Stop Fighting with Drawing PDFs: Get Clean BOMs in Minutes

If you build quotes, release builds, or manage PLM/ERP systems, you know the drill: getting a clean, trustworthy BOM from an engineering drawing should be simple—but it rarely is. Tables split across pages. Headers span multiple rows. Faint gridlines disappear. And somehow you always end up manually fixing the "automated" extraction.

Before File2BOM: Spend 2 hours manually transcribing a 50-line BOM, then another hour fixing errors when you realize the tool grabbed the revision history instead of the parts list.

After File2BOM: Upload the PDF, review the extracted table with a visual preview, export to your system—done in 5 minutes.

How It Works

File2BOM does one thing exceptionally well: it finds the actual BOM in your drawing and returns a clean, machine-readable table—with a clipped image of the source table so you can verify instantly.

1. Find the BOM tablesWe detect candidate tables across all pages, even when they're borderless or span multiple sheets. You can also specify regions if you know where your BOMs typically live.

2. Make everything machine-readableThe system enhances image quality automatically—reinforcing faint gridlines and upsampling resolution so small text and crowded cells stay legible. When fonts require it, OCR kicks in on individual cells (not entire pages) to capture the exact values.

3. Validate it's actually a BOMNot every table in a drawing is a BOM. We score headers for genuine BOM indicators ("Part #", "Qty", "Description"), merge multi-row headers, align columns properly, and verify part numbers. Revision logs, legends, and title blocks get filtered out automatically.

4. Return clean, import-ready dataYou get a normalized table with headers in the first row and consistent formatting. Missing values are forward-filled. And critically—you get a clipped image of the detected table alongside the data, so verification takes seconds, not minutes.

What Makes It Reliable

Most table detection tools work great on clean documents but struggle with engineering drawings. We built File2BOM specifically for the messy reality of manufacturing PDFs.

Here's why it works: AI finds the tables, engineering rules verify them. Neural networks are excellent at locating tables, but they can't always tell a BOM from a revision log when both look like tables. So we add domain-specific checks—header scoring, part number validation, structural analysis—to confirm we found the right table.

The visual audit trail is the final piece. You don't have to trust the algorithm—you can see exactly what it captured and verify it in seconds.

What You Get

Quoting & Sourcing Teams (Contract Manufacturers):A verified BOM you can immediately use for quote prep, vendor sourcing, and pricing—without arguing about whether the extraction missed rows or grabbed the wrong table.

Manufacturing & Sustaining Engineers (OEMs):An import-safe table with coherent headers, no spacer rows, and validated part numbers. Need to know the mating connector or required crimp tool? Ask follow-up questions grounded in actual datasheets, not AI guesses.

PLM/ERP Systems Owners:Consistent, scalable output that doesn't drift between runs. The visual audit trail satisfies reviews and compliance requirements. Formats that drop cleanly into your import pipelines.

What Clean BOMs Unlock

Once extraction is reliable, downstream automation becomes possible:

• Auto-sourcing: Match part numbers to multiple vendors, surface price breaks, compute total costs
• Inventory intelligence: Check what's on-hand, compare to last-paid costs, make buy-vs-use decisions
• Datasheet-powered answers: For wiring harnesses, automatically identify mating connectors and required crimp tools based on source documents

These workflows only work when the starting data is trustworthy. That's the problem File2BOM solves.

The Reality Check

Here's the honest truth: perfect automation doesn't exist. What separates enterprise-grade tools from "mostly works" tools is what happens when edge cases appear.

Engineering drawings are uniquely challenging—dense callouts, borderless cells, odd fonts, inconsistent layouts. Tools built for research papers or invoices struggle here. That's why File2BOM layers multiple approaches: if the primary detection method misses something, backup strategies catch it. If text extraction hits unusual fonts, OCR fills the gaps. If a table looks ambiguous, validation rules confirm it's actually a BOM.

And when you need to verify? The clipped table image lets you reconcile any value instantly. No digging through the original PDF.

Who It's For

File2BOM is built for teams that:

• Process customer drawings for quotes (contract manufacturers)
• Release builds from engineering PDFs (OEMs)
• Maintain PLM/ERP data pipelines (systems integrators)
• Need defensible, auditable extraction (regulated industries)

If "close enough" isn't good enough for your operation, this is the tool.

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