AI Feedback Intelligence Platform

Umumiy ko‘rinish

Tizim bo‘yicha umumiy tahlil paneli

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Universitet kayfiyati

Talabalar kayfiyati va emotsional signallar

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Fanlar

Fanlar bo‘yicha fikr-mulohaza tahlili

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O‘qituvchilar

AI yordamidagi monitoring signali — yakuniy baho emas

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Trendlar

Vaqt bo‘yicha sentiment va feedback oqimi

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Muammolar

Top muammolar va institutsional tavsiyalar

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Xavf signallari

AI signallari inson tomonidan tekshirilishi kerak

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Kalit so‘zlar

Eng ko‘p uchraydigan so‘zlar va mavzu klasterlari

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RECORD INTELLIGENCE

Yozuvlar

AI tahlil qilingan feedback yozuvlari, risk signallari va tekshiruv navbati

Batch tahlil

JSON datasetlarni yuklash, mapping qilish, validatsiya qilish va AI orqali ommaviy tahlil qilish
BATCH OPERATIONS CENTER

Feedback dataset ingestion pipeline

Fayl yuklanadi → schema tekshiriladi → flat/raw obyektlar inputToSystem ga mapping qilinadi → batch AI tahlil bajariladi → dashboard avtomatik yangilanadi.

Upload
Validate
Map
AI Batch
Dataset source
Demo fayl yoki o‘zingizning JSON faylingiz
JSON only

JSON dataset upload

inputToSystem array yoki flat object array yuklang. Tizim mapping va validatsiya qiladi.

Fayl tanlanmagan
Mission status
Ingestion + AI processing holati

Batch pipeline kutish rejimida

Fayl yuklang yoki demo source tanlab batch tahlilni boshlang.

Schema diagnostics
Structure checking, mapping and quality signals
Upload qilingandan keyin validatsiya signallari chiqadi.
Processing intelligence
Success/failure/fallback va throughput indikatorlari
Batch tugagandan keyin indikatorlar chiqadi.

Test tahlil

Jury uchun real vaqtli AI feedback diagnostika paneli
LIVE AI ANALYSIS

Talaba fikrini real vaqt rejimida tahlil qilish

Matn kiritiladi → inputToSystem yaratiladi → inputToAI shakllanadi → Vertex AI modeli tahlil qiladi → dashboard va indikatorlar yangilanadi.

Input
AI
Signals
Dashboard
Fikr-mulohaza kiritish
Asosiy maydon — talaba feedback matni
Natija nafaqat JSON ko‘rinishida, balki sentiment, xavf, jiddiylik, tavsiya va signal kartalari orqali ham ko‘rsatiladi.

Live AI natija shu yerda chiqadi

Jury feedback yozadi va tizim darhol sentiment, xavf, emotsiya, muammo turi, tavsiya va strukturalangan JSON natijani ko‘rsatadi.

Simulyatsiya

Synthetic feedback scenario lab: demo, stress-test va AI pipeline sinovi
SCENARIO SIMULATION LAB

Feedback oqimini oldindan sinovdan o‘tkazish

Bu modul real LMS kelishidan oldin tizim qanday ishlashini ko‘rsatadi: synthetic feedbacklar yaratiladi, strukturasi tekshiriladi, AI tahlil qilinadi va dashboardga qo‘shiladi.

Scenario
Generate
AI Analyze
Dashboard
Scenario generator
Synthetic feedback parametrlarini tanlang
Demo safe
Generated records vaqtinchalik. AI orqali analyze qilinsa, dashboardga qo‘shiladi.

Scenario hali yaratilmagan

Generator sozlamalarini tanlang va synthetic feedback oqimini yarating.

Scenario intelligence
Generated dataset strukturasi va signal prognozi

Generate qilingandan keyin scenario intelligence chiqadi.

AI processing report
Analyze qilingandan keyin success/failure signallari

Analyze with AI tugmasidan keyin report chiqadi.

Integration

LMS, HEMIS va boshqa boshqaruv tizimlarini secure REST orqali ulash
SECURE REST INTEGRATION

LMS → AI Feedback Analyzer ingestion pipeline

Tashqi LMS yoki HEMIS token oladi, feedbackni xavfsiz REST endpoint orqali yuboradi, tizim schema/mapping/rate-limit tekshiradi va AI tahlilga uzatadi.

Token
Validate
Map
Analyze
Create integration token
LMS/HEMIS uchun secure REST token
Shown once

Token yaratilgandan keyin shu yerda ko‘rinadi.

Integration status
Active systems, security, rate limit

Integration status yuklanmagan

Status tugmasini bosing yoki token yarating.

REST contract
Tashqi LMS/HEMIS yuboradigan minimal payload
POST /integrations/ingest-feedback
      Header: X-Integration-Token: lmsint_xxx

      {
        "feedback": "Dars yaxshi, lekin baholash aniqroq bo‘lsin.",
        "rating": 4,
        "course_id": "CS-101",
        "course_name": "Algorithms",
        "teacher_id": "T-01",
        "teacher_name": "Aziz Karimov",
        "department": "Computer Science"
      }
Live ingest test
Jury uchun real-time integration demo
Security controls
Production-like protection layer
Hashed tokens Token plaintext saqlanmaydi
Rate limiting 30 req/min/token
Schema validation inputToSystem/flat mapping
Audit logging Every ingest is logged
Ingest result
Test ingest natijasi

Test ingest ishga tushirilsa, input/output natijasi ko‘rinadi.

AUDIT OBSERVABILITY

Loglar

AI tahlil, integratsiya, batch, xavf signallari va tizim holati bo‘yicha audit konsoli
Event stream
Real-time audit trail va diagnostika signallari
0 events

Loglar yuklanmoqda...

CONTROL SURFACE

Sozlamalar

Runtime, platform health, demo controls, and project identity
AI RUNTIME

Sentiment Engine

Live inference backend and analysis pipeline status.

Online
Provider —
Project —
Model —
Processed —
Platform Health
Backend availability and service diagnostics.
—
Demo Control
Clear generated dashboard state without touching source files.

Processed results and dashboard state will be cleared. Source JSON files remain unchanged.