Project 04 of 13

GPU OCR Gateway & Video → VQA Pipelines

One visual-data initiative, with two pipelines that stay separate.

  • Ongoing
  • OCR gateway: prototype, not deployed
  • VQA: used in assessments
Read the case study

The problem

An existing GPU OCR service needed a controlled front door. Separately, video annotations needed to become structured question data that people can review.

What I did

  • Designed the OCR gateway and reviewed its agent-assisted implementation: authenticated requests, encrypted storage, lease-aware jobs and audit records.
  • Converted video annotations into typed facts, review workbooks and multiple-choice question exports.
  • Kept question generation tied to structured facts. The VQA exports were imported into the assessment platform in project 05.

Decisions

  1. Two pipelines, no dependency

    OCR and VQA share an initiative, not a runtime.

  2. Wrap, don’t rebuild

    The gateway adds access control, job handling and audit around an existing OCR service.

  3. Questions come from facts

    Generation is tied to typed facts a person can check in a workbook.

Boundaries

Service integration and data preparation around existing models; no OCR model was trained. The OCR gateway is an undeployed prototype.

Synthetic demo · fictional data