Foundational Literacy & Numeracy · NCERT NISHTHA

एफ़एलएन साथी

कक्षा एक से तीन के बच्चों के माता-पिता के लिए एक AI आवाज़ हेल्पलाइन। यह हर बार एक छोटा, घर पर करने लायक पढ़ने या गिनती का खेल बताती है — सरल हिंदी में, गर्मजोशी के साथ, और NCERT निष्ठा एफ़एलएन सामग्री पर आधारित। एक AI सहायक, कोई शिक्षक या अधिकारी नहीं।

📊 Explore the full platform & campaign dashboard

Live · Browser demo

अभी एफ़एलएन साथी से बात करें

Click the orb. एफ़एलएन साथी greets you in Hindi and gives one simple, do-at-home reading or counting activity for your child (Grades 1–3) — grounded in NCERT NISHTHA FLN material. No phone number needed. Allow microphone access when prompted.

Click the orb to start the call

एफ़एलएन साथी identifies itself as an automated AI helper — never as a person, teacher, or government officer. Demo content; validate against official NISHTHA FLN material before any real use.

Full product capability

One voice platform, many education missions

The FLN parent helpline you just spoke to is one application of a mother-tongue voice layer that reaches any citizen on any phone — no app, no literacy required. Here is where it fits across the school system.

High-fit domains ✓

Parent FLN Coaching

Strongest RCT evidence; zero digital literacy required.

Oral Reading Assessment

ASR correlates 0.96 with human graders; fills the national assessment gap.

Teacher Micro-Training

Bypasses the collapsed cascade; reaches 10.1M teachers on phones they own.

CWSN Assistive Support

No viable human alternative at scale; RPwD Act compliance imperative.

Use-case catalogue

Each use case maps a documented system problem to a voice solution and a measurable KPI chain (intermediate → impact).

6.1

Dropout risk detection

Problem: ~65.7 lakh dropouts over 5 years; secondary NER 47.5%.
Voice solution: Per-child risk scoring (attendance + transition data) triggers parent voice outreach in the mother tongue.
KPIs: % high-risk parents reached <72h; re-engagement rate → secondary dropout reduction.

6.2

Attendance monitoring

Problem: Teacher-recorded; chronic absence detected late.
Voice solution: Automated check-ins to parents of flagged absentees.
KPIs: % absentees contacted <48h → attendance recovery rate.

6.3

Parent engagement

Problem: No structured channel for non-literate / rural parents.
Voice solution: Periodic mother-tongue voice pulse calls.
KPIs: Parent participation rate; CSAT → home-support behaviours.

6.4

PM POSHAN (Mid-Day Meal) audits

Problem: Quality lapses; only 143,324 of 211,366 schools reported daily MDM data (30 Apr 2026).
Voice solution: Independent voice audits to parents/students on meal receipt and quality.
KPIs: Daily-reporting completeness; complaint-to-resolution time → meal quality/coverage.

6.5

Learning-outcome assessment

Problem: NAS infrequent and labour-heavy (~1.82 lakh investigators).
Voice solution: Voice-based oral reading/numeracy micro-assessments between NAS cycles.
KPIs: Assessment frequency; FLN trend granularity → foundational learning.

6.6

Scholarship awareness & verification

Problem: ~89 lakh beneficiaries fell off 9 SC/ST/OBC schemes (2020-21 to 2024-25).
Voice solution: Proactive eligibility/deadline campaigns + verification calls.
KPIs: Eligible-applicant uplift; ghost-beneficiary reduction → aid reaching the eligible.

6.7

Teacher-training tracking

Problem: NISHTHA completion verified weakly; effectiveness feedback thin.
Voice solution: Completion-verification + knowledge-check calls.
KPIs: Verified completion %; module efficacy score → teaching quality.

6.8

Infrastructure audits

Problem: UDISE+ infrastructure self-reported.
Voice solution: Voice audits to principals/SMC members to validate entries.
KPIs: Data-discrepancy rate → verified school infrastructure.

Demo overview. Problem figures are as cited in the source materials; validate against current official data before any deployment. Production targets Bhashini + sovereign Indian infrastructure; ElevenLabs is used only for this demonstration.