Automated Trademark Image Matching and Design Code Assignment

UseCase Description:

This solution assists trademark examiners by comparing new trademark images against a database of registered images. It identifies similar images, suggests the correct design codes, and evaluates the appropriateness of goods and services identifications. The system improves accuracy and consistency while reducing manual workload and processing time.

Various publicly available sources and LLMs were used to gather these use cases. They are meant to initiate talks and give you a starting point for further refinement to meet your requirements.

Business Challenges

  • Examiners spend significant time matching incoming images to registered trademark images.
  • Manual classification leads to inconsistencies in design code assignments.
  • Current systems struggle with accurate identification of similar trademark images.
  • Incorrect or inconsistent mapping affects the determination of goods and services acceptability.
  • High manual workload increases processing time and operating costs.

AI Solution Description

  • The system processes trademark images using a multi-modal model that combines visual and text analysis.
  • Incoming images are pre-processed and visual features are extracted using a computer vision component.
  • A large language model analyzes accompanying text, including design code descriptions and goods/services information.
  • Visual features and text embeddings are compared against a database of registered trademark images.
  • The system retrieves similar images and suggests the most appropriate design codes.
  • The model provides an evaluation of goods and services alignment to support examiner decisions.
  • Examiner feedback is used to refine the model continuously, ensuring improved accuracy over time

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Expected Impact / Business Outcome

 

Revenue

  • Improved accuracy in trademark processing may boost filing confidence and increase revenue.
  • Faster and more reliable classifications may attract more trademark applications.

User Experience

  • Examiners receive clear, consistent recommendations that reduce manual effort.
  • The system streamlines decision-making, making the review process smoother.
  • Better support improves examiner satisfaction and trust in the process.

Operations

  • Automation reduces the time spent on manual image comparison and code assignment.
  • The system ensures uniformity in the evaluation of trademark images.
  • Operational efficiency improves with fewer errors and rework.

Process

  • The process becomes more efficient with automated image matching and code suggestion.
  • Real-time output supports faster and more consistent decision-making.
  • The approach enhances quality control throughout the trademark evaluation process.

Cost

  • Reduced manual labor lowers overall operating costs.
  • Automation minimizes errors, cutting the cost of corrections and appeals.
  • Improved efficiency accelerates processing times, saving additional resources.

Required Data Sources:

  1. Incoming trademark images submitted for evaluation.
  2. A comprehensive database of registered trademark images.
  3. Associated design codes linked to registered images.
  4. Text descriptions of goods and services for each trademark.
  5. Historical examiner feedback on classification decisions.
strategic-fit-and-planning

Strategic Fit and Impact

  • The solution fits strategically by addressing key operational challenges with high impact.
  • Automation and improved accuracy will drive down costs and enhance user satisfaction.
  • The approach supports core business goals in revenue growth, operational efficiency, and process quality.
  • The strategic fit is high, given the potential to streamline critical processes and improve decision consistency.