Pricing
Pricing — Optimize Every Price, At Scale
AI-driven price optimization powered by real data,constraints, and business rules.
Pricing built on real retail complexity
Data
Sales
Competitors
Costs
Logic
Constraints
Rules
Strategy
AI Models
Elasticity
Optimization
Forecasting
Data + Logic + AI → converge into one pricing engine
How Pricing Works
Step 1
Demand Modeling
SKU elasticity (highconfidence)
Category / cluster fallback
Competitive signals
Step 2
Optimization
Profit / revenue goals
Price constraints
Business rules
Step 2
Exploration
Controlled price testing
Small adjustments (±2–5%)
Confidence-based strategy
Step 4
Learning Loop
Collect results
Update models
Reduce uncertainty
Key Features
Elasticity Modeling
Estimate demand sensitivity per product
Rule-based Constraints
Full control over pricing boundaries
Optimization Engine
Find the best price automatically
Competitor Integration
Always aligned with the market
AI Recommendations
Clear, explainable price suggestions
Works Inside AI Grid
Pricing where your data lives
Pricing Strategies
Choose your approach. Combine rules and AI to match your business goals.
Margin Protection
Conservative
Min margin: 5%
Limit price decrease
Priority: protect margin
Priority: margin > competitiveness
Competitive Matching
Balanced
Match competitor price ±2%
Keep margin above threshold
Priority: market position
Priority: competitiveness
Aggressive Growth
Aggressive
Undercut competitors
Allow margin compression
Test elasticity
Priority: volume > margin
Profit Optimization
AI driven
Maximize profit curve
Use elasticity
Ignore competitors if needed
Priority: maximize profit curve
From Analysis → Action
Before
Spreadsheets
Manual updates
Slow decisions
After
Automated recommendations
Controlled execution
Continuous optimization
Stop guessing prices. Start optimizing them.
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