Is this a real clinic case study?

No. This is a simulated proof-of-method asset built with synthetic sample rows. It is not a real clinic, patient-data analysis, PHI, crisis log, customer outcome, testimonial, medical advice, clinical advice, legal advice, privacy advice, DPDP compliance claim, revenue claim, therapy outcome or ROI claim.

What buyer problem does this demonstrate?

It demonstrates how counselling enquiries from calls, WhatsApp, Instagram, paid search, website forms, corporate wellness, referrals, parent enquiries, webinars and EAP handoffs can become owner queues for callback SLA, source capture, counselling triage logging, DPDP prompt evidence, WhatsApp opt-in evidence, AI-boundary disclosure, clinical-supervisor routing and closure reasons.

Can this guarantee safety, compliance, treatment outcomes, revenue or AI accuracy?

No. The numbers are synthetic arithmetic outputs only. A real pilot would need permissioned clinic data, clinical leadership approval and qualified legal, privacy, medical, advertising and security review before publishing any patient, safety, compliance, treatment, revenue or AI-accuracy statement.

Simulated proof asset · India Healthcare GrowthOS

Simulated India mental-health clinic counselling triage + DPDP diagnostic

This no-fake-client proof asset shows how AICS can inspect counselling enquiries, risk-triage evidence, missed-call callback ownership, DPDP prompts, WhatsApp opt-in evidence, AI-boundary disclosure and clinical-supervisor routing before a clinic owner scales ads, WhatsApp automation, CRM or AI reception. It is synthetic only: no real clinic, patient, minor, parent, PHI, crisis record, DPDP compliance, crisis intervention, therapy outcome, revenue or ROI claim is made.

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Important claim boundary: this page is a simulated proof-of-method demonstration. It is not a customer case study, not a testimonial, not a clinic-data analysis, and makes no real clinic, no patient, no minor, no parent, no PHI, no crisis log, no counselling, no diagnosis, no crisis intervention, no medical advice, no clinical advice, no legal advice, no privacy advice, no security advice, no DPDP attestation, no certification, no platform partnership, no advertising, no ranking, no revenue, no ROI, no therapy outcome and no AI-accuracy promise.

Synthetic enquiries1,59012 synthetic workflow/channel rows

After-hours enquiries247sample events needing callback ownership

Missed calls45synthetic calls not initially answered

Callback coverage proxy47.3%after-hours + missed-call base with callback in 2 hours

Consults booked512synthetic booking queue only

Booked not attended150synthetic attendance follow-up gap

Risk triage required457synthetic human-review queue

Risk triage logged40.5%185 of 457 sample enquiries logged

Diagnostic method

What a clinic owner can inspect before scaling WhatsApp, AI reception, paid search or CRM follow-up

The diagnostic converts enquiry rows into operating queues: source tagging, care-owner assignment, callback SLA, counselling triage logging, crisis-escalation route, DPDP notice prompt, WhatsApp opt-in evidence, AI boundary disclosure, clinical-supervisor route and closure reasons.

Evidence/control area	Synthetic enquiry volume with gap	Why AICS would flag it
Source captured	677	Owners cannot reliably compare GBP calls, WhatsApp, Instagram, paid search, website forms, corporate wellness referrals, parent enquiries, webinars and EAP handoffs.
Care owner assigned	812	Unowned sensitive enquiries weaken callbacks, handoffs and human review accountability.
Risk triage logged	272	Only 185 of 457 synthetic triage-required enquiries have triage logged; this is an operational evidence gap, not a clinical-risk or safety claim.
Crisis escalation route present	1,075	Sensitive workflows need explicit human/clinical supervisor routing before any automation is considered.
DPDP notice prompt present	1,401	The workflow lacks operational evidence that data-use notice language was presented; this is not compliance advice.
WhatsApp opt-in evidence	1,352	Follow-up templates should distinguish permissioned messages from ad hoc staff messaging.
AI boundary disclosed	1,263	The process must state that automation cannot provide counselling, diagnosis, crisis intervention or emergency support.
Clinical supervisor route	1,027	Owner dashboards should surface the human reviewer for minors/parents, self-harm terms, urgent distress and medication/diagnosis requests.
Closure reason captured	1,405	Without closure reasons, the owner cannot distinguish resolved enquiries from risky silence.

Before diagnostic

Phone, WhatsApp, Instagram, webinar, EAP and referral enquiries sit in separate inboxes.
Owner sees booked consultations, but not counselling triage evidence, source gaps, AI-boundary gaps, DPDP prompt gaps or supervisor-route gaps.
Sensitive messages can remain inside channel threads without a consistent handoff note.
WhatsApp opt-in evidence and closure reasons are often assumed rather than evidenced.

After diagnostic operating rule

Every enquiry receives source, owner, status, DPDP prompt flag, WhatsApp opt-in flag, AI-boundary flag and closure reason.
High-sensitivity language and under-logged triage cases appear in a same-day human review queue.
Clinical-supervisor route is explicit before any automation recommendation.
Automation remains limited to acknowledgement, scheduling support and owner visibility; it does not provide counselling, diagnosis, crisis intervention or legal/privacy advice.

Evidence needed before publishing any real mental-health clinic outcome

A real pilot should collect only permissioned, minimized operational exports where possible; define callback SLA, care owner, qualified clinical leadership review and crisis-escalation boundaries; document triage logging, notice/purpose prompts, WhatsApp opt-in handling, AI/admin boundary wording and closure reasons; and obtain explicit clinic approval plus qualified legal/privacy/advertising/clinical review before any public patient, DPDP, safety, therapy, crisis-response, revenue or ROI statement.

Request counselling workflow fit check View Healthcare GrowthOS

Reproducibility

Internal synthetic artifact: /home/agent/.hermes/aicloudstrategist/case-studies/simulated-india-mental-health-clinic-counselling-triage-dpdp-2026-08-21/. Expected headline output: rows=12, total_enquiries=1590, after_hours_enquiries=247, missed_calls=45, callbacks_within_2h=138, callback_coverage_pct=47.3, consults_booked=512, consults_attended=362, synthetic_booked_not_attended=150, synthetic_attendance_rate_pct=70.7, risk_triage_required=457, risk_triage_logged=185, risk_triage_logging_pct=40.5, crisis_escalation_route_gap_enquiries=1075, source_gap_enquiries=677, care_owner_gap_enquiries=812, dpdp_notice_gap_enquiries=1401, whatsapp_optin_gap_enquiries=1352, ai_boundary_gap_enquiries=1263, clinical_supervisor_route_gap_enquiries=1027, closure_reason_gap_enquiries=1405, attention_rows=12. Input SHA256 68cab3dccd6afcc95ea191f19b1d0eba0998df1211b278e88baffd4fffd832c0; generator SHA256 1a0107cfbaf7650dba6da3cf2cfcac3b38f4c174068b72eb35b00d88f0a3ddbe; report SHA256 9863a8eecb0b205f39f09b98212e8157d1fca4db560042df04c748930da0b32e.

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