TrustEvolveAI

Overview

Developed an AI-driven platform that evaluates trust metrics in business relationships using machine learning models and natural language processing.

The Problem

Businesses needed an automated way to assess and monitor trustworthiness of their partners and vendors without manual due diligence for every transaction.

The Solution

Built an AI pipeline that aggregates data from multiple sources, applies ML models for risk scoring, and provides actionable insights through an intuitive dashboard.

Architecture

Monolithic Laravel application with Python ML microservice, PostgreSQL database, Redis caching, and React dashboard.

Challenges

• Integrating multiple data sources with varying reliability
• Building explainable AI models for compliance requirements
• Optimizing ML inference for real-time scoring

Key Learnings

• Prompt engineering for structured data extraction
• Building hybrid AI systems combining rules and ML
• Data pipeline architecture for ML applications