SIkai Saathi

Sikāi Sathi · सिकाइ साथी Your learning companion. Your language. Your pace. One-liner: A Nepal-first AI companion that reads a Grade 8 student's handwritten math, names the exact mistake, explains it in Nepali, and proves learning with practice — never rote answers. 1. Problem (education sector) Rote over understanding. Students memorize final answers (e.g. x = 15) instead of learning the step they missed (dividing both sides by 3). No 1:1 feedback at scale. Teachers can't hand-mark every copy; parents can't always help with algebra. Language gap. Most AI tutors explain in English. A Nepali-medium student thinks in Nepali (पक्ष, भाग गर) but is tested in a second language. Phone-first, low-bandwidth reality. The student device is a low-to-mid Android phone on patchy 3G/4G — heavy apps and full-photo uploads fail. Untrustworthy AI. Generic LLM tutors hallucinate correctness and invent mastery. In education, a wrong "Mastery: YES" is worse than no feedback. 2. Solution Submit → Diagnose → Learn → Practice — one learning loop, 4 screens, 3 taps to practice (down from 7 screens / 5 taps in the audit). Step Student does App does 1. Submit Photo of copy or typed steps Pinned equation bar; Photo/Type tabs, "Try an example" 2. Diagnose Reads flagged steps Highlights wrong line, names misconception in student language ("Look at line 3…", लाइन 3 हेर) 3. Learn Reads + answers inline Nepali/English explanation, quick-check with self-check, balance-scale visual tipped by their own answer 4. Practice Solves fresh variant Deterministic new question every time, hint → retry (2 tries) → worked solution, "N of 3" progress + activity timeline Core rule: correctness, misconception labels, and mastery are decided only by deterministic Python (backend/app/math_engine.py). The LLM only explains. Typed steps are diagnosed deterministically even when an LLM provider is active.