Fix and Sail

Fix and Sail started as the idea of a private client who wanted to turn it into a real product: a platform that knows a boat in detail and helps its owner manage it. I followed development from the prototype to the launch phase, and it's one of the projects I've enjoyed most, for the quality of the design and the advanced features to build.

The project

Fix and Sail presents itself as an AI assistant that knows your boat in detail and helps with maintenance, deadlines, manuals and accessories. It has three modules: My Boat (your boat in digital form, maintenance, reminders and checklists), Explore (shipyard history and accessory data sheets) and the Captain, the AI assistant that answers based on the manuals of the accessories on board. When AI isn't enough, it connects you with real experts. You start for free, in two minutes.

Architecture and technologies

The frontend is a Nuxt.js application, the backend is Strapi, consumed through REST APIs. Boats, accessories and documents are modelled as content types, the private area works with authenticated calls and state is shared across sections, with loading and errors handled so users never lose track. It's a lean architecture, suited to a product that needs to reach the market quickly but must also be able to grow without being rewritten.

My work

From Figma to components

The design comes from Figma and my job is to turn it into a Nuxt.js interface faithful in every detail: typography, spacing, states and behaviour on every screen. I don't just reproduce screens one by one; I build a base of reusable components, so every new section comes out consistent with the existing ones and the design stays solid as the product grows.

Boat configuration and AI recognition

The heart of the application is the configuration: users recreate their boat digitally, choosing model and accessories, and customise it. Maintenance, deadlines, checklists and the AI assistant's answers all rest on it, so every accessory added changes what the rest of the platform shows, and the data structure and flow must be designed with care. To make data entry simple, the catalogue of models and accessories is paired with AI recognition: instead of searching for codes and part numbers, you take a photo of the part and the AI suggests the model to check before linking it to the boat.

The outcome

I turned an idea into a product, with a Nuxt.js and Strapi architecture ready for launch and for growth. A configuration with many variables, across models, accessories, documents and deadlines, became a simple path for people who sail, and data entry lost its biggest friction: a photo instead of a catalogue search.