Product Tour

Trainingload.ai connects five kinds of evidence: who the athlete is, what was planned, what was completed, how load and performance changed, and what decision should come next.

Trainingload.ai

Home training workspace

Plan context, completed activity, and current training state converge in the signed-in home experience.

Plan

4 week block

Load

steady build

Activity

matched

AI review

ready

Home and Today

Use Home on web or Today on mobile for the immediate training question: what is planned, what just happened, and what needs attention. These surfaces summarize data from plans, activities, current state, and reviews rather than creating separate copies.

Activities

Activities is the completed-workout record. You can:

• Import provider data or FIT, TCX, and GPX files.
• Search and filter the feed.
• Open detailed maps and sensor charts.
• Correct sport classification or session RPE where supported.
• Export or delete an activity.
• Link the activity to a planned workout.
• Review strength-specific exercise and set data.

Start with Activities Feed and Search and Activity Detail.

Calendar and day detail

Calendar puts planned workouts, completed activities, and competitions on the same date axis. Day detail is the bridge between “what should happen” and “what did happen.” It is also the fastest place to notice an unlinked activity or a conflict on competition day.

Plans and structured workouts

Plans support manual and AI-assisted creation, lifecycle states, workout status, expected load, completed activity links, and plan review. Workouts use endurance, strength, or supported text structures rather than an unvalidated note blob.

Continue with Plans and Workouts.

AI Coach

AI Coach can use account context to discuss training, create a plan draft, review execution, and prepare a workout adjustment. Mutating actions remain reviewable: inspect the structured card or before/after change before applying it.

Competitions

Competition events are independent from plans. Store date, sport, importance, goal, distance or target time, location, and notes. Trainingload.ai can then evaluate how a competition affects the current plan without forcing the event to become a planned workout.

Dashboard and analysis

Dashboard, Analysis, Power, Heart Rate, Pace, PMC, best-distance, map, and metric-history views answer different questions from the same activity history. Use them to test a hypothesis—such as whether load is building steadily or efficiency is improving—not to collect isolated numbers.

Profile, thresholds, zones, and current state

Profile settings establish units, time zone, body metrics, sport context, thresholds, zone models, and load-source priority. Mobile current-state input adds short-lived athlete context that can help review the training day.

Connections, notifications, and usage

Connections control activity and workout exchange with supported providers. Notifications show import and review results. Review automation controls which eligible AI reviews can run automatically. Usage shows AI entitlement and consumption information.

Mobile recording

The mobile recorder captures a workout locally, recovers interrupted sessions where possible, and imports the saved result into the same activity pipeline used by connected providers and file uploads.

Recommended next step

Choose the workflow that matches your goal in Choose Your Path, then complete Getting Started.