Local Intelligence and Curated Programs
BodEvo does not call external AI services. Plan analysis and meal suggestions use local rule-based logic that summarizes likely outcomes, strengths, risks, bottlenecks, and suggested adjustments from the data already entered. This keeps the app local-first and avoids API keys in the frontend.
Training is no longer rule-generated at all. Instead of assembling a routine from generic heuristics, the app ships a library of established programs — a full-body linear progression, the beginner pattern popularized by the r/Fitness wiki, Cody Lefever's GZCL tier method, upper/lower, push/pull/legs, and a bodyweight template — filterable by level, goal, days per week, and available equipment.
Every program credits whoever devised it, links to where they published it, and states plainly how our rendering differs from theirs. A program's structure is a method, which copyright does not cover, but an author's own words and branding belong to them: descriptions here are ours, and trademarked program names are not used.
Once you log a session, the app fills in the next one — adding weight after a session you completed, holding it after one you missed, and cutting back after repeated misses rather than prescribing a load you have already failed.
Related in “How the tools & numbers work”
- Integrated Calculator Flow
- Formula A vs Formula B
- How Daily Activity Affects Calories
- Why Step Count Matters
- How Activity Levels Work
Use it in the app: open Learn inside BodEvo — free, local-first, no account required.