1 points | by ayushmaanbhav 9 hours ago
3 comments
The Current Reality
*Scattered Across Code* ```java // Hidden in service layer if (customer.age > 65 && customer.income < 50000) { premium = basePremium * 1.5; } else if (customer.riskScore > 7) { premium = basePremium * 1.3; } // ... 500 more lines scattered across 20 files ``` *Buried in Spreadsheets* ```text Excel files passed between teams - v1_final.xlsx - v1_final_FINAL.xlsx - v1_final_FINAL_approved_v2.xlsx No version control. No audit trail. ``` *Lost in Configuration Files* ```yaml # config/pricing_rules.yaml # Last modified: ??? # By whom: ??? # Why: ??? rules: - condition: "age > 65" action: "multiply 1.5" ```
The Consequences
Problem | Impact
Fragmented Logic | Business rules scattered across codebases, spreadsheets, and documents
No Single Source of Truth | Different systems calculate differently, causing inconsistencies
Change is Risky | Modifying rules requires code deployments; one mistake affects production
No Visibility | Business teams can’t see or understand the actual rules running
No Audit Trail | When rules change, there’s no record of who changed what and why
Slow Time-to-Market | Every rule change requires developer involvement and release cycles
Features
Rule Engine
- JSON Logic Expressions - Industry-standard rule format
- Tiered Compilation - AST → Bytecode VM (3.5x speedup)
- DAG Execution - Automatic dependency resolution
- Parallel Processing - Rules without dependencies run concurrently
- Cycle Detection - Prevents infinite loops
Visual Interface
- Block-based Editor - Build rules visually
- Interactive DAG Canvas - Drag, zoom, and explore
- Real-time Simulation - Test with live feedback
- AI Chat Assistant - Natural language to rules
- Impact Analysis - See what changes affect
Data Management
- Product Lifecycle - Draft → Pending → Active → Discontinued
- Abstract Attributes - Reusable templates
- Custom DataTypes - With constraints and validation
- Enumerations - Type-safe value sets
- Tag Organization - Filter and group attributes
Enterprise Ready
- REST + gRPC APIs - Dual protocol support
- DGraph Database - Graph-native storage
- LRU Caching - Hot data performance
- Batch Evaluation - Process multiple inputs
- Streaming Support - Real-time evaluation
Who Is Product-FARM For?
Product Managers
- Define business logic without writing code
- Visualize how rules interact and affect outcomes
- Test scenarios before going live
- Track changes and understand their impact
Business Analysts
- Translate business requirements into executable rules
- Validate rules against expected outcomes
- Document rule logic in a structured format
- Collaborate with technical teams effectively
Developers
- Focus on building features, not maintaining rule spaghetti
- Integrate via REST or gRPC APIs
- Trust that business logic is correct and consistent
- Deploy rule changes without code releases
Compliance & Audit Teams
- Complete audit trail of all rule changes
- Understand exactly how decisions are made
- Verify regulatory compliance
- Generate reports on rule behavior
The Current Reality
*Scattered Across Code* ```java // Hidden in service layer if (customer.age > 65 && customer.income < 50000) { premium = basePremium * 1.5; } else if (customer.riskScore > 7) { premium = basePremium * 1.3; } // ... 500 more lines scattered across 20 files ``` *Buried in Spreadsheets* ```text Excel files passed between teams - v1_final.xlsx - v1_final_FINAL.xlsx - v1_final_FINAL_approved_v2.xlsx No version control. No audit trail. ``` *Lost in Configuration Files* ```yaml # config/pricing_rules.yaml # Last modified: ??? # By whom: ??? # Why: ??? rules: - condition: "age > 65" action: "multiply 1.5" ```
The Consequences
Problem | Impact
Fragmented Logic | Business rules scattered across codebases, spreadsheets, and documents
No Single Source of Truth | Different systems calculate differently, causing inconsistencies
Change is Risky | Modifying rules requires code deployments; one mistake affects production
No Visibility | Business teams can’t see or understand the actual rules running
No Audit Trail | When rules change, there’s no record of who changed what and why
Slow Time-to-Market | Every rule change requires developer involvement and release cycles
Features
Rule Engine
- JSON Logic Expressions - Industry-standard rule format
- Tiered Compilation - AST → Bytecode VM (3.5x speedup)
- DAG Execution - Automatic dependency resolution
- Parallel Processing - Rules without dependencies run concurrently
- Cycle Detection - Prevents infinite loops
Visual Interface
- Block-based Editor - Build rules visually
- Interactive DAG Canvas - Drag, zoom, and explore
- Real-time Simulation - Test with live feedback
- AI Chat Assistant - Natural language to rules
- Impact Analysis - See what changes affect
Data Management
- Product Lifecycle - Draft → Pending → Active → Discontinued
- Abstract Attributes - Reusable templates
- Custom DataTypes - With constraints and validation
- Enumerations - Type-safe value sets
- Tag Organization - Filter and group attributes
Enterprise Ready
- REST + gRPC APIs - Dual protocol support
- DGraph Database - Graph-native storage
- LRU Caching - Hot data performance
- Batch Evaluation - Process multiple inputs
- Streaming Support - Real-time evaluation
Who Is Product-FARM For?
Product Managers
- Define business logic without writing code
- Visualize how rules interact and affect outcomes
- Test scenarios before going live
- Track changes and understand their impact
Business Analysts
- Translate business requirements into executable rules
- Validate rules against expected outcomes
- Document rule logic in a structured format
- Collaborate with technical teams effectively
Developers
- Focus on building features, not maintaining rule spaghetti
- Integrate via REST or gRPC APIs
- Trust that business logic is correct and consistent
- Deploy rule changes without code releases
Compliance & Audit Teams
- Complete audit trail of all rule changes
- Understand exactly how decisions are made
- Verify regulatory compliance
- Generate reports on rule behavior