Education · Generative AI & RAG
The handbook, answerable at 2am.
Retrieval over handbooks, course material and policy documents, answering with citations in the student's language — and saying so when the answer isn't there.
- Retrieval pipelines
- Fine-tuned domain models
- Multimodal (text · image · voice)
- Eval + guardrails
What we build
Generative AI & RAG for education, specifically.
- 01
Policy and administrative answers
Attendance, extensions, fees and grading answered from the current handbook with the section cited, at the hours students actually ask.
- 02
Course material Q&A
Scoped to a module's own readings and lectures, so answers reflect what was taught rather than the internet's average view of the topic.
- 03
Programme and eligibility guidance
Prospective students get accurate entry-requirement answers with the source, instead of a prospectus PDF and a contact form.
What we measure
- Accuracy on a staff-graded question set
- Share of enquiries resolved without a staff touch
- Out-of-hours resolution rate
- Answer quality across supported languages
Instrumented in week one and reported weekly. These are the numbers the engagement is judged on — not a forecast of what they'll be.
Constraints
What has to be true in education.
- 01
Academic help is Socratic by design
For coursework, the system asks and hints rather than answering, and hands off to a human when a student is genuinely stuck. Building the answer-machine version is easy and actively harmful to the institution buying it.
- 02
Minors change the data rules
Under-18 cohorts bring stricter consent, retention and moderation obligations under DPDP, GDPR and COPPA-equivalent regimes. That shapes the architecture, not just the privacy notice.
- 03
An educator reviews anything assessed
Generated assessment content and feedback drafts go to an educator before a student sees them. Grading with consequences stays human.
How it runs
The Generative AI & RAG engagement, step by step.
- 1
Data inventory
What docs / databases / APIs / feeds matter? What's PII vs public? What changes daily vs quarterly? We map it before writing code.
- 2
Retrieval architecture
Hybrid (BM25 + vector) retrieval, chunking strategy, reranking, citations. Tuned for your domain not a generic benchmark.
- 3
Eval suite
Real-world question set with golden answers. Faithfulness, context precision, latency. So you know when changes ship a regression.
- 4
Guardrails
Prompt-injection defense, PII scrubbing, refusal patterns, output schemas. Especially critical for customer-facing deployments.
- 5
Production + iterate
Cost-effective inference (caching, fallback models), monitoring, weekly eval reports. Fine-tune when the data justifies it.
Integrations
Systems we wire into for education.
- Moodle & Canvas
- Google Classroom
- Student information systems
- Salesforce Education Cloud
- Twilio & WhatsApp Business
- Zoom & Google Meet
- Payment gateways for fee collection
FAQ
RAG for course material and student support: your questions.
How do we stop it answering assessment questions?
Assessment content is excluded from the index, and coursework-shaped queries route to the Socratic mode rather than the retrieval answer. Both behaviours are scored in the eval suite so a model change can't quietly relax them.
Our policies change every year. How do we keep it current?
Version-aware indexing keyed to the academic year, with the cohort's year as a retrieval filter — a returning student's rules and a fresher's are not the same document.
Should I use RAG or fine-tuning?
RAG for facts that change. Fine-tuning for style, format, or domain reasoning. Most production systems use both — and we'll tell you which mix is right after a 1-week discovery.
Can I use my own LLM (open-weights)?
Yes. We work with Llama, Mistral, Qwen, and similar — useful for data residency, cost predictability, and air-gapped environments.
Contact
Talk to us about generative ai & rag for education.
Two or three sentences about the workflow you'd start with. We reply within one business day.
Or skip the form — book a Calendly slot directlyadmin@neuroxai.com · +91 70149 99768
Remote-first team across India · US · EU · HQ in Udaipur, India
More for Education
Other work we do in this vertical.
- AI agents for admissions and student servicesAgents that qualify applicants, chase documents, answer eligibility questions and book counselling calls across WhatsApp, voice and email.Read
- EdTech prototype to productionAuth, roles, data protection for minors, and load behaviour added to an edtech prototype before an institution's procurement team asks about any of it.Read
Same service, other industries
Generative AI & RAG elsewhere.
- RAG for banking and financial servicesRetrieval over circulars, product terms and internal procedure — returning the clause, the revision date, and a link to the page it came from.Read
- RAG for healthcare and clinical documentsRetrieval over clinical guidelines, payer policy and internal SOPs — with the citation, the version, and an explicit refusal when the library doesn't cover the question.Read
- AI product search and catalogue RAGSemantic search and grounded product Q&A over your catalogue, reviews and size guides — with stock and price read live rather than remembered.Read