Detect callouts
Find number labels, reference markers, and hotspots on schematic images.
Auto-number detection and matching
Faster parts catalog creation with AI-assisted matching.
PartGrid detects schematic callouts, reads reference numbers, and matches them to parts data where possible, so your team can review exceptions instead of linking every part manually.
Detect schematic callouts
Read reference numbers
Match against parts data where possible
AI-assisted first pass
Schematic references become reviewable data
12
13
14
15
4 callouts detected
Reference numbers stored as schematic data
Link review
Review what matched before publishing
Matched references
42
Hotspots without BOM rows
5
BOM rows without hotspots
3
Needs manual correction
2
Next action
Confirm uncertain references, correct missing links, then publish the interactive catalog.
Manual work problem
Manual schematic linking does not scale.
Turning diagrams into interactive catalogs often means manually finding every callout, reading every reference number, and matching each one to a parts list or BOM row. That can work for a few diagrams. It becomes expensive and error-prone across hundreds or thousands of schematics.
Find every callout on every diagram.
Read and enter every reference number.
Match references against BOM rows or parts lists.
Create links between schematic positions and part records.
Review large batches before publishing.
Correct mistakes caused by manual data entry.
AI-assisted first pass
Let AI handle the first pass.
Instead of starting from an empty diagram, your team starts from a structured draft that can be reviewed, corrected, and published.
1
Detect
2
Read
3
Match
4
Review
5
Publish
Structured catalog data
From visual references to usable catalog data.
PartGrid does more than find numbers visually. Detected references become editable schematic data that can be compared with BOM rows and connected to existing part records where possible.
Read references
Extract reference numbers from detected callouts and normalize them for matching.
Match parts data
Compare detected references with BOM rows and existing part records where the source data supports it.
Prepare for review
Surface matched, missing, duplicate, and uncertain results before publishing.
Review first
Built for review, not blind automation.
PartGrid does not hide uncertainty. Review screens help teams see which references matched, which BOM rows are missing hotspots, which hotspots do not have matching BOM rows, and where manual correction is needed.
AI accelerates catalog creation. Your team controls the final result.
AI-assisted first pass
Schematic references become reviewable data
12
13
14
15
4 callouts detected
Reference numbers stored as schematic data
Link review
Review what matched before publishing
Matched references
42
Hotspots without BOM rows
5
BOM rows without hotspots
3
Needs manual correction
2
Next action
Confirm uncertain references, correct missing links, then publish the interactive catalog.
Existing inputs
Use the documentation and parts data you already have.
PartGrid is designed for real-world catalog modernization projects where diagrams, manuals, BOMs, spreadsheets, and part records often come from different systems. The better the source data, the more PartGrid can assist with detection and matching.
Schematic images
Exploded views
PDF manuals
BOM tables
CSV or spreadsheet parts lists
Existing part records
Why it matters
Spend less time linking. More time publishing.
Auto number detection and matching helps teams move from manual catalog creation toward a repeatable review workflow for customers, dealers, and service teams.
Create catalogs faster
Reduce the manual work required to prepare interactive diagrams.
Improve consistency
Store diagram references as structured catalog data instead of loose annotations.
Reduce manual errors
Review exceptions instead of retyping every reference from scratch.
Scale modernization
Process larger documentation sets with a repeatable review workflow.
FAQ
Auto-number detection questions.
How accurate is the automatic detection?+
Accuracy depends on source image quality, diagram style, callout design, and the selected model. PartGrid is designed to accelerate the first pass and provide review tools before publishing.
Does PartGrid automatically create a finished catalog?+
No. PartGrid can detect callouts, read reference numbers, and match them to available data where possible. The final catalog should still be reviewed before it goes live.
What happens if the system cannot read a number?+
Uncertain or missing results can be reviewed and corrected manually. The goal is to reduce manual work, not remove the review process entirely.
Can PartGrid match detected numbers to parts automatically?+
Yes, where matching BOM rows and existing part records are available. If source data is incomplete or inconsistent, PartGrid surfaces those cases for review.
Does PartGrid create missing parts automatically?+
Detection and matching do not need to invent parts. Missing parts or unmatched references should be handled through the appropriate product or catalog workflow.
Can PartGrid process PDF manuals?+
PartGrid supports workflows where manual pages and BOM data can be reviewed and promoted into structured schematics. Results depend on the quality and structure of the source manual.
Can models be tuned for our diagram style?+
Model-based detection workflows can be scoped for specific diagram styles and enterprise requirements. Custom tuning should be discussed as part of implementation planning.
Ready to turn diagrams into structured parts catalogs?
Use PartGrid to detect schematic references, match parts data where possible, and review exceptions before publishing.