AI Agent for Efficient Cost Allocation

Project Specification: AI Engineering Agent for Cost Estimate Allocation & Automated Document Parsing - A 95% to 98% degree of accuracy is needed for this project. - The Lump Sum (LS) valves must only be generated when the model has maximized all measured data resources and do not have an alternative Objective You will develop and integrate an autonomous AI Model Agent capable of eliminating unallocated cost data from construction project cost estimates. The current production model dumps unmeasured items into a "catch-all" section labeled "Found on the drawings, not measured (no quantity on the drawings, not priced)". Your agent must autonomously parse multi-discipline AutoCAD PDF drawing sets, interpret the project masterplan, classify scope by CSI MasterFormat Codes, segregate structural areas (Main Buildings, Site Improvements, Civil), and programmatically apply smart engineering assumptions or Lump Sum (LS) values when explicit quantities are missing. System Architecture & Workflow [Masterplan & AutoCAD PDFs] ──> [AI Agent Vision/Text Parser] ──> [CSI & Zone Classifier] │ [Zero unallocated items] Budget: USD 250–750