Combine AI-assisted coding with experienced engineering to rapidly build, test, and launch modern web applications without compromising quality, security, or scalability.
From idea validation and product strategy to AI development and launch, Cinovic helps businesses turn promising AI concepts into functional MVPs ready for real-world testing.
We combine product thinking, modern technology, and engineering expertise to build scalable digital products from frontend to backend.
See how we've helped teams turn early AI concepts into working, validated products.
This case study is a real-world example of our work as a Hyva development company, rebuilding a fashion retailer's Magento 2 storefront on Hyva after the legacy Luma theme's heavy JavaScript and CSS payload was slowing down mobile pages and contributing to cart abandonment.
Cinovic rescued a stalled migration of 50 million orders to Magento 2 Open Source. A rebuilt process cut the timeline from about 100 days to 24 hours, then fixed the performance issues that followed.
Discover how restaurant wastage and stock transfer control help track inventory movement, reduce product waste, and improve stock visibility across locations.
From validating your initial concept to launching a functional MVP, we provide the strategy, design, AI, and engineering expertise needed to get your product moving.
Define your AI opportunity, target users, MVP objectives, technology approach, and product roadmap.
Build MVPs powered by generative AI, from content and chat experiences to AI-assisted workflows, grounded in a clear product strategy.
Integrate AI models and automation into your product to solve real workflow problems, not just add AI for its own sake.
Test technical feasibility and model performance quickly before committing to a full MVP build.
Design user experiences that make AI features intuitive, trustworthy, and easy to adopt.
Build a bespoke AI-powered MVP from the ground up, tailored to your specific use case and users.
Define your AI opportunity, target users, MVP objectives, technology approach, and product roadmap.
Build MVPs powered by generative AI, from content and chat experiences to AI-assisted workflows, grounded in a clear product strategy.
Integrate AI models and automation into your product to solve real workflow problems, not just add AI for its own sake.
Test technical feasibility and model performance quickly before committing to a full MVP build.
Design user experiences that make AI features intuitive, trustworthy, and easy to adopt.
Build a bespoke AI-powered MVP from the ground up, tailored to your specific use case and users.
We focus on building the smallest useful product, not simply the smallest product. Our approach helps you test important assumptions while creating a strong foundation for future development.
Test your AI concept with real users before making larger product investments.
Prioritize functionality that directly supports your product validation goals.
Create an architecture that can evolve from MVP to a production-ready product.
Bring strategy, UX, AI engineering, development, and deployment together.
Stay ahead with practical guides on turning AI ideas into validated, scalable products
Turn AI ambition into measurable results. Explore the four pillars of AI consulting, a 6-step engagement roadmap, and a real client case study.
Build software that grows without rebuilds. Explore scalable architecture patterns, a 7-phase roadmap, AI-accelerated delivery, and a real case study.
Discover the benefits of hiring AI/ML consulting for enterprises, from building an effective AI strategy to reducing costs, improving efficiency, and scaling innovation.
Have an AI product idea or an existing prototype? Tell us about your vision, and our experts will help define the right MVP scope, technology approach, and path to launch.
An AI MVP is the smallest version of your AI product that still delivers real value and lets you test your core assumptions with actual users, not a stripped-down demo, but a focused, working product.
Most AI MVPs take 6 to 12 weeks depending on scope, model complexity, and integrations. We'll give you a specific timeline after an initial scoping call.
No. We can help you validate the concept, choose the right AI approach, and build a proof of concept if you're starting from an idea rather than existing technology.
We prioritize functionality that directly tests your core product hypothesis and validates real user demand, leaving nice-to-have features for later iterations.
Yes. We architect MVPs with future growth in mind, so a validated product can be extended into a production-ready platform rather than rebuilt from scratch.