are common, the underlying narrative is more significant. Enterprise AI is moving away from pilot projects and dashboards toward systems that can reason, decide and act across complex environments. For industries such as construction, infrastructure and transport, where cyber resilience and operational continuity are increasingly mission critical, this shift has real-world implications.
Why Enterprise AI Is Entering a New Phase
Across sectors, organisations are drowning in tools. Cybersecurity alone often involves dozens of platforms covering threat detection, identity management, compliance, vulnerability scanning and incident response. According to research from Gartner and IDC, large enterprises frequently run more than 50 security and IT tools simultaneously, creating fragmented workflows and data silos.
This fragmentation comes at a cost. Security teams face alert fatigue, IT departments struggle with integration complexity, and business leaders lack real-time decision visibility. AI has been promoted as the solution, yet in many cases it has delivered only incremental improvements. Copilots summarise data, dashboards visualise trends, and automation scripts execute narrow workflows. The gap between AI promise and enterprise reality has remained stubbornly wide.
Airrived’s launch reflects a broader industry realisation. Enterprises no longer need more point tools. They need a unified intelligence layer capable of orchestrating decisions across existing systems.
The Rise of Agentic AI in Enterprise Operations
Agentic AI has become one of the most talked-about concepts in enterprise technology. Unlike traditional automation, which follows predefined rules, agentic systems are designed to reason through problems, adapt to changing conditions and take action autonomously within defined guardrails.
This shift aligns with broader market trends. Analysts have increasingly highlighted the move toward autonomous enterprise systems, where AI handles complex workflows that previously required human intervention. In cybersecurity, for example, the volume of threats continues to grow faster than the workforce capable of responding. In IT operations, the complexity of cloud, hybrid and edge environments has made manual management increasingly unsustainable.
Against this backdrop, Airrived’s approach centres on positioning agentic AI as an operating system rather than an add-on capability. The company calls this layer the Agentic OS.
Introducing a New Operating Layer for Intelligence
The Agentic OS is presented as a platform designed to unify enterprise domains such as security operations centres, governance risk and compliance, identity and access management, vulnerability management, IT operations and broader business workflows.
Rather than offering isolated AI features, the platform aims to enable organisations to fine tune large language models, build reasoning agents and orchestrate decision making across multiple tools without requiring specialist AI expertise. This approach reflects a growing demand for accessible AI deployment models that move beyond specialist data science teams.
By consolidating fragmented tools into a single system, the platform seeks to allow enterprises to standardise their approach to automation and intelligence. That positioning resonates with organisations that have spent years layering new technologies onto already complex IT stacks.
Investor Confidence Signals a Broader Market Shift
The investors behind the seed funding round emphasised the importance of the platform’s architecture and real-world applicability. Shelley Jhuang, Founder and Managing Partner at Cannage Capital, highlighted the broader ambition behind the technology: “Airrived stood out because of its agentic-first architecture. This isn’t automation or scripted playbooks—it’s a composable agentic platform designed to scale across use cases. We are honored to back the mission-driven Airrived founders as they enable enterprises to build intelligent automation across security and IT.”
The emphasis on composability and scale reflects a key challenge in enterprise AI adoption. Many organisations struggle to move from pilot projects to full production deployment. Platforms that address governance, reliability and operational integration are increasingly attracting investor attention.
Amit Patel, Partner at Plug and Play Ventures, pointed to the operational realities facing security teams: “What I like about Airrived is that it’s built for the day-to-day reality of security teams—fewer handoffs, fewer errors, and faster execution. That’s how you reduce operational overhead while improving outcomes.”
This focus on workflow efficiency rather than experimental AI capabilities highlights a maturing market. Investors are increasingly prioritising solutions that deliver measurable operational impact.
From Pilot Projects to Production Systems
One of the most persistent challenges in enterprise AI adoption has been the transition from experimentation to production. Many organisations have invested heavily in AI pilots but struggled to scale them across critical operations. Governance, integration complexity and skills shortages have slowed adoption.
Airrived positions its platform as purpose built for production environments. By consolidating multiple agentic tools into a single system, the company aims to reduce reliance on scarce AI specialists and enable broader enterprise adoption.
The CEO and co founder, Anurag Gurtu, framed the company’s vision in terms of foundational change: “Enterprises don’t need more tools or surface-level AI. They need a new foundation. Airrived represents arrival—the moment agentic intelligence becomes native to the enterprise. This funding validates our belief that agentic AI isn’t the future of security and IT; it’s the era we’re defining now.”
The language reflects a wider industry narrative. As generative AI matures, attention is shifting toward operational AI capable of delivering measurable outcomes.
Early Enterprise Adoption Signals Market Readiness
The company reports deployments across several large enterprises, including a Fortune 150 insurance firm, a global bank, a major telecom infrastructure company and a large restaurant chain. While details remain limited, the range of industries suggests the platform is designed for environments with high regulatory and operational complexity.
These sectors share common characteristics. They operate at scale, manage sensitive data and rely on continuous system availability. The ability to deploy agentic systems in such environments suggests growing confidence in AI governance and reliability.
For infrastructure and construction sectors, this trend carries increasing relevance. Digital transformation, connected equipment and smart infrastructure initiatives are expanding the attack surface for cyber threats. At the same time, project timelines and operational efficiency leave little room for disruption.
Implications for Infrastructure and Construction
The construction and infrastructure industries have historically lagged behind sectors such as finance and telecommunications in cybersecurity investment. That gap is narrowing rapidly. Connected machinery, digital twins, remote monitoring and cloud-based project management tools are becoming standard across major projects.
As infrastructure becomes more digitised, cyber resilience is becoming as critical as physical safety. A cyber incident affecting project management systems, supply chains or connected equipment can disrupt construction schedules and increase project risk.
Agentic AI platforms designed to orchestrate security and IT workflows could play an increasingly important role in these environments. Automated incident response, continuous compliance monitoring and integrated vulnerability management are becoming essential capabilities for organisations managing complex infrastructure projects.
Recognition and Industry Momentum
Airrived has already received several industry recognitions, including being named a Gartner Tech Innovator in Agentic AI, receiving a Security Today CyberSecured Award and being recognised as a BIG Innovator in Agentic AI.
Awards alone do not guarantee long term success, yet they reflect growing industry interest in platforms that move beyond experimental AI. Recognition from analyst organisations and industry bodies often signals that a technology aligns with broader market trends.
The company’s positioning around an operating system for intelligence mirrors earlier shifts in enterprise technology. Cloud computing, containerisation and platform engineering all followed similar trajectories, moving from niche innovation to foundational infrastructure.
The Bigger Picture for Enterprise Technology
The emergence of platforms such as Airrived reflects a broader evolution in enterprise technology. AI is gradually shifting from being a feature embedded in individual tools to becoming a foundational layer across entire organisations.
This transition mirrors the early days of cloud computing, when organisations moved from isolated servers to shared infrastructure. Today, enterprises appear to be moving from isolated AI tools to shared intelligence platforms.
For global infrastructure and construction stakeholders, this trend is more than a technology story. It is a shift that could reshape how projects are secured, managed and delivered in an increasingly digital world.
As agentic AI continues to mature, the organisations that treat intelligence as infrastructure rather than an experiment may find themselves better positioned to manage risk, improve efficiency and navigate the complexities of modern operations.
