AI-Powered Federal Cost Estimation
Deploys an 8-agent autonomous system that processes project documents in parallel, extracts scope and quantities, queries historical databases, applies regional cost factors, identifies VE opportunities, assesses risks, and generates compliant federal cost estimates—reducing estimation time from weeks to minutes while improving accuracy through multi-source validation..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Project Configuration - Input wizard for defining project parameters, location, and uploading documents for AI-powered cost estimation.
Live AI Analysis - Real-time agent processing showing AI discoveries, market insights, and supply chain alerts with tool execution tracking.
Executive Summary - AI-generated cost report with total estimate, VE savings opportunities, contingency recommendations, and key findings.
AI Chat Assistant - Conversational interface for querying cost breakdowns, risk analysis, VE opportunities, and market conditions.
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Complex cost estimation requires coordinating multiple specialized analyses (parsing, historical lookup, estimation, risk) while ensuring consistent results and resolving conflicts between agent outputs.
Core Logic
Uses Claude 3 Opus (temperature 0.1, 4096 tokens) as central coordinator. Delegates tasks to specialized agents, aggregates results, resolves conflicts between estimates, and manages workflow progression. Tools: `delegate_task`, `aggregate_results`, `resolve_conflicts`. Maintains workflow state and ensures all agents complete before synthesis.
Document Parser Agent
Construction documents (specs, drawings, contracts) contain critical scope information scattered across hundreds of pages in various formats, requiring hours of manual extraction.
Core Logic
Uses Claude 3 Sonnet (temperature 0.0, 8192 tokens) for deterministic extraction. Parses PDF specifications, identifies CSI divisions and specified items, extracts quantities and key terms, determines project scope with confidence scoring. Tools: `parse_pdf`, `extract_scope`, `identify_csi`. Returns structured data for downstream agents.
Historical Analyst Agent
Cost estimates lack context without comparison to similar completed projects, making it difficult to validate accuracy or identify anomalies.
Core Logic
Uses Claude 3 Sonnet (temperature 0.2, 4096 tokens) with access to historical project database. Performs similarity analysis against past projects, detects cost patterns, calculates escalation factors, and identifies trend-based adjustments. Tools: `query_historical_db`, `calculate_similarity`, `apply_escalation`. Provides benchmark data and confidence intervals.
Cost Estimator Agent
Generating accurate line-item estimates requires querying multiple cost databases, applying regional factors, and calculating quantities—a time-consuming process prone to human error.
Core Logic
Uses Claude 3 Opus (temperature 0.1, 8192 tokens) as primary estimation engine. Queries RS Means/Gordian cost databases, calculates quantities from scope data, applies regional and temporal adjustment factors, generates division-level and line-item estimates with P10/P90 confidence intervals. Tools: `query_cost_db`, `calculate_quantity`, `apply_factors`.
Risk Analyst Agent
Project risks (market volatility, supply chain disruptions, labor shortages, regulatory changes) can significantly impact costs but are often identified too late for effective mitigation.
Core Logic
Uses Claude 3 Sonnet to analyze six risk categories: market, supply chain, labor, regulatory, technical, and schedule risks. Calculates probability and impact scores, computes risk-adjusted contingency amounts, identifies affected CSI divisions, and recommends mitigation strategies. Provides contingency allocation recommendations based on risk tolerance.
Value Engineering Agent
Identifying cost reduction opportunities while maintaining quality requires deep expertise and analysis of alternatives—often performed too late in the project lifecycle.
Core Logic
Uses Claude 3 Sonnet to identify VE opportunities by analyzing scope against alternatives. Evaluates each opportunity for savings potential, implementation complexity, schedule impact, and quality implications. Provides historical success rates from similar projects and ranks recommendations by risk-adjusted ROI. Outputs include proposed vs. current cost comparisons.
Compliance & Sustainability Agent
Federal projects must meet regulatory requirements and increasingly stringent sustainability goals (LEED, carbon targets), requiring specialized compliance verification.
Core Logic
Uses Claude 3 Sonnet to verify compliance with federal acquisition regulations and sustainability standards. Analyzes carbon footprint (Scope 1/2/3 emissions), evaluates LEED/Green certification readiness, calculates ESG metrics, and identifies green building credits available. Ensures estimates include costs for required compliance measures.
Market Intelligence Agent
Material and labor costs fluctuate with market conditions, and estimates based on static databases quickly become outdated, leading to budget overruns.
Core Logic
Uses Claude 3 Sonnet with real-time market data feeds. Tracks material pricing trends (steel, concrete, lumber), labor market conditions by region, weather risk integration, and regional demand patterns. Provides volatility indicators and price forecasts to adjust estimates for current market conditions and project timeline.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
5 technologies
Architecture Diagram
System flow visualization