Generate a complete week with workouts, rest days, exercises, sets, reps and RIR targets.
All Features
One training system.
One training system.
Every layer connected.
RepForge brings planning, workout execution, progression, recovery, review and community into one product — without pretending every feature belongs on the homepage.
01 · Plan
Build the week around
Build the week around
the actual athlete.
Programming starts from training context, not a generic template.
Explore Training System →Check how strongly the generated week fits profile, structure, volume and recovery spacing.
Prioritize selected muscle groups without throwing the rest of the week out of balance.
Carry joint or body-area protection preferences into exercise and planning decisions.
Keep programming aligned with equipment, experience level and preferred split.
Support missed-workout recovery, rescheduling, simplified weeks and maintain-plan scenarios.
Use split-based planning or build days manually when full AI generation is not the right tool.
Request a different weekly variation without losing the athlete context behind the plan.
02 · Train
Carry the decision
Carry the decision
onto the gym floor.
Execution stays connected to the target actually prescribed for the session.
Explore Active Workout →Run the session set by set with prescribed reps, load and RIR visible in context.
Use current-session evidence to protect or guide the next set.
Start from the canonical progression target and preserve the session-start prescription.
Adapt today's ask when effort or recovery calls for caution.
Log reserve-in-reps alongside reps and load so effort remains part of the performance record.
Replace a movement during the session when the current exercise is not the right fit.
Keep practical setup guidance attached to the movement when needed.
Use build-up guidance and plate calculation without leaving the workout flow.
Keep rest guidance available alongside the set workflow.
Train outside a generated week without giving up structured workout tracking.
03 · Progress
Turn training history
Turn training history
into the next call.
Performance evidence is used to decide what should happen next, not just displayed after the fact.
Explore Progression →Connect session evidence, comparable history and effort to the next progression decision.
Show the next supported reps, load and RIR target for the selected exercise.
Read improving, stable or declining performance from relevant history.
Keep best previous sets and performance references visible in the right role.
Visualize exercise performance over time with session-level history.
Surface meaningful personal records and training milestones from saved sessions.
Show a forward-looking target path with confidence and re-test context.
Review broader training patterns and performance summaries outside the active session.
04 · Recover
Recovery needs more
Recovery needs more
than one generic score.
Systemic and local signals remain distinct enough to guide training with useful context.
Explore Recovery →Inspect muscle-level recovery, fatigue, progression state and data maturity.
Summarize the current training state and today’s broad approach.
Keep muscle or exercise-area recovery separate from a single global recovery label.
Surface when recent demand suggests caution before adding more stress.
Represent whether progression is ready, controlled, blocked or locked by current evidence.
Let recovery context protect execution without rewriting long-term performance authority.
Evaluate fatigue, recovery debt and performance decline scenarios conservatively.
05 · Review
Finish the session with
Finish the session with
a useful conclusion.
Review layers explain what changed and what the next session should confirm.
Summarize session score, performance state, effort signals and the next-workout direction.
Compare the relevant previous result with the current session in plain language.
Turn the review into a practical next-session action.
Keep user-entered session notes attached to the saved workout context.
Step back from individual sessions and inspect broader recent training patterns.
Review training volume with weighting that better reflects the structure of the week.
Track nutrition locally with targets and short-term intake views. Nutrition does not drive RepForge AI recovery or progression decisions.
06 · Community
Share progress without
Share progress without
turning training into noise.
Community wraps identity and shared training moments around the training system.
Explore Community →Use a public training identity with profile details and avatar.
Share completed workouts with other lifters.
Share meaningful personal records and milestones.
Add training photos to Community posts.
Give lightweight positive feedback on shared training activity.
Surface relevant Community activity through real-time notification flows.
Share Community content through the device’s native sharing surface.
Use reporting plus block/unblock controls as part of the moderation foundation.
07 · Account
Keep ownership and
Keep ownership and
account controls clear.
Account, cloud and deletion controls stay separate from training intelligence.
Authenticate with Google through the app’s Firebase-backed account flow.
Sync saved workout history to the signed-in user’s cloud account.
Keep cloud workout data scoped to the authenticated user.
Clear local app data without presenting that action as equivalent to deleting published Community content.
Remove the account through the in-app deletion flow, including authored Community content and associated account data covered by the deletion implementation.
The Feature List Is Long.
The Product Story Shouldn’t Be.
Start with the training system, then go deeper only where you want more detail.
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