AI Sport Tech Consultant

Andrea
Zignoli

I help sport tech startups turn physiology and performance data into production-ready AI solutions that drive subscriptions, enhance UX, and deliver new features.

I bridge the gap between sports science research and deployed code — whiteboarding with exercise physiologists in the morning, shipping containerised APIs by evening.

Services

What I do

Training Prescription & Assessment

Adaptive algorithms that personalise training load based on individual athlete physiology, historical performance data, and real-time feedback signals.

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Cardiopulmonary Exercise Testing

ML models for automated threshold detection and CPET interpretation — from ventilatory thresholds to VO₂ kinetics — deployed at scale.

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Continuous Glucose Monitoring

Insights extraction from CGM data for metabolic optimisation in endurance athletes — identifying fuelling patterns, glycaemic responses, and actionable recommendations.

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Pacing & Race Strategy

Simulation models for optimal pacing, incorporating aerodynamics, terrain, fatigue dynamics, and competitive constraints to maximise performance.

Approach

How I work

I combine first-principles modelling with machine learning. Depending on the problem, I write differential equations by hand, train neural networks, or blend both approaches.

I prototype fast, validate against real data, and iterate until the model delivers business value. Full-stack: from research and model development to Docker containers, Flask/FastAPI services, and production deployment.

Recent work: educational courses, performance models deployed as APIs, web apps connected to CMS via LLM pipelines.

Tech stack

PythonClaude CodeFastAPIFlaskDockerAWS LambdaHerokuLLM PipelinesPyTorch/Kerasscikit-learnPandasFastAPIGit
Interested in discussing a project proposal? andrea.zignoli@unitn.it

Background

Who I am

Research & Education

M.Eng. Mechatronics + PhD Sports Science — I enrolled to study robotics and ended up studying the most wonderfully made machine: the human body.

Post-doctoral research at the University of Trento (sport performance modelling), Yokohama National University (rehabilitation robotics), and the University of Verona (exercise physiology).

I maintain active research collaborations and publish in peer-reviewed journals. Associate Editor at Sports Engineering (Springer) and peer reviewer for several top sports science journals.

Clients & Collaborations

Athletica.aiApr 2024 – Present

AI-driven training platform

Modelling, feature design, backend development

Enhance-dJan 2025 – Jun 2025

T1D training & CGM platform

Agentic frameworks, backend systems

Tyme WearDec 2024 – Present

Wearable tech

Deep learning models, backend solutions

Supersapiens2021 – 2024

CGM for athletes

Data analysis, algorithm development, scientific writing

Speaking

Talks & podcasts

Training Science Podcast2025

AI Agents, HRV Readiness & the Next Era of Training

Deep dive on how AI agents are being integrated into training platforms, how HRV readiness assessments are evolving, and what the next generation of training methodologies looks like.

Listen
Training Science Podcast2025

Workout Reserve and the Future of AI Coaching

Why traditional models like W′ fall short, and how Workout Reserve offers a more flexible mechanical way to understand athlete capability. The future of AI coaching: RAG-AI, LLMs, and agents in training platforms.

Listen
Training Science Podcast2025

Modelling First: Building Smarter Endurance Training

Why modeling must come before AI can be useful in coaching. Models like Critical Power, Banister TRIMP, and HRV response curves provide the structure AI needs to make smart, adaptable decisions.

Listen
Video2024

Human-AI Balance in Coaching: Athletica's AI-Assisted HRV Monitoring

HRV and its role in optimising training readiness and recovery. As co-architect of Athletica's AI-assisted HRV monitoring, I explain how AI enhances HRV analysis while maintaining the importance of human expertise.

Watch