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Case study

PhaseForge

Co-developing the material-ingestion and question-family/verification backend for an AI assessment platform that turns instructor course materials into grounded, exam-ready questions with answer keys.

Contribution
Co-developing the FastAPI material-ingestion and question-family/verification backend.

Context

The problem

Turn instructor course PDFs into grounded, exam-ready questions with answer keys.

System

Architecture

  • Course PDF parsing
  • Embeddings and semantic retrieval
  • PostgreSQL with pgvector
  • FastAPI backend
  • Pydantic schemas and structured LLM outputs

Engineering judgment

Technical decisions

Index course content for semantic retrieval

The ingestion pipeline parses course PDFs, generates embeddings, and indexes content in PostgreSQL/pgvector.

Use reusable question-family templates

The workflow converts generated questions into reusable templates and instantiates student-specific variants.

Validate generated outputs

The verification service checks answer correctness, concept consistency, and source provenance through typed Pydantic schemas and structured LLM outputs.

Result

Outcome

Contributed ingestion, reusable question-family, and verification capabilities to the co-developed assessment platform.