Adaptive Learning Platforms, Built for Real Classrooms
Learners don't struggle on the syllabus's schedule. We build platforms where content reorganises around what each learner actually gets wrong: semantic search that finds the gap, AI tutors that explain it, and assessments that prove it closed.
- Adaptive paths from real learner data
- Voice and multilingual AI tutors
- Built to survive exam-day traffic
Who we build for
- Publishers turning textbooks into adaptive, assessable digital courses.
- Coaching and test-prep companies that need practice engines and analytics at exam-season scale.
- Universities and skilling programmes delivering courses in several Indian languages.
- Corporate L&D teams that want training tied to measurable skills, not completion ticks.
- EdTech startups that have the pedagogy and the users but not the in-house AI and platform engineering.
What we build
Adaptive learning engine
Vector embeddings over your content and learner responses to recommend the next best item, so each learner's path adapts to their gaps.
AI tutors
Tutors grounded in your own material, with voice input and output, that explain rather than just give answers, and cite the lesson they draw from.
Assessments
Question banks, auto-graded assessments and item analytics, so you know which questions actually discriminate between learners.
Multilingual delivery
Content, search and tutoring across Indian languages, designed for learners who switch between languages mid-sentence.
Interactive content
Interactive 3D models and simulations for subjects where seeing beats reading, from geography to engineering.
Analytics for teachers
Dashboards that show teachers and administrators where a cohort is stuck, early enough to act on it.
Built for Indian conditions
Indian edtech traffic is spiky: a mock test or a results day can bring a month's load in an hour. We design for that peak from day one, with caching, queueing and load testing against your real calendar.
Many learners are on low-end Android phones and patchy mobile data. We keep pages light, make key flows work offline where it matters, and measure performance on the devices your learners actually use.
Learner data is personal data under India's DPDP Act. We minimise what is collected, keep it in-region, and can run AI models on infrastructure you control so student data never goes to a third-party API.
Proof
For an adaptive learning platform that needed better recommendations and safer releases, we tuned semantic retrieval, added production monitoring and introduced staged rollouts, so the team could improve the product without breaking it for learners. It is one of the case studies on this site.
Frequently asked questions
Do you build an LMS from scratch or integrate with ours?
Usually we integrate. If you already run Moodle, Canvas or a custom LMS, we add the adaptive engine, tutors and analytics as services alongside it. We only recommend a rebuild when the existing platform is the bottleneck.
Can the AI tutor support Indian languages?
Yes, with honest limits. Quality varies by language and subject, so we evaluate the tutor on your own content in each target language before launch and tell you where human review is still needed.
How do you keep an AI tutor from giving wrong answers?
The tutor answers from your vetted material with citations, refuses outside that scope, and is evaluated against a test set of real learner questions before every release.
Can the platform handle exam-day spikes?
We load-test against your expected peak, not an average day, and design caching and queueing so a results announcement doesn't take the platform down.
How is student data protected?
Data minimisation, encryption, role-based access and in-region hosting by default, aligned with the DPDP Act. For sensitive programmes we can run the AI models on your own infrastructure.
Tell us about your learners and your platform
Five fields. An engineer reads it and replies within one working day (IST), usually with a first opinion, not a sales pitch.