NexoraAI Product Studio
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11-module AI prep with RAG grounding and numerical verification

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The Problem

What we were solving for

GATE demands MCQ + MSQ + NAT support and mathematically verified answers — standard LLMs hallucinate on numericals.

The Build

How we approached it

Built on NEET architecture with pgvector RAG for syllabus-grounded answers, Python SymPy sidecar for numerical verification, and smart model routing (Haiku → Sonnet → Opus).

The Outcome

What it does in production

11 modules. 60–70% AI cost reduction via smart routing. Expandable across CS, EC, ME, EE, CE papers.

Tech Stack

Built with

ReactNode.jsTypeScriptClaude APIpgvectorFastAPISymPyRedis
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