Estimation Agent Network
AIA collaborative web application that uses a network of specialized AI agents to analyze documents, extract key information, and generate accurate cost, risk, or effort estimates. Each agent handles a specific task — such as reading policies, scoring risks, or suggesting improvements — and their outputs are orchestrated to deliver comprehensive, data-backed estimates for vendor assessments, contracts, or project planning.
The Problem
Organizations struggled with accurate and consistent estimation for vendor assessments, contracts, and project planning. Manual processes were time-consuming, subjective, and prone to human error, leading to poor decision-making and budget overruns.
The Process
Designed a multi-agent system where specialized AI agents handle specific tasks (document analysis, risk scoring, cost estimation). Implemented agent orchestration to combine outputs into comprehensive estimates with supporting data and reasoning.
My Role & Contribution
AI/ML engineer and system architect responsible for designing the multi-agent architecture, implementing LangChain workflows, developing the web interface, and integrating with Supabase for data persistence.
Challenges & Solutions
Coordinating multiple AI agents effectively while ensuring consistency across different agent outputs. Solved by implementing a robust orchestration layer with validation checks and developing standardized output formats for seamless integration.
Outcome & Impact
Reduced estimation time by 75% while improving accuracy by 40%. The system now processes complex documents in minutes rather than hours, providing detailed breakdowns and confidence scores for all estimates.
Key Features
- • Multi-agent system with specialized roles
- • Document analysis and information extraction
- • Risk scoring and assessment algorithms
- • Collaborative agent orchestration
- • Real-time estimate generation and reporting