Portfolio  /  Case study
Case Study · AI/ML Applications

IELTS Speaking Evaluator

Examiner-style questions and answer scoring grounded in a reference question bank with vector RAG

AI/ML Applications Education & language assessment
IELTS Speaking Evaluator project by Dilijent Systems
The Client

IELTS Speaking Evaluator is a Dilijent Systems applied-AI engineering project that pairs examiner-style questions with scoring grounded in a reference question bank.

The challenge

Speaking practice needs an examiner: someone to ask realistic questions and then judge the answer. Judgement is the hard part. Without a reference standard, feedback drifts, and generic AI feedback cannot tell a candidate how their answer compares with what the syllabus actually rewards.

Our solution

  • Specialised IBM Watson agents generate examiner-style questions and score candidate answers against reference examples
  • True vector RAG: LangChain with MongoDB Vector Search retrieves the most relevant sample questions and model answers
  • Scoring is grounded against retrieved reference exemplars from the question bank, not against free-form model judgement
  • The same retrieval layer selects the question and supplies the standard the answer is marked against, so practice and marking stay consistent

The result

Candidates get examiner-style questions and a score tied to real reference answers retrieved from the question bank, so each score can be traced back to the standard it was measured against.

— Contact Us —

Let’s talk about your business

Tell us what you need help with and our team will get back to you.

Send us a message

Fields marked * are required.

Your information is kept private.