Webinar: Building Enterprise AI with Cloudaeon's RAG, MCP and Agentic Frameworks
In our recent webinar, “Building Enterprise AI”, Cloudaeon experts explained what it really takes to productionise AI, from overcoming delivery roadblocks to operationalising AI through accelerators and frameworks that de-risk every stage.
The session brought together Raj Kumar (Chief Architect), Amol (Co-Founder & CTO), and Ashutosh (Lead AI Engineer) to share insights, strategies and a live demo of Cloudaeon’s accelerator, a unified platform integrating RAG, MCP and Agentic AI to help enterprises scale AI safely and efficiently.
With over 143 live attendees and a highly active Q&A throughout, audience engagement hit new highs, making it one of our most dynamic webinars yet.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged.
The Hard Truth: Why So Many AI Pilots Fail
Raj opened the discussion by highlighting a common reality,
“According to Gartner, 80% of enterprise AI pilots never reach production. The problem isn ’t the model, it’s how they’re engineered, governed and scaled.”- Raj Kumar
He explained that most enterprises approach AI as a traditional software project, missing the nuances of adaptive models, dynamic data and continuous governance.
Top challenges he outlined:
Rigid development practices that can’t keep up with model evolution.
Hidden R&D costs that distort ROI and delay scale.
Governance gaps in data, IP ownership and accountability.
“We built our AI delivery model to solve exactly these issues, so pilots don’t fade, they flourish,” Raj noted.
Cloudaeon’s Core Principles for Enterprise AI Delivery
Taking over from Raj, Amol shifted focus to execution on how Cloudaeon helps enterprises move beyond pilots through structure, accountability and measurable outcomes.
“Technology is evolving fast, but what’s really stopping enterprises isn’t the code. It’s the fear of re-strategising every six months as AI evolves.”- Amol
The core principles that drive Cloudaeon’s delivery framework:
De-risk AI delivery, Cloudaeon takes ownership of delivery risk by using proven accelerators and reusable IP to deliver results in weeks, not months. This structured, outcome-first approach helps clients validate use cases quickly, reduce uncertainty, and build confidence in AI adoption without large upfront investments.
Beyond de-risking, Cloudaeon’s model focuses on client-led strategy, rapid pilot to production, business aligned innovation, AI ops and continuous improvement and reusable IP with shared acceleration.
Each engagement is co-built with the client’s business goals at the centre, ensuring governance and ongoing optimisation from day one.
The Cloudaeon Delivery Model: Start. Scale. Sustain.
Amol expanded on Cloudaeon’s “Start, Scale, Sustain” delivery model, explaining how the team translates principles into tangible action. Drawing from years of hands-on AI implementation and countless POVs, Cloudaeon can deliver validated AI outcomes within 4–6 weeks, helping clients make clear go or no-go decisions.
Each engagement builds reusable assets, ensuring even early efforts contribute long-term value. Moving from pilot to production, Amol highlighted, demands more than quick prototypes it requires robust infrastructure, security guardrails, model governance, and continuous learning mechanisms.
His personal emphasis, however, was on the “Sustain” phase, embedding AIOps to monitor performance, user feedback and cost efficiency. “Start and scale are crucial,” he noted, “but without sustain, AI maturity stalls. That’s where managed services, proactive monitoring and continuous optimisation truly make enterprise AI future ready.
Cloudaeon’s model includes:
Start – Validate quickly with pre-built accelerators and focused use cases.
Scale – Operationalise with enterprise-grade infrastructure, security and governance.
Sustain – Embed AIOps for continuous performance and cost optimisation.
“Sustainability isn’t an afterthought, it’s designed from day one.” - Raj Kumar
Demo Highlight: Cloudaeon’s AI Hub
To bring these principles to life, Ashutosh showcased the Cloudaeon RAG Accelerator.
“We wanted to give enterprises a foundation to build intelligent, context-aware systems where multiple AI agents can collaborate, access external tools and continuously learn from their data.”- Ashutosh
Key demo takeaways:
A unified workspace for LLMs, vector databases and data sources.
Automated scheduling, logging and version control.
A real-world demo: turning a bakery operations manual into an AI chatbot that instantly retrieves context-specific procedures, cutting manual search time drastically.
3 Pillars of Cloudaeon’s AI hub
Amol highlighted three core principles that shaped the Cloudaeon AI Hub:
Freedom of choice, Integrate any LLM, vector database, or cloud platform that fits your use case.
IP ownership, Clients retain full control with no vendor lock-in.
Reusability, Built-in accelerators and shared assets make every AI project faster and smarter.
“Freedom, ownership, and reusability, that’s what makes enterprise AI truly yours,” Amol said.
Key Takeaways for Enterprises
AI success is about delivery, not just data science.
Governance and speed can coexist when supported by structured frameworks.
Client-led strategies ensure accountability and control.
Sustainability must be built in from the start.
“We don’t just build AI applications, we help you build a sustainable AI ecosystem.”- Amol
Next Steps: Bring Your AI Vision into Reality
Cloudaeon empowers enterprises to scale AI responsibly with speed and sustainability.
Ready to move your AI pilot into production?
Submit your use case or experience Cloudaeon’s AI Hub in your environment with our experts to see how Cloudaeon’s accelerators and frameworks can help you de-risk your AI journey.
