Family
PPO
in-developmentApache 2.0rlretail-facing
Savings Optimizer.
RL agent for savings-plan optimization. PPO-based policy learning over user financial state. Continuous online learning.
Foundation · PPO
What it does
The honest description.
RL agent for savings-plan optimization. PPO-based policy learning over user financial state. Continuous online learning.
Architecture
How it works.
Current savings balance, goals (shortfall amount + target date), income and spending trends, investment returns by asset class. Optimized savings plan: monthly savings target, asset-allocation advice, account recommendation. Confidence in plan feasibility + online-learning reward signal.
Training data & drift
What it learned from, and how we watch it.
Source
Inputs: Current savings balance, goals (shortfall amount + target date), income and spending trends, investment returns by asset class.
Drift baseline · current quarter
Drift baseline not yet documented for this model.
What it's NOT
- PPO (Proximal Policy Optimization) RL agent.
- Online learning from user adoption of savings plan recommendations.
- No per-run cost.
- Online learning only — no batch trainer.
Who calls this model
Across the house and the API.
Internal routes
No public routes documented yet.
Featured in
/features/goalsVersion history · immutable once published
Every release, traceable.
Data Mukodi holds about you is subject to DPDP §12 erasure (use /consent in the app), and any concern about this model can be raised via [email protected] under DPDP §13 grievance, or via /security.