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AI Tutor & RAG Learning Assistant

Answers grounded in your own course content

An AI tutor that answers learner questions from your own course content, so learners stay unblocked and your team stops repeating itself.

See Pragyanta, our live learning platform — built by the same team behind seven production platforms →
AI Tutor & RAG Learning Assistant — SADigisoft

Service at a glance

LMSLearning delivery
SCORMStandards support
AITutor options
CloudHosting & operations

What we build into your AI tutor

AI Tutor & RAG Learning Assistant

Learners ask the same questions over and over, usually after hours when no one is available to answer. An AI tutor gives them reliable, instant answers drawn from your own course material — so they stay unblocked and your team stops repeating itself.

What we build

  • A retrieval-augmented (RAG) assistant grounded in your courses, documents and slides.
  • Answers that stay within your material rather than guessing.
  • A chat experience embedded in your LMS or course site.
  • Controls over scope, tone and the content the tutor is allowed to use.
  • A practical stack — FastAPI, OpenAI and a Postgres/pgvector knowledge base.

This helps coaching institutes and course creators support large cohorts without scaling support staff, and helps corporate training teams answer policy and compliance questions consistently. Because the tutor only draws on the content you give it, answers stay on-message.

We have built and tested these flows on Pragyanta, our in-house learning platform, so this is a demonstrated capability rather than a slide. An AI tutor works best as part of a full custom LMS, and pairs well with a quiz and assessment platform so learners can check understanding straight after asking.

We work within your licensed or open-source learning environment and keep your content yours. How we work: we start with a contained pilot on one course, watch how learners use it, then expand the scope and the content it can draw on.

Questions we are usually asked

Will it make things up? The tutor answers from the material you give it and is scoped to stay inside it. Where it has no grounding for an answer it says so rather than guessing — which is the difference between a novelty and something you can put in front of compliance content.

Is our content used to train someone else's model? No. Your material stays yours and is used to answer your learners' questions.

Do we need a full LMS first? No. A tutor can sit on an existing course site or platform, though it becomes more useful when it can see where a learner has got to.

Want to add an AI tutor to your learning platform? Book a free consultation and we will scope a demo against your own content.

Grounded answers, not a general chatbot

A general-purpose AI assistant will confidently answer questions your course material never covered, which is exactly the failure mode that makes learners distrust the whole system. We scope the tutor's knowledge to what you actually give it — your courses, documents and slides — and it says so when a question falls outside that material, rather than inventing a plausible-sounding answer from general training data.

Questions we get asked

Can the AI tutor answer questions outside our course content?

By design it stays within the content you give it, and is instructed to say so when a question falls outside that material rather than guessing from general knowledge.

How do we control what the tutor is allowed to discuss?

Scope, tone and the content the tutor can use are all configurable — you decide what it's grounded in, and can restrict or expand that as your material grows.

Does this replace instructors or support staff?

No — it handles the repetitive, after-hours questions instructors and support staff would otherwise answer the same way many times, freeing their time for the questions that actually need a person.

What's the technical stack behind this?

FastAPI, OpenAI and a Postgres/pgvector knowledge base — the same retrieval-augmented approach we use across our AI work, proven on our own AI-tutor demo inside Pragyanta.

How We Deliver

01

Discovery

We map your goals, audience, learner journeys, and technical requirements before writing a single line of code.

02

Solution Design

We define course flow, learner roles, content structure, reporting requirements, and platform boundaries before build work accelerates.

03

Development

Sprint-based build with progress updates, code reviews, and continuous testing.

04

Launch & Improve

Go-live support, reporting, operational handover, and iteration once real learners begin using the system.

Need help shaping this service into a real LMS plan?

Connect with us to discuss scope, learner journeys, migration needs, integrations, and the right delivery path for your training use case.

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