Cloud202 launches Qubitz AI, an agent AI platform for building production-ready business applications, announcing that it can reduce development costs by up to 80%.
Created by former Amazon Web Services specialists Lucky Sharma and Naman Gupta, the platform is aimed at organizations that have tested artificial intelligence ideas but struggled to turn them into deployable systems with governance and compliance controls.
Qubitz AI starts by identifying a business problem and generates requirements documents, multi-agent architectures, workflows, and deployment models. We also produce full-stack applications, as well as test and control layers covering areas such as GDPR compliance, observability, and responsible AI.
The announcement comes as many companies are experimenting with tools that can quickly generate AI applications, but are finding it difficult to move prototypes into production. Cloud202 argues that the gap between experimentation and adoption remains one of the main barriers to widespread adoption in large organizations.
Sharma and Gupta developed the product after seeing clients spending large sums of money on AI consulting and proof-of-concept work but not getting adoption. Mr Sharma said that in his previous roles at Accenture and AWS, he had seen companies spend between £350,000 and £500,000 on consulting to get an application up and running.
One of our early users is Halfed.io, a learning support system for students. The company’s founder, Andy James, had previously asked another supplier to develop an application, but the resulting product did not meet the company’s needs.
Cloud202 rebuilt the Halved.io platform using Qubitz AI, adding responsible AI controls, security measures, and GDPR compliance at approximately 20% of previous costs. The effort took four weeks, compared to an estimated six months for traditional development and compliance processes.
Mr. Gupta described this project as an example of what the platform could be used for.
“Halved.io had to move quickly to launch trials in schools before the summer holidays,” said Naman Gupta, founder and CEO of Cloud202. “Using Qubitz AI, we were able to accelerate development, implement responsible AI safeguards, achieve GDPR compliance, and prepare our platform for deployment in a fraction of the time and cost that these projects typically take.”
production focus
Built-in testbeds check the system’s output against your organization’s own expectations before launch. The goal is to ensure that the application is evaluated against business requirements, not just whether the demonstration runs properly.
Qubitz AI also gives you the option of deploying your application in your own AWS environment or starting in Cloud202’s environment and migrating later. The code is kept in the customer’s private GitHub repository, security checks are performed through the pipeline, and the customer can modify the application through the Qubitz interface.
Another client cited by Cloud202 is music discovery company SphereTrax, which has worked on projects such as Harry Potter and Frozen, as well as artists such as Michael Bublé and Bruno Mars. After using Qubitz AI to evaluate potential AI use cases, the company selected one focused on emotional music and sound effects discovery.
The resulting concept is called “Search With Feeling,” according to Cloud202, and uses an AI tagging engine to analyze thousands of soundtracks and categorize them by emotional signature, genre, and similarity. This project shows how this platform can be used not only to generate software, but also to prioritize which AI ideas to pursue.
Sharma said a large portion of the market is stuck in the prototype stage.
“A large part of the AI market is still focused on experimentation,” Lucky Sharma said. “Many organizations generate prototypes, spend tokens, and build MVPs without ever reaching production. We wanted to create a platform focused on meaningful AI solutions that solve real business problems and can be safely deployed at scale.
“And when the next enterprise customer asks about AI governance, the answer is not, ‘We use ChatGPT.’ Governance, observability, and compliance need to be the operating layer of the agent system, not an afterthought.”
Blueprint library
The platform includes a library of industry blueprints in areas such as recruitment screening, document processing, customer support automation, personalization, and recommendation engines. These templates combine pre-built architectures, deployment patterns, and sector-specific practices to reduce the amount of new development required for each new project.
Cloud202 seeks to position Qubitz AI in an increasingly crowded market of application building tools and differentiate itself through governance, testing, and deployment capabilities. Its founders are betting that if companies can tie projects more closely to specific business problems and maintain control over their data and cloud environments, they will spend less on AI experiments.
A key part of this approach is what Cloud202 calls a bring-your-own-cloud model, which allows organizations to move applications to their own AWS assets while maintaining control over security and compliance requirements.
