What is CHAI Universe?

CHAI Universe is CloudHedge's AI-powered application discovery and portfolio intelligence platform. It maps your entire enterprise application estate — thousands of apps across hundreds of servers — and delivers actionable modernization roadmaps in hours, not months.

How does CHAI Universe discover applications?

CHAI Universe uses agentic AI to automatically scan, classify, and score every application in your portfolio. It analyzes dependencies, infrastructure, and business criticality without requiring manual inventory or documentation.

What is sovereign AI in CHAI Universe?

CHAI Universe operates as a fully air-gapped system that runs inside your own cloud tenant. No source code or application data leaves your environment — the AI engine connects to your own inference endpoints (AWS Bedrock or Azure AI Foundry).

Can CHAI Universe work without existing documentation?

Yes. CHAI Universe discovers applications directly from your runtime environment and infrastructure. It doesn't depend on existing documentation, architecture diagrams, or tribal knowledge.

How long does a portfolio assessment take with CHAI Universe?

A typical enterprise portfolio of 1,000+ applications can be discovered and assessed within days. Traditional manual approaches take 6-12 months for the same scope.

The Application Modernization Harness for the Enterprise

Name: CHAI Universe™
Brand: CloudHedge
Availability: InStock

A unified harness bringing assessment, intelligence, learning, and execution together, transforming legacy systems at enterprise scale with Sovereign AI and advanced Reinforcement Learning.

Get Started → ▶ Watch Demo

Platform Architecture

CHAI Universe MCP

An intelligent control plane orchestrating every layer of your modernization journey.

Orchestration

CHAI Flow Engine

Orchestration Layer

Multi-agent collaboration turning modernization chaos into controlled, repeatable workflows.

CHAI Recipes

Optimization Templates

Enterprise-approved, governed modernization playbooks. Reusable blueprints for every use case.

Dynamic Context Engine

Adaptive Intelligence

App Graph Builder, Dependency Mapper, Knowledge Graph, and Hallucination Filter.

Tri-Vector Analyzer

Workload Analyzer

Performance Profiling

Runtime Analyzer

Live Monitoring

Source Code Analyzer

Static Analysis

Intelligence

Unified Intelligence

Engine

CHAI Reinforcement

Learning

Context Aware Unified Intelligence With Chai

See It In Action

CHAI Universe at Work

From legacy source code to a complete design document, generated in seconds, not weeks.

ATRS (Airline Ticket Reservation System) — Design Document

Table of Contents

01Executive Summary 02System Overview 03Layered Architecture 04Domain Model 05Service Layer & Fare Pipeline 06REST API 07Security Filter Chain 08Async Processing (JMS) 09Architecture Assessment 10Modernization Path

1. Executive Summary

ATRS is a multi-module Java/Spring web application for airline ticket reservation. Built on the TERASOLUNA framework (v5.10.0), it demonstrates enterprise-grade patterns for a transactional booking system.

Version1.11.0.RELEASE Java17 FrameworkSpring MVC 6.x, Spring Security 6.x ORMMyBatis DatabasePostgreSQL ViewJSP MessagingActiveMQ Artemis (JMS)

2. System Context

Fig 2.1 — Actors interact via HTTP and REST; both funnel through the Service Layer into PostgreSQL and the JMS broker.

2.1 Core Features

A0–A2Authentication — login, logout, session mgmt B0–B2Ticket Operations — flight search, fare calc, reservation C0–C2Member Management — registration, profile update D1Reporting — async reservation history report

3. Layered Architecture

Fig 3.1 — Five-layer stack with strict downward dependencies — presentation through infrastructure, terminating at external data & messaging.

4. Domain Model — Core Entities

MembercustomerNo, name, mail, creditNo FlightdepartureDate, flightName, vacantNum RouterouteNo, basicFare, airports ReservationreserveNo, totalFare, representative Passengername, age, gender FareTypediscountRate, reservationPeriod

5. Service Layer — 10 services across 4 domains

b0TicketSharedService · calculateFare, validate b1TicketSearchService · searchFlight(criteria) b2TicketReserveService · register, calcTotal a1 · a2AuthLogin / Logout · updateLoginStatus d1ReservationHistoryReport · async via JMS

5.3 Fare Calculation Pipeline

Fig 6.3 — Four-step deterministic pricing pipeline composed by TicketSharedService.calculateFare().

