Transform your business with AI-powered process optimization
Products
Smart Operators
Sindhan Decide

Sindhan Decide

Rule engine and ML decision framework for automated business logic execution.

Overview

Sindhan Decide implements a hybrid decision engine combining rule-based logic (RETE algorithm) with ML models (decision trees, gradient boosting). Supports complex decision flows with uncertainty quantification and explainability features.

Key Features

Cognitive Decision Making

  • Context-aware decision logic
  • Multi-factor analysis
  • Continuous learning from outcomes

Balanced Judgment

  • Risk assessment and mitigation
  • Trade-off analysis
  • Ethical consideration frameworks

Explainable AI

  • Clear reasoning for every decision
  • Audit trail for compliance
  • Human-readable explanations

Decision Types

Operational Decisions

  • Resource allocation
  • Priority assignment
  • Routing and distribution
  • Exception handling

Business Decisions

  • Pricing optimization
  • Credit approvals
  • Vendor selection
  • Investment recommendations

Strategic Decisions

  • Market entry timing
  • Product launch decisions
  • Partnership evaluations
  • Risk management

How It Works

  1. Data Input: Gather relevant information from multiple sources
  2. Context Analysis: Understand the situation and constraints
  3. Option Generation: Identify possible decision paths
  4. Impact Prediction: Forecast outcomes for each option
  5. Decision Selection: Choose optimal path based on objectives
  6. Learning Loop: Analyze results to improve future decisions

Decision Frameworks

Rule-Based Logic

  • Predefined business rules
  • Compliance requirements
  • Policy enforcement

Machine Learning Models

  • Pattern-based decisions
  • Predictive analytics
  • Classification and clustering

Deep Learning

  • Complex pattern recognition
  • Natural language understanding
  • Image and document analysis

Hybrid Approaches

  • Combine rules with AI
  • Human-in-the-loop options
  • Escalation protocols

Industry Applications

Financial Services

  • Loan Approvals: Instant credit decisions with 95% accuracy
  • Fraud Detection: Real-time transaction analysis
  • Investment Recommendations: Personalized portfolio optimization

Healthcare

  • Treatment Recommendations: Evidence-based care suggestions
  • Resource Allocation: Optimize staff and equipment usage
  • Risk Assessment: Patient outcome predictions

Retail

  • Dynamic Pricing: Real-time price optimization
  • Inventory Management: Stock level decisions
  • Personalization: Customer experience customization

Advanced Capabilities

Multi-Criteria Optimization

  • Balance multiple objectives
  • Handle conflicting priorities
  • Pareto-optimal solutions

Uncertainty Handling

  • Probabilistic reasoning
  • Scenario analysis
  • Confidence scoring

Adaptive Learning

  • Continuous improvement
  • Domain adaptation
  • Transfer learning

Technical Capabilities

  • Decision Throughput: 10K+ decisions/second with under 10ms latency
  • Rule Engine: RETE-based pattern matching with conflict resolution
  • ML Integration: Scikit-learn, XGBoost models with SHAP explanations
  • Audit Trail: Complete decision logging with reasoning traces

Implementation Best Practices

  1. Start Simple: Begin with well-defined decisions
  2. Validate Thoroughly: Test against historical data
  3. Monitor Closely: Track decision quality metrics
  4. Iterate Quickly: Improve based on feedback
  5. Maintain Oversight: Keep human review capabilities

Ethical Considerations

  • Transparency in decision logic
  • Bias detection and mitigation
  • Fair treatment across demographics
  • Regulatory compliance

Quick Deployment Guide

Prerequisites

  • RAM: 32GB minimum, 128GB recommended for production
  • OS: Linux (Ubuntu 20.04+), macOS, or Windows 10+
  • Docker installed on your system
  • GPU recommended for complex decision models

Deploy in Minutes

Production Deployment (Linux servers):

# Download and start with production configuration
curl -sSL https://get.sindhan.ai/decide | bash -s production

Development/Testing:

# Download and start with minimal resources
curl -sSL https://get.sindhan.ai/decide | bash

That's it! The system will:

  • Download AI decision engine containers
  • Configure machine learning models
  • Set up decision rule frameworks
  • Initialize decision monitoring dashboard

Access & Configuration

  1. Open Browser: Navigate to http://<your-server-ip>:8093

  2. Initial Setup:

    • Define decision criteria
    • Configure business rules
    • Set approval thresholds

  3. Connect Data Sources:

    • Real-time data streams
    • Historical decision data
    • External context sources

  4. Train Models: Upload decision examples for AI learning

View Results

Access decision center at: http://<your-server-ip>:8093/decisions

Decision intelligence:

  • Decision logic explanations
  • Decision outcome tracking
  • Confidence scoring analysis
  • Decision audit trails

Production Recommendations

  • GPU clusters for complex decision models
  • High-availability setup for critical decisions
  • Data encryption for sensitive decision inputs
  • Compliance logging for regulatory requirements

Getting Started Summary

Total deployment time: 18 minutes

✅ System deployed
✅ Models configured
✅ Rules defined
✅ Decisions automating

Learn how the Decision Engine can transform your operations. Schedule a consultation today.

Sindhan PredictSindhan Execute