Prime Highlights
- Cloud202 launched Qubitz AI, an agentic AI platform designed to reduce business app development costs by up to 80%.
- The platform helps organisations move AI projects from concept to deployment faster and more efficiently.
Key Facts
- Qubitz AI was developed by former AWS specialists Lucky Sharma and Naman Gupta.
- It creates full-stack applications with built-in testing, governance, compliance, and security features.
Background
Cloud202 has launched Qubitz AI, an agentic AI platform designed to build production ready business applications, claiming it can cut development costs by as much as 80 per cent.
Former Amazon Web Services specialists Lucky Sharma and Naman Gupta created the platform for organisations that have experimented with artificial intelligence but struggled to turn early ideas into deployable systems backed by proper governance and compliance controls.
Qubitz AI starts by identifying a business problem, then generates requirements documents, multi agent architectures, workflows and deployment models. The platform generates a full-stack app with integrated testing and governance features.
Sharma said the idea grew out of watching clients pour money into AI consultancy and proof of concept work that rarely reached deployment. During earlier roles at Accenture and AWS, he said, he saw businesses spend between £350,000 and £500,000 on consultancy before a single application went live.
Halved.io, a learning support system for students, offers an early example of the platform in action. Founder Andy James had previously hired another developer, but the result fell short of the company’s needs. Using Qubitz AI, Cloud202 redeveloped the platform in just four weeks at roughly one-fifth of the cost of the previous solution.
Naman Gupta, Founder and Chief Executive Officer of Cloud202, said Halved.io needed to move fast to begin school trials before the summer break. Using Qubitz AI, he said, the team accelerated development, built in responsible AI safeguards and reached GDPR compliance in a fraction of the usual time and cost.
Sharma said much of the AI market remained stuck at the prototype stage, with organisations building demos and consuming tokens without reaching production. He said governance, observability and compliance needed to sit at the core of any agentic system rather than be added on afterward.