AI-Powered Industrial Design Similarity Search
Enforcement · Planning & Decision-making
What it collects
- Industrial design images and registration data from collective databases of 80 international intellectual property offices worldwide, containing existing design applications and registrations. No personal information is involved.
- Newly-filed industrial design applications submitted to ISED Canada, including the design images and associated metadata for examination. These are official records of design applications, not personal data.
- Run by
- Innovation, Science and Economic Development Canada (ISED)
- Where
- No fixed location
- Kept
- Not stated by the Helpful Places.
- Shared with
- Accountable organization
- Your copy
- You cannot see the data it holds about you. What you can do
What it is for
DesignVision is an AI system used by Government of Canada employees at Innovation, Science and Economic Development Canada to search tens of millions of industrial design applications and registrations from 80 international intellectual property offices in seconds, comparing newly-filed designs against existing ones. It uses computer vision and deep learning to rank similar designs and flag potential conflicts, replacing manual visual inspection. The system does not involve personal information. Applicants and the public are informed that AI is used in the examination process.
What it collects and what happens to it
Data taken in
- Industrial design images and registration data from collective databases of 80 international intellectual property offices worldwide, containing existing design applications and registrations. No personal information is involved.
- Newly-filed industrial design applications submitted to ISED Canada, including the design images and associated metadata for examination. These are official records of design applications, not personal data.
Processing
- Computer vision and image recognition software analyzes visual features of industrial design images to detect patterns and measure visual similarity across tens of millions of design records worldwide.
- Deep learning algorithm classifies and ranks existing designs by similarity score relative to a newly-filed design, enabling pattern detection across the global design corpus in seconds.
What it does
- Computer vision and image recognition software senses and structures visual features from design images, converting raw image inputs into structured detections and similarity vectors for downstream ranking. Human examiners make final decisions on design registrations.
- Deep learning algorithm ranks and scores design similarity across tens of millions of existing applications and registrations worldwide, producing a ranked list of potentially conflicting designs for human examiner review.
Outputs
- A ranked list of existing industrial design registrations and applications that are visually similar to a newly-filed design, surfaced for review by human design examiners. The system advises; GC examiners decide.
Run by
- Federal department responsible for deploying and operating DesignVision for the examination of industrial design applications.
Built by
- Vendor that built and supplies the DesignVision computer vision and image recognition system used for industrial design similarity search.
Kept for
Not stated by the Helpful Places.
Shared with
- Similarity search results and ranked outputs are available to GC employees (design examiners) at ISED Canada for use in the examination process.
- As a design applicant or member of the public, you do not have direct access to the AI similarity search results generated during the examination of your application.
Stored
Not stated by the Helpful Places.
How to read the colours
Can it identify you?
- Anonymized data
- Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
- Pseudonymous data
- Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
- Identifiable data
- The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.
Who completes the loop?
- Human decides
- This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
- Human executes
- This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
- Autonomous
- This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.
Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.
- AI registerGovernment of Canada Algorithmic Impact Assessment Register — DesignVision (2526-ISED-ISDE-006)Innovation, Science and Economic Development Canada. AI Register entry 2526-ISED-ISDE-006.
- AI registerGC AI Register — DesignVision
- AI registerGC AI Register — DesignVision
- Register entryPublished by the Helpful Places. Reference 58d7e05d. This disclosure was drafted with AI assistance.Schema: ai@2026-05-06-beta
What you can do
Ask about this system
Questions go to the Helpful Places, not the vendor.
Your rights
- Right to Algorithmic TransparencyThe Government of Canada discloses that AI is used in the examination of industrial design applications. This is indicated in the GC AI Register, which is publicly accessible. Applicants are informed that AI use is disclosed to users.
- Right to a Human ReviewHuman examiners at ISED Canada make all final decisions on industrial design registration. The AI system provides ranked similarity results to support, not replace, human judgment. Applicants may engage with the examination process through standard ISED procedures.
Risks and safeguards
No risks or safeguards have been published for this system yet.