From Data to Intelligence
AI-Powered Analytics Pipeline
SENTINEL transforms raw supply chain data into actionable intelligence through a sophisticated multi-stage analytics pipeline. Our foundation principle: Data is just data. Information is created from data, knowledge, and experience.
The SENTINEL Analytics Pipeline
Four critical stages transform raw supply chain data into predictive intelligence
Interface & Integration
SENTINEL's first stage establishes comprehensive data connectivity across diverse supply chain systems, creating a unified data foundation from disparate sources.
Multi-Protocol Integration
REST APIs, EDI, XML, JSON, real-time streaming protocols
Sensor Networks
RFID, BLE, cellular, satellite, mesh radio communications
Enterprise Systems
ERP, WMS, TMS, CRM integration with legacy compatibility
Real-Time Processing
Sub-second data ingestion with edge computing capabilities
Processing, Cleansing & Normalization
Advanced algorithms validate, cleanse, and standardize data across formats and systems, ensuring high-quality information feeds downstream analytics processes.
Data Validation
Automated quality checks, anomaly detection, completeness validation
Intelligent Cleansing
Duplicate removal, format standardization, missing data interpolation
Normalization
Unit conversion, timezone alignment, format standardization
Semantic Enrichment
Ontology mapping, contextual tagging, metadata enhancement
Relationship Development
Graph-based analytics establish complex relationships between entities, events, and patterns, creating a comprehensive network view of supply chain interactions and dependencies.
Graph Analytics
Entity relationship mapping, network analysis, dependency graphs
Correlation Engine
Multi-dimensional pattern detection, causal relationship identification
Context Awareness
Temporal relationships, geospatial correlations, business rule integration
Knowledge Graphs
Semantic networks, ontology-driven insights, expert system integration
Data Analysis, Evaluation & Response
Advanced AI and machine learning models generate predictive insights, risk assessments, and automated responses, transforming processed information into actionable intelligence for decision makers.
Predictive Analytics
ML models for demand forecasting, risk prediction, optimization
Retrieval Augmented Generation (RAG)
AI-powered query system combining real-time data with knowledge bases for intelligent responses
Vector Processing
High-dimensional similarity search and semantic analysis for pattern recognition
Agentic Workflows
Autonomous AI agents orchestrating complex multi-step analysis and response processes
Intelligent Alerting
Context-aware notifications, severity classification, escalation workflows
Dynamic Visualization
Real-time dashboards, interactive analytics, mobile-responsive interfaces
Automated Response
Rule-based actions, API triggers, workflow automation, decision support
Our Data Foundation Drives Intelligence
Data Quality
Rigorous validation and cleansing ensure high-fidelity inputs to all downstream analytics processes
Connected Intelligence
Graph-based relationships reveal hidden patterns and dependencies across complex supply networks
Predictive Models
AI/ML algorithms continuously learn and adapt, improving prediction accuracy over time
Real-Time Intelligence
Sub-second processing enables immediate response to critical supply chain events