System Architecture
CredAxis is a full-stack, Web3-enabled software platform designed to solve the critical issues of academic transcript fraud, slow verification times, and data siloing in international education.
1. The Decentralized Ledger (Smart Contracts)
The system operates on a Monorepo architecture. The decentralized ledger is written in Foundry (Solidity).
- TranscriptRegistry.sol: The immutable ledger mapping cryptographic hashes of student transcripts to university issuer addresses.
- UniversityFactory.sol: A factory pattern implementation allowing autonomous deployment of dedicated registry instances for participating universities.
- Security Paradigm: Implements strict Access Control Lists (ACL) ensuring only authorized Registrar wallets can mint and amend transcript records.
2. The Indexing & Caching Layer (Backend)
Due to the slow querying times of remote RPC blockchain nodes, the backend implements an Event Indexer built on Node.js, Express, Drizzle ORM, and PostgreSQL.
- Functionality: Listens to emitted events from TranscriptRegistry.sol (e.g., TranscriptIssued) and caches the metadata into a relational PostgreSQL database.
- API Services: Exposes REST endpoints to the frontend for lightning-fast querying, and handles side-effects such as automated email notifications.
3. The Client Interface (Frontend)
The frontend is a modern web app built with Next.js 16 App Router, React, and Tailwind CSS.
- Authentication: Role-Based Access Control (RBAC) securely differentiating UI views and permissions for Students, Registrars, Verifiers, and the Public.
- Registrar UX Abstraction (Hybrid State Architecture): Enables features like Cohort Invite Codes for mass student self-onboarding and OTP Fast-Track Approvals to bypass mandatory Web3 wallet transaction signing.
- Performance Engineering: Implements chunked asynchronous processing (`setTimeout` yielding) during intensive operations like CSV parsing to prevent Interaction to Next Paint (INP) browser freezing.
4. AI & Systems Integration (MCP)
CredAxis natively integrates with emerging AI research tools.
- Framework: Model Context Protocol (MCP) Server.
- Functionality: Exposes a Server-Sent Events (SSE) stream allowing authorized AI Agents to read real-time database metrics (e.g., Active Universities, Issued Transcripts).
SEO & Market Viability
To compete with established entities like WES, the platform injects JSON-LD EducationalApplication schemas directly into the HTML <head> and utilizes auto-generated sitemaps with rigorous hreflang alternates to prevent localized duplicate content penalties by Google crawlers.