6. REST API Layer — /api/v1

GET/api/v1/flight → FlightResource[] (200) POST/api/v1/ticket → TicketReserveResource (201) GET/api/v1/ticket/check → TicketReserveResource (200)

7. Security Filter Chain

Fig 9.1 — Two independent filter chains: stateful Web (form-login, CSRF) and stateless REST (HTTP Basic, no CSRF).

8. Async Processing (JMS) — Report Generation

Fig 12.5 — User-facing request returns immediately with an ID; heavy report generation runs off-thread via JMS.

9. Architecture Assessment

Modularity4 / 5 — well-structured multi-module Maven project Maintainability4 / 5 — clean separation of concerns Security4 / 5 — comprehensive Spring Security Scalability3 / 5 — stateful design limits horizontal scaling Documentation2 / 5 — limited inline/external docs Overall3.5 / 5 — solid enterprise architecture with room for modernization

9.3 Technology Maturity vs Maintenance

Fig 13.3 — Modern core (Spring 6, Java 17, PostgreSQL) vs. legacy UI/framework (JSP, TERASOLUNA) that warrants modernization.

10. Recommended Modernization Path

ContainersDockerize · deploy on Kubernetes (AKS/EKS/GKE) API DocsIntroduce OpenAPI / Swagger CachingAdd caching for airports, routes, fare types MonitoringSpring Boot Actuator + Micrometer + Prometheus CI/CDGitHub Actions pipeline — automated build & deploy

Prompt

Generate a source code design document for the ATRS application. Analyze the full codebase (modules, services, entities, architecture layers) and produce a comprehensive technical document.

Source

atrs-1.11.0.RELEASE (Java/Spring)

Generated By

CHAI Universe™ — Context Engine

Core Capabilities

Six Pillars of Transformation

Enterprise-grade capabilities designed to accelerate your modernization journey.

Context Aware Modernization

Three Dimensions. One Truth.

Tri-Vector assessment builds dynamic context, making transformation predictable and eliminating hallucination.

Sovereign AI

Your intelligence stays in your walls.

Intelligence stays within your organization with air-gapped deployment and zero data exfiltration.

Unified Intelligence

One brain. Infinite reach.

Eliminates fragmented LLM usage with one cohesive AI layer across your entire SDLC.

CHAI Recipes

Enterprise-approved blueprints.

Governed modernization playbooks with consistent, reusable blueprints for .NET, Java, VMware, DC exits and more.

Reinforcement Learning

Gets smarter with every move.

AI that continuously learns and improves from your environment with enterprise-specific optimization.

Enterprise Scale

Built for complexity.

Handles complex application portfolios with governance and compliance (CMMC, IL6, HIPAA) at its core.

How It Works

From Legacy to Modern

A systematic four-step approach to enterprise transformation.

Assess

Tri-Vector analysis captures runtime, dependencies, and business context.

Plan

AI-generated pathways aligned to your goals and constraints.

Execute

Governed recipes automate transformation with guardrails.

Optimize

Continuous learning refines pathways and reduces rework.

New · Business Value Framework

CHAI Compass™: Quantify Value Before You Commit

The newest pillar of the CHAI Universe. Compass ensures every modernization decision is backed by business value, compliance posture, and goal alignment, not guesswork.

ROI Modeler Compliance Score Goal Modeler Regression Suite

Get Early Access →

End-to-End Platform

Works for Brownfield & Greenfield

Whether modernizing legacy applications or building new, CHAI handles both.

Brownfield Applications

Modernize existing legacy systems with full context, safety, and institutional knowledge, without ripping out what works.

