From prototype to launch: AI MVP development for music startup Sineco
When Sineco, a Manchester-based music technology startup, needed to turn a promising AI prototype into a launch-ready product on a controlled budget, it needed a team that could take on AI minimum viable product (MVP) development quickly and without cutting corners.
From AI prototype to production-ready MVP
With scalability validated against the agreed load profile
To support the subscription model
Define
Sineco is a Manchester-based music technology start-up that uses wearable data to personalise training in real time. Its machine-learning model combines musical features such as tempo, rhythm, mood and energy with the listener’s changing physiology. As the user speeds up, finds a rhythm or recovers, the music adapts to match.
The core idea had already been proven through an AI-powered mobile prototype. Moving from prototype to a launch-ready product was a different challenge, and AI MVP development of this kind exposes problems in performance, infrastructure, integration and release engineering.
Sineco needed specialist support to address four priorities within a controlled budget:
- Latency across the loop between wearable and machine-learning model
- Priority security and load defects
- Low-latency biometric scoring and feedback to drive adaptive music playback
- A scalable foundation for more devices and customers.
Design
Definia assembled and managed a team spanning architecture, technical project management and development, and brought it into Sineco’s existing product team. Working alongside Sineco’s fractional CIO and product leadership, the team turned technical findings and agreed priorities into an engineering programme.
Delivery focused on the existing mobile app, back end and AI platform, with the barriers to a usable running and yoga experience tackled first. The team:
- Reviewed the inherited code and addressed priority stability, security and integration issues
- Improved the path from wearable biometric input through scoring to music playback
- Implemented adaptive playback using biometric intensity scoring and pre-recorded music selection
- Added the paywall and refined the running and yoga experiences
- Hardened the Amazon Web Services environment and supporting services
Regular reporting, budget tracking, client reviews and demonstrations kept progress and scope visible throughout.
Ben Etches
Founder, Sineco
“Working with Definia through the project was fantastic. The team were highly professional from day one, engaged fully with our product and our goals, and delivered everything we asked for and more. The programmers were incredibly skilled, taking on a technically difficult build and delivering it within a short timeframe. They were genuinely great to work with, and we came out of the engagement with a stronger product that was ready for launch. You are all brilliant, thanks for your support throughout this project.”
Deliver
Within 12 weeks, Definia took Sineco’s product from prototype to a production-ready MVP. Key outcomes included:
- More responsive playback and improved reliability across the customer journey
- A paywall in place to support the subscription model
- Scalability validated against the agreed early-user load profile of approximately 1,000 users
- Quality assurance, stress and throttling tests and auto-scaling validation completed, with stronger monitoring and alerting in place
- Improved release readiness and technical foundations for App Store submission
The result is more than a working app. Sineco now has a resilient MVP, tested under realistic load and failure conditions, and the app is available to download on the App Store.
Contact us
Reach out to the team to find out how we can help you.