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BBS Harness — AI Structural Drawing Analyzer

Ongoing1 developer

An auditable AI workflow that extracts bar-bending schedules from structural drawings while preserving source evidence and engineer review at the highest-risk stages.

Technologies Used

LangGraphTypeScriptPythonComputer VisionPostgreSQLLangSmith

The Challenge

Extracting a bar bending schedule from a structural drawing set is a full day of manual counting, and the output feeds straight into procurement and pouring. An error is expensive and effectively permanent. A naive OCR pass does not work: the values only make sense in the context of the region of the drawing they sit in.

The Solution

I built a multi-stage pipeline that starts with page overviews, detects regions with computer vision, then inspects detail and context crops. Every extracted value links back to its source, while typed review gates let engineers correct decomposition and classification without restarting a run.

Key Features

Multi-modal progressive inspection: low-res overview → CV region detection → detail + context crop extraction
Evidence linking: every extracted value traces back to its source page and region
Human-in-the-loop review gates at decomposition and classification, as typed interrupt boundaries — approve or edit without restarting the run
Durable Postgres-backed checkpointing for resumable, crash-tolerant orchestration
Token budget management with payload estimation and message pruning for large multi-page documents
Typed event contract (40+ event types) over SSE for live progress, with a full audit trail in Postgres

Impact & Results

In an internal evaluation across 40 drawing sets, reduced an approximately eight-hour workflow to under 30 minutes at 94% field-level accuracy while preserving engineer oversight.

My Role: AI Engineer

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