Cost & Team Optimization Transparency & Traceability Workflow & Agent Automation Test Case Generation

Greenfield Applications

Build AI-native, agentic applications from the ground up, with governance, compliance, and self-healing built in from day one.

Migration & Modernization App Lifecycle Management Compliance & Documentation Self-Healing Agents

Ecosystem

The Only Modernization Platform You'll Ever Need

From Insight to Execution. At Scale.

CHAI DART™

Provides deep, continuous intelligence across applications, workloads, and runtime behavior.

→

CHAI Universe™

Captures DART intelligence within broader context, turning insights into prioritized, enterprise-ready decisions.

→

CHAI Flow™

Ensures modernization is context-aware, measurable, and repeatable across the enterprise.

→

CHAI Compass™ NEW

Validates business value, ROI, and compliance posture at every step of the journey.

Ready to Transform?

Turn modernization from a project into a repeatable enterprise capability. Migrate Anything. Modernize Everything. Break Nothing.

Schedule a Demo → Explore on AWS Marketplace

CHAI by CloudHedge — Agent View

/products/universe/

# CHAI Universe — The Application Modernization Harness for the Enterprise

CHAI Universe is CloudHedge's unified harness that brings assessment, intelligence, learning, and execution together — transforming legacy systems at enterprise scale with Sovereign AI and advanced Reinforcement Learning.

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## Platform Architecture — CHAI Universe MCP
An intelligent control plane orchestrating every layer of your modernization journey:

### Orchestration Layer
- **CHAI Flow Engine** — Multi-agent collaboration turning modernization chaos into controlled, repeatable workflows
- **CHAI Recipes** — Enterprise-approved, governed modernization playbooks. Reusable blueprints for every use case.
- **Dynamic Context Engine** — App Graph Builder, Dependency Mapper, Knowledge Graph, and Hallucination Filter

### Tri-Vector Analyzer
- Workload Analyzer (Performance Profiling)
- Runtime Analyzer (Live Monitoring)
- Source Code Analyzer (Static Analysis)

### Intelligence Layer
- Unified Intelligence Engine
- CHAI Reinforcement Learning

## Six Pillars of Transformation
1. **Context Aware Modernization** — Tri-Vector assessment builds dynamic context, making transformation predictable
2. **Sovereign AI** — Intelligence stays within your organization with air-gapped deployment and zero data exfiltration
3. **Unified Intelligence** — Eliminates fragmented LLM usage with one cohesive AI layer across your entire SDLC
4. **CHAI Recipes** — Governed modernization playbooks for .NET, Java, VMware, DC exits and more
5. **Reinforcement Learning** — AI that continuously learns and improves from your environment
6. **Enterprise Scale** — Handles complex portfolios with governance and compliance (CMMC, IL6, HIPAA)

## How It Works
1. **Assess** — Tri-Vector analysis captures runtime, dependencies, and business context
2. **Plan** — AI-generated pathways aligned to your goals and constraints
3. **Execute** — Governed recipes automate transformation with guardrails
4. **Optimize** — Continuous learning refines pathways and reduces rework

## CHAI Compass (New)
Business Value Framework — Quantify value before you commit. ROI Modeler, Compliance Score, Goal Modeler, Regression Suite.

## Works for Brownfield and Greenfield
- **Brownfield Applications** — Modernize existing legacy systems with full context, safety, and institutional knowledge
- **Greenfield Applications** — Build AI-native, agentic applications from the ground up with governance, compliance, and self-healing

## Ecosystem Flow
CHAI DART (deep intelligence) -> CHAI Universe (enterprise-ready decisions) -> CHAI Flow (context-aware execution) -> CHAI Compass (business value validation)

## Availability
Available on AWS Marketplace.

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## Products
- CHAI Universe — AI-powered application discovery and portfolio intelligence: /products/universe/
- CHAI DART — Tri-Vector deep application assessment: /products/dart/
- CHAI Flow — Agentic orchestration for automated modernization: /products/flow/

## Contact
Schedule a demo: /contact/
Email: hello@cloudhedge.io