

šØ THE MENTAL HEALTH AI CRISIS šØ
THE PROBLEM:
ā AI chatbot tells anorexia patient: āMaintain 500ā1,000 calorie deficitā
ā āBuy calipers to measure body fatā
ā Patient activist: āI wouldnāt be alive if Iād used thisā
Thatās not fiction.
Thatās NEDAās āTessaā chatbot, 2023.
THE NUMBERS:
š° $67.4 BILLION lost to AI hallucinations (2024)
āļø Hospitals now face liability when chatbots miss suicide risk
š„ FDA cracking down on āwellnessā excuse for medical AI
š Malpractice insurers demanding auditability
THE ISSUE:
Most mental health AI uses Large Language Models (LLMs).
Theyāre trained to be:
ā Conversational
ā Agreeable
ā Helpful
But agreeable ā safe.
When someone with an eating disorder asks about weight loss, a standard LLM sees a legitimate query ā not a clinical red flag.
THE SOLUTION: VERIPRAJNAāS CLINICAL SAFETY FIREWALL
We donāt make LLMs āsafer.ā
We architect safety INTO the system.
š¹ INPUT MONITOR
Scans messages against the C-SSRS suicide risk scale BEFORE they reach AI
š¹ HARD-CUT
Detects risk? Disconnects the LLM. Switches to a pre-approved crisis script.
š¹ OUTPUT CHECK
Blocks hallucinated medical advice before it reaches users
š¹ EHR INTEGRATION
Patient history determines whatās safe for THEM specifically
THE ARCHITECTURE:
Probabilistic AI (engagement) + Deterministic Firewall (safety) = Protected patients
THE REALITY:
Empathy canāt be simulated.
But danger CAN be automated.
So safety must be automated too.
Safety isnāt a feature.
Itās the architecture.
Letās discuss how Clinical Safety Firewalls protect your healthcare AI deployment.
š Read the full technical whitepaper here:
https://veriprajna.com/whitepapers/clinical-safety-firewall-deterministic-triage-health-ai
š§ [email protected]
š https://veriprajna.com
š¬ WhatsApp: +919217059957
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