AETHER AI — Multi-Model Intelligence Council

Capstone Project Title

AETHER AI: A Multi-Model Intelligence Council for Truth-Oriented AI Decision Making

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Project Idea

AETHER AI is a multi-agent artificial intelligence system designed to improve the quality, reliability, and trustworthiness of AI-generated outputs.

Instead of relying on a single AI model, AETHER AI creates a council of multiple AI models (such as ChatGPT, Gemini, Claude, Copilot, etc.). Each model independently receives the same task and generates its own solution. These solutions are then cross-verified, critiqued, and evaluated by other AI agents in a blind-review process.

A central decision-making agent, called the Aether Arbiter, analyzes all outputs and verification results to produce one final, optimized, and high-confidence solution.

The goal of AETHER AI is not just to generate answers, but to refine intelligence through collective reasoning, reducing hallucinations, bias, and single-model limitations.

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Key Objectives

• Build a multi-model AI orchestration system
• Enable blind cross-verification between AI agents
• Improve correctness, consistency, and reliability of AI outputs
• Demonstrate system design, architecture, and full-stack development skills
• Apply real-world AI governance and decision-making principles

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Tech Stack

• Frontend: Next.js, Tailwind CSS
• Backend: Python, FastAPI
• Architecture: Multi-agent orchestration system
• Version Control: Git & GitHub

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Capstone Day-by-Day Plan

Day 1 – Project Setup & Planning

• Create GitHub repository
• Define project idea and architecture
• Set up README and documentation
• Create initial project folder structure

Day 2 – Frontend Setup

• Initialize Next.js project with Tailwind CSS
• Create base layout (Topbar, Sidebar, Panels)
• Implement basic UI structure for dashboard

Day 3 – Backend Setup

• Set up FastAPI backend
• Create basic API endpoints
• Establish frontend–backend communication

Day 4 – Aether Council Implementation

• Define AI agent interfaces
• Simulate multiple AI model responses
• Standardize input/output formats

Day 5 – Verification & Arbiter Logic

• Implement cross-verification logic
• Add scoring and evaluation mechanisms
• Design Arbiter decision-making flow

Day 6 – Integration & Testing

• Integrate frontend with backend logic
• Test multi-agent workflows
• Fix bugs and edge cases

Day 7 – Documentation & Final Review

• Update documentation and diagrams
• Final testing and optimization
• Prepare project for capstone submission

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Expected Outcome

By the end of the capstone project, AETHER AI will demonstrate how collective intelligence from multiple AI models can be orchestrated to produce more reliable and high-quality results than any single model alone.

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Author

Naorem Nganthoiba Singh

Capstone Project — AETHER AI

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Capstone Submission Status: README setup completed.