Apple Ads auctions change constantly. Competition, user behavior, and seasonality shift daily. Reinforcement learning continuously adapts to these changes, learning from every interaction.
A machine learning paradigm where an agent learns optimal behavior by trial and error, maximizing cumulative rewards over time.
Pre-trained through millions of simulated auctions, the model learns optimal bidding strategies before deployment.
When activated on your campaigns, it's already optimized and ready to perform, fine-tuning only to your specific goals.
Reward represents performance relative to your goals (CPA, ROAS).
During pre-training in simulations, early exploration yields low rewards. As the model discovers better strategies, performance improves steadily, ready for deployment.
Apple Ads auctions are dynamic systems where static models quickly become obsolete.
Traditional models only scale what works (exploitation). RL balances scaling proven strategies with testing new opportunities (exploration).
Exploitation
Scale high-performing keywords
Exploration
Test new keywords and bid levels
Purpose-built for Apple Ads optimization, trained on campaign-specific data.
Offline simulation for training, online fine-tuning to adapt to your specific goals.
Trained on millions of simulated auctions. Learns general bidding strategies without risking budgets.
Adapts to your real campaign data. Learns app-specific patterns and optimizes for your goals.
Every flagship model is validated through backtesting and A/B testing before deployment.
Historical campaign replay validates performance improvements
Control vs RL comparison provides clear metrics
Ensures conversions are truly incremental, not cannibalized
Measurable results across multiple industries
Autonomous optimization, every day.
Observes Performance
Pulls latest campaign data daily
Analyzes Patterns
Identifies winners, losers, and shifts in conversion rates
Adjusts Bids
Calculates optimal bid for each keyword
Explores Opportunities
Tests new keywords and bid levels
Manages Budget
Ensures optimal pacing and allocation
Learns & Adapts
Updates strategy based on outcomes
Purpose-built for ASA auction dynamics, not adapted from other platforms.
Pre-trained on far more auction environments than any single client generates.
Optimizes for real growth, not organic cannibalization.
Continuous updates as market conditions evolve and data accumulates.
Each client gets a dedicated model. Your data stays yours.
Explore real results from clients using our RL bidding system.