Script-Zero Audit: Native-Script Crisis Detection Test for Indic Safety Chatbots
A testing service that checks if safety chatbots can understand distress signals written in Indian scripts.
A pre-launch testing service that fires scripted distress and threat messages in six native Indian scripts (plus transliterations) at a crisis or safety chatbot, then reports exactly which languages the bot actually detects — catching failures like the demonstrated one where a 'trilingual' bot only matches Latin-script keywords.
Concept
A pre-deployment audit for multilingual crisis and safety chatbots. The customer connects their bot (via API or scripted chat sessions); the service runs a curated red-team suite of distress, threat, and crisis expressions in Devanagari, Tamil, Kannada, Telugu, Bengali, and Malayalam — in native script, in Roman transliteration, and in code-mixed forms (e.g., Hinglish). The deliverable is a per-script detection coverage report: which inputs triggered the bot's escalation path and which scored zero, plus a remediation pack (expanded per-script lexicon entries and a transliteration-normalization layer). The single wedge is one honest number per script — 'your bot catches most English threats and 0% of Tamil' — so helpline procurement teams can demand the report before go-live and vendors can fix silent failures before survivors find them.
Why now
The Shakti paper's Version 2 corrections verify, in a publicly deployed women's safety AI (live at meetshakti.in), that threat detection is Latin-script substring matching — so input in Devanagari, Tamil, Kannada, Telugu, Bengali, and Malayalam scores 0.0, in a system described as trilingual Hindi/Kannada/English (Hindi is written in Devanagari; Kannada in its own script). The failure surfaced only through post-hoc correction, because the paper's own evaluation was two prompts with no red-teaming — precisely the pre-deployment gap this audit fills. India's helpline ecosystem (Tele-MANAS and NGO lines) operates across exactly these scripts, so the demonstrated failure mode is live and currently unchecked by any standard QA step.
Written by GLM · 9 Oct 2026
AI assessment
A high-utility, narrow-scope QA tool that leverages a specific, documented failure in Indian safety AI to create a mandatory procurement gate for high-stakes government and NGO helplines.
- Evidence strength 5/5
- The idea is directly derived from a specific, corrected finding in the Shakti paper that explicitly proves a live system failed to detect threats in native scripts despite claiming trilingual support.
- Market pull 4/5
- Governmental bodies like Tele-MANAS and NGOs have high urgency and legal/ethical liability for safety failures, making them strong candidates for a mandatory audit requirement.
- Novelty & moat 4/5
- While other auditors exist, this focuses on a specific script-based failure mode in a high-stakes safety context, filling a gap not addressed by the general prompt or language-ID tools in the catalog.
- Feasibility 5/5
- Building a red-team suite of scripted messages and a reporting dashboard is a straightforward engineering task that does not require training new foundation models.
- Wedge clarity 5/5
- The 'one honest number per script' is a sharp, undeniable metric that creates immediate pressure for vendors to improve and for buyers to demand the report.
- Simplicity / focus 5/5
- The product is a single, focused testing service with a clear input (bot API) and output (coverage report), avoiding platform bloat.
Scored by Gemma 4 · 9 Oct 2026. Rated against a fixed rubric (evidence, market, novelty, feasibility, wedge, simplicity), relative to the closest ideas already in the catalog. A prior estimate to compare ideas before real-world signal arrives.
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Who benefits
Operates a national multilingual mental-health service; a per-script detection report is a concrete procurement and QA gate for any chat-based triage, directly preventing the demonstrated silent failure where native-script input scores 0.0.
- iCall (Tata Institute of Social Sciences)organization
A multilingual psychosocial helpline that would run this audit before deploying or procuring chat triage, so Hindi, Kannada, and other-script callers get equal detection quality.
- Vandrevala Foundationorganization
Runs a 24/7 multilingual helpline; the audit would catch script-coverage gaps for languages their off-hours staffing cannot cover.
- Yellow.aicompany
Indian conversational-AI vendor building government and enterprise helpline bots; attaching a per-script coverage report becomes a compliance artifact that differentiates its safety deployments.
- Turn.iocompany
WhatsApp-based helpline platform used by NGOs; embedding this audit de-risks Indic-language safety-bot launches for its clients.