# RAG Systems for Ed-Tech

> RAG systems for Ed-Tech: a tutor and search layer grounded in your courseware, so answers cite the lesson instead of inventing them. Retrieval-augmented learning by Sentient Arc.

A tutor and search layer grounded in your own courseware, answers that cite the lesson, not the open internet.

## The challenge in Ed-Tech
Ed-Tech products that bolt on a general model get confidently wrong answers that contradict the course, undermine the instructor, and erode trust with learners and the institutions that buy. The value is not a model that knows everything. It is one that answers strictly from your curriculum, textbooks, and lesson content, and points the learner to where the answer lives so they can keep learning rather than copy a result.

## Example workflows

### Curriculum-grounded tutoring
- Ingest course materials, textbooks, lecture transcripts, and problem sets
- Chunk and embed by topic so concepts and worked examples stay retrievable
- Retrieve the relevant lesson passages for a learner question
- Answer only from the curriculum, citing the lesson or section it draws on
- Offer the source so the learner can read further instead of just taking the answer

### Instructor and content search
- Index the full content library across courses into one corpus
- Let instructors find existing explanations, examples, and assessments by meaning
- Surface gaps where a topic lacks coverage to support content planning

## Outcomes
- Learners get answers that match the course and cite the lesson, not the open web
- Instructors find and reuse existing explanations and assessments by meaning
- Responses stay inside your pedagogy, protecting trust with schools and learners
- New courses and editions enter the corpus without re-engineering retrieval

## FAQ
**How is a RAG tutor different from putting ChatGPT in our product?**

A general model answers from training data and contradicts your course. A RAG tutor answers only from your curriculum and cites the lesson, keeping responses aligned with how you actually teach.

**Does grounding in our content reduce wrong answers?**

Sharply. Constraining the model to retrieved curriculum passages and verifying citations before responding keeps answers anchored to your material instead of the model inventing them.

**Can it point learners to the source instead of just giving the answer?**

Yes. Each answer carries a citation to the lesson or section, so learners can read further and keep learning rather than copy a result with no context.

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Canonical page: https://www.sentientarc.com/solutions/rag-systems-for-edtech