For colleges & universities
Teach AI without a GPU budget
NEP 2020, AICTE curricula, and the IndiaAI Mission ask institutions to teach AI at national scale — while GPU and cloud budgets stay tight. NIKITRIA's planned education offering runs curriculum-specific models offline, on the computer labs you already have.
Education vertical
Curriculum-specific AI for India's classrooms — offline and affordable
Indian institutions are being asked to teach AI at national scale on constrained budgets. NIKITRIA's planned education offering pairs curriculum-specific SLMs with hardware schools already own: no GPU cluster, no per-student cloud bill, and it works with no internet at all.
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Curriculum-specific experts
Planned: specialist models aligned to specific syllabi and courses, for student practice and faculty support.
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Runs on existing computer labs
The same local-first runtime shown in our prototype — designed for modest, consumer-grade hardware rather than GPU clusters.
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Offline by design
Connectivity gaps stop being a blocker: everything runs on the machine in the room.
NEP 2020 emphasizes AI-integrated, personalized learning. CBSE offers a 15-hour AI module from Class VI and AI as an elective in Classes IX–XII; NCERT has embedded AI content in Class XI CS/IP textbooks; AICTE published a model AI & Data Science curriculum (2021) and runs faculty development programs. — NEP 2020; CBSE; NCERT; AICTE
The IndiaAI Mission (₹10,371.92 crore approved March 2024, seven pillars including FutureSkills) aims to expand AI courses across UG, PG, and PhD programs. — IndiaAI Mission, Mar 2024
The honest read on the tailwind
As of Feb 2026, only ~₹400 crore of the IndiaAI Mission's ₹10,372 crore outlay had been released, and the FY2026-27 allocation was cut roughly in half. Institutional GPU and compute budgets are genuinely constrained — which strengthens, not weakens, the case for low-cost, offline SLM deployments. — Budget reporting, Feb 2026
Prototype demo
Watch the prototype run
Orchestrator v0, running entirely on an 8GB Apple M1 Mac: a question routed across a panel of specialist experts and synthesized into one answer, with per-expert provenance, relevance scores, and real, unedited timings — no cloud in the loop.
Short public preview shown here; a full walkthrough is available to investors and design partners on request.
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The 45-second silent screen recording shows Orchestrator v0 receiving a question, routing it across specialist experts, and returning a synthesized answer with per-expert provenance and unedited stage timings — all running locally on the machine. A downloadable copy is available on request via the contact page.
How it works
A panel of experts, on your machine
Instead of one giant generalist model in someone else's datacenter, NIKITRIA runs a panel of small specialist models on your own hardware and combines their answers — with every step visible and attributable.
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Ask
Your question is processed entirely on your device. Nothing is sent anywhere.
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Route
An embedding-based router matches the question to the best-suited specialist expert — semantic matching, not keywords, and still no network calls.
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Panel of experts
One or more specialist Small Language Models produce candidate answers within a strict on-device memory budget.
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Synthesize with provenance
The answers are combined into a single response, and every part of it traces back to the expert that produced it.
Architecture shown at the conceptual level.
Pilot with us
We are looking for a small number of institutions to shape the education offering as design partners. Express interest below or through the contact page — no commitment beyond a conversation.
Express interest