KULG launches a context-aware personal training assistant for runners
With its latest release, KULG introduces a major upgrade to how runners understand and improve their training: KULG AI Training Assistant, a personal AI running coach and context-aware coaching system that understands each athlete’s training history, performance patterns, recovery signals, and goals.
Instead of generic training advice, runners get instant, evidence-based insights and guidance tailored to their unique physiology, training load, and recovery context. Built specifically for recreational runners, the assistant combines training analytics, recovery analysis, and AI coaching directly inside the KULG app. Athletes can either use the shared KULG AI setup or connect their own API key and preferred LLM model for expanded usage and intelligence level.
The Training assistant is already available for subscribed runners, with free access rolling out soon.
AI running coach built for runners
KULG’s AI Training Assistant is built differently from most AI fitness tools. Instead of generic advice or persistent AI chat histories, it delivers context-aware coaching based on each runner’s actual training data, recovery state, subjective feedback, goals, and performance patterns, while keeping privacy at the core.
The assistant combines training metrics, HR zones, recovery feedback, lab data, injury history, and long-term progression to provide evidence-based running guidance that adapts to the athlete over time. It is designed specifically for runners, with intelligence focused on pacing, fatigue, load management, endurance progression, and recovery decisions.
Unlike generic AI fitness chatbots or multi-sport coaching platforms, KULG focuses specifically on running performance and endurance training. The system is built on deep athlete context, sports science principles, and a privacy-first architecture. Conversations are ephemeral by default: chats reset when closed or after 30 minutes of inactivity, with no persistent memory or hidden profiling.
The experience is integrated directly into the KULG app with Training assistant widgets on the Overview and Activities’ views, enabling both full training analysis and post-run insights. Users can start with predefined coaching prompts or ask custom questions for deeper analysis after accepting consent on first use.
Runners can ask questions such as:
Am I on track for my goal race?
Am I at risk of overtraining?
How does my last run compare to similar runs?
Am I recovering properly for my race goal?
The free plan will include 3 AI questions per week, while Runner subscribers get 10 weekly questions with the KULG AI key and 20 questions when using their own API key.
First context-aware training intelligence system
Running is data-rich but insight-poor. Modern runners generate more data than ever, but most platforms fail to connect performance, recovery, and progression into meaningful guidance.
KULG’s AI Training assistant changes that by turning training history into coaching insight, considering recovery, performance, fatigue, and goals in one system. The assistant delivers instant answers and provides personalised coaching recommendations that adapt continuously to each athlete’s context.
KULG combines the functionality of an AI running coach, training analytics platform, and recovery assistant into a single context-aware system designed specifically for endurance athletes.
The launch of the Training assistant positions KULG as the first context-aware training intelligence system built specifically for runners to progress toward their long-term goals without setbacks and injuries.
FAQ
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KULG AI Training assistant is a personalised AI running coach that analyses training history, recovery, HR zones, athlete goals, and performance data to provide real-time coaching insights inside the KULG app.
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Yes. The assistant is designed specifically for running performance, pacing, fatigue management, recovery analysis, and endurance training progression.
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Unlike general-purpose AI models such as ChatGPT or Gemini, KULG AI Training assistant has direct access to an athlete’s running-specific context, including training history, HR zones, recovery metrics, subjective feedback, goals, and performance progression. This allows KULG to provide highly personalised, evidence-based coaching insights instead of generic fitness advice. The assistant is also built specifically for endurance running, with privacy-first architecture and in-app integration designed around real training workflows. The more data the runner adds, the better the context used for analysis.
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No. Conversations are ephemeral and automatically reset after the chat is closed or after 30 minutes of inactivity.
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Yes. Users can connect their own API key and choose their preferred LLM model under Settings → AI.
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KULG Training assistant is rolling out in the next week or two on the free plan.
