Government · US state permitting departments

Object recognition for government permitting workflows

Neural networks and knowledge graphs that read construction drawings, apply 3D regulatory rules, and catch compliance issues before submission.

How it works

4 steps, from input to result

01
Construction drawing in
The applicant's drawings arrive as flat PDF submissions.
02
Identify objects
Neural networks find and categorise the objects within each drawing.
03
Apply the rules
A knowledge graph and evolving data dictionary match against current regulations.
04
Flag before submission
Automated review with self-correcting markup catches issues upfront.

Identifying and validating objects inside construction drawings was slow and manual.
Complex 3D regulatory rules had to be applied to flat PDF submissions.
Applicants resubmitted repeatedly because compliance problems surfaced late.

Neural networks and knowledge graphs that identify and categorise objects within drawings.
A dynamic, evolving data dictionary used for pattern matching as rules change.
Automated review with self-correcting markup, so issues are flagged before submission.

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Tell us the workflow and the constraints it runs under. We will tell you whether it is worth building.