AI-Assisted Trademark Pre-Assessment for Applicants

Enforcement · Planning & Decision-making

What it collects

Operational data

Anonymized data

Internal trademark application data, including goods and services descriptions submitted by applicants in new trademark applications and in unclassed registered trademarks approaching renewal.

About a measurement

Anonymized data

The Canadian Intellectual Property Office Goods and Services Manual, which provides the reference vocabulary and structure used to validate and classify goods and services descriptions against Nice classes.

Run by: Innovation, Science and Economic Development Canada (ISED)
Where: No fixed location
Kept: Retained as required by Government of Canada records management policy
Shared with: Accountable organization
Your copy: You cannot see the data it holds about you. What you can do

What it is for

Enforcement

Planning & Decision-making

This system uses artificial intelligence to automatically analyze goods and services descriptions in new trademark applications, identifying potential deficiencies before a human examiner reviews the file. It also suggests appropriate Nice classification classes for unclassed registered trademarks approaching renewal. When issues are detected, the Canadian Intellectual Property Office sends a pre-assessment letter to the applicant explaining what needs to be corrected. The use of AI in this process is disclosed to applicants.

What it collects and what happens to it

Data taken in

Operational data

Anonymized data

Internal trademark application data, including goods and services descriptions submitted by applicants in new trademark applications and in unclassed registered trademarks approaching renewal.

About a measurement

Anonymized data

The Canadian Intellectual Property Office Goods and Services Manual, which provides the reference vocabulary and structure used to validate and classify goods and services descriptions against Nice classes.

Processing

Language Models

Natural language processing is used to analyze free-text goods and services descriptions in trademark applications, interpreting and matching them against the Nice classification system.

Classification & Prediction

A classification algorithm matches goods and services descriptions to Nice classes and flags potential deficiencies or issues for communication to applicants via pre-assessment letters.

What it does

Deciding (Analytical AI)

Human decides

The system classifies and scores goods and services descriptions against Nice classes, producing deficiency flags and class suggestions. Human trademark examiners retain decision-making authority over the final examination outcome.

Creating (Generative AI)

Human decides

The system generates pre-assessment letters containing recommendations and guidance for trademark applicants, producing new text content based on the detected deficiencies and suggested Nice classes.

Outputs

Generated content

Anonymized data

Pre-assessment letters generated by the system and issued by CIPO to trademark applicants. These letters describe detected deficiencies or issues and provide recommendations, including suggested Nice classes for unclassed trademarks.

A recommendation or prediction

Anonymized data

Suggested acceptable Nice classification classes for unclassed registered trademarks prior to renewal, and recommendations on how applicants can address identified deficiencies in their goods and services descriptions.

Run by

Innovation, Science and Economic Development Canada (ISED)

The Canadian Intellectual Property Office (CIPO), a branch of Innovation, Science and Economic Development Canada, deploys this AI system to issue pre-assessment letters to trademark applicants and to suggest Nice classes for unclassed registered trademarks prior to renewal.

Government of Canada AI Register — 2526-ISED-ISDE-001

Built by

Onscope

Onscope is the vendor that built and supplies the Onscope Search System, including its AI-enabled components used by CIPO for trademark pre-assessment.

Government of Canada AI Register — 2526-ISED-ISDE-001

Kept for

Retained as required by Government of Canada records management policy

Trademark application data and generated pre-assessment letters are retained in accordance with Government of Canada records management requirements. The register does not specify a precise retention period.
Duration: as required by Government of Canada records management policy

Shared with

Not available to me

The AI system's internal analysis and scoring of trademark applications is not directly accessible to individual applicants. Applicants receive only the resulting pre-assessment letter; the underlying AI outputs are not exposed.

Available to the accountable organization

CIPO and Innovation, Science and Economic Development Canada have access to the AI system's outputs and the generated pre-assessment letters as part of the trademark examination process.

Stored

Stored locally

As a Government of Canada system operated by CIPO, data is stored within Canadian jurisdiction in accordance with federal information management requirements.
Duration: as required by Government of Canada records management policy

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.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

Right to Algorithmic TransparencyThe Canadian Intellectual Property Office discloses the use of AI in the pre-assessment process to applicants. Applicants who receive a pre-assessment letter are informed that AI was used to generate the analysis and recommendations contained in the letter.
Right to Be Informed of AI UseApplicants are notified of AI use when they receive a pre-assessment letter from the Canadian Intellectual Property Office. The register confirms that AI use is disclosed to users.

Risks and safeguards

Civil liberties harmAutomated pre-assessment letters may incorrectly flag compliant applications, placing unfair burden on applicants.Safeguard: Letters are advisory in nature and precede formal human examination; applicants are informed of AI use and given guidance on how to address identified issues. Human examiners make all final decisions.
Reputational harmErroneous classification suggestions or deficiency flags could mislead applicants and delay legitimate trademark registrations, potentially harming business interests.Safeguard: Pre-assessment letters are framed as advisory, AI involvement is disclosed, and applicants can proceed through normal examination channels where human review applies.