Azzilla
Fitness, nutrition, community, and AI automation in one subscription platform.
- Client
- Azzilla
- Sector
- Health, fitness, and wellness
- Our role
- Full-stack platform build and AI automation layer
- Status
- In production, AI modules in active development
The brief
What was breaking
People pursuing a fitness goal end up running their lives across four apps: one for workouts, one for meals, one for tracking, and a group chat somewhere else. None of them know about each other, so nothing adapts to anything. Azzilla wanted the whole loop in one subscription product.
- Fitness, nutrition, tracking, and community lived in separate tools, so no programme could respond to what a user actually did.
- Personalised programming at scale is a content problem before it is a software problem, and it was being handled manually.
- Recurring revenue depends on engagement, and there was no mechanism to nurture leads or bring lapsed users back.
- Operating across five languages and multiple markets multiplied the admin burden on a small team.
What we built
The system we delivered
Fitness and nutrition programming
An exercise library with progressions, regressions, and variations, plus meal blocks, recipes, macro tracking, and generated grocery lists, all assembled into saved weekly programmes.
Health tracking that feeds the programme
Check-ins, questionnaires, water intake, and calculated BMR, BMI, body fat, and heart-rate training zones, computed from configurable clinical equations rather than one hardcoded formula.
A community layer, not a comments section
Timelines, posts, groups, events, messaging, and follows, with real-time delivery so conversation happens live rather than on refresh.
GPT-powered assistance and content
A conversational assistant, generated daily motivational content, and GPT-analysed bug reports, with every model call logged for cost and quality review.
Semantic search over the platform's own knowledge
A vector store with cosine-similarity search lets the assistant answer from Azzilla's own material instead of guessing from general training data.
Automated lead nurturing
Scheduled bot jobs prospect and score leads through GPT analysis, sync them to email campaigns, and log every action for review.
Built with
The stack behind it
The lead tier is what makes this system what it is. Everything under it is the platform that carries it.
AI and intelligence
Backend
Frontend
Platform
What changed
The result in production
One ecosystem instead of four apps
Programming, nutrition, tracking, and community share a data model, so what a user does in one place informs the rest.
AI doing the repetitive work
Assistant conversations, daily content, lead scoring, and bug triage run automatically, with the model calls logged and reviewable.
Built to operate, not just to launch
Caching, queues, containerised deployment, and an admin surface for every module mean the platform is maintainable by the team that runs it.
Same problem?
Let's scope what this would look like for you
Start with a two-week Discovery Sprint. We map your highest-value workflows and deliver a prioritised pilot roadmap grounded in what we have already shipped.