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AccessibilityAI & Research

Ada Remediation

2026 - Present

Ada Remediation is an AI-powered PDF accessibility remediation system I am building across a FastAPI backend, a Next.js 16 platform, and a marketing site. The workflow inspects PDF structure trees, renders pages for vision analysis, reports WCAG 2.1 AA and PDF/UA issues, lets reviewers accept, edit, or reject each proposed fix, then applies structured remediation with pikepdf to export cleaner, more accessible documents. Current work spans audit persistence, review UX, screen-reader checks, and productionizing the pipeline for real document workflows.

Key Highlights

Agent-First Audit Loop

Combines PDF structure inspection, page rendering, and model-driven issue reporting to find remediation work with document-level context instead of relying on a static checker alone.

Human Review Before Export

Every proposed fix can be accepted, rejected, or edited before export, preserving human control over heading structure, alt text, reading order, and artifact decisions.

Structured PDF/UA Export Pipeline

Applies exact fixes such as alt text, heading levels, structure types, metadata, document tags, and figure bounding boxes through a pikepdf-based export flow.

Full-Stack Remediation Product

Built across a FastAPI backend and a Next.js 16 plus React 19 frontend, with ongoing work on persistence and project-level audit management for production use.