Launching August 2026

India’s First Foundational Model Engine for Computational Psychiatric Care

Translating multi-population raw genomic arrays into highly precise, clinically actionable pharmacogenomic adjustments and localized polygenic risk profiles structured for the Indian subcontinent genome landscape.

Cross-Ancestry Model Engine Calibration
Global GWAS >80% Euro-Centric Data GENIATRY TL-PRS OS Indian Cohorts 44.03M Unique Variants Isolated Immediate 25% to 30% Predictive Gain

The Genomic Vacuum & Clinical Guesswork Crisis

Modern precision health models are limited by an extreme Eurocentric ancestry dataset bias, forcing domestic neuro-psychiatric practices to rely heavily on standard clinical trial-and-error treatment methods.

>80%
Western Dataset Imbalance
Over 80% of major global genome-wide association datasets sample European ancestral backgrounds exclusively, leaving less than 5% representation for the distinct genomic complexities of the Indian Subcontinent.
2x to 5x
PRS Efficacy Degradation
Standard international Polygenic Risk Score structures experience severe degradation in predictive accuracy—dropping by a factor of 2x to 5x—when deployed directly onto complex South Asian variant arrangements.
44.03M
Sovereign Variant Space
National data mapping benchmarks verify that out of 129.93 Million genetic variants tracked within domestic lines, 44.03 Million sequence variations remain entirely unique and unaccounted for in traditional Western catalogs.
The Trial-and-Error Treatment Split

Psychiatry regularly operates without baseline molecular biomarkers, meaning clinical diagnostics remain dependent on standard symptom checklist observations. The landmark prospective clinical study indicates a harsh distribution limit:

33% Full Remission Baseline
Only one-third of individuals achieve symptom-free stabilization on an initial antidepressant line, requiring an average threshold of 7 weeks to assess accurate compound efficacy.
33% Vulnerable Partial Response
Another third demonstrate sub-optimal clinical modifications, leaving them structurally susceptible to quick symptom relapses and prolonged functional disruptions.
34% Complete Non-Response
The remaining third extract no measurable clinical asset, enduring systemic compound toxicity and trending directly toward clinical Treatment-Resistant status.
The Macroeconomic & Infrastructure Deficit

Catastrophic clinical management blockages pair with severe infrastructure resource limits inside domestic healthcare domains, compounding the systemic impact.

$1.03 Trillion Productivity Drain
Estimated direct macroeconomic loss to the Indian state due to untreated or improperly managed mental health disruptions driven by structural workspace absenteeism and premature attrition.
0.75 Specialists per 100,000 Citizens
Critical local medical workforce access deficit, trailing significantly behind the targeted world benchmark allocation recommendation of 3.0 psychiatric specialists per 100k cohort.
92% Regional Treatment Isolation Gap
A systemic supply gap that leaves over 90% of rural patients without expert clinical validation, forcing community general practitioners to prescribe mental health chemical lines without biological guidance.

The Biological Computing Platform

Geniatry models complex molecular pathology using structural systems computing paradigms, parsing the 3-billion-letter human genome hard drive as a unified network operating layer.

The Molecular System Paradigm

Traditional precision protocols track individual isolated target metrics. Geniatry maps multi-gene interaction pathways, configuring polygenic liabilities using continuous threshold arrays rather than basic single-mutation targets.

Monogenic (Deterministic Faults) vs. Polygenic (Psychiatric Reality)

A monogenic illness mimics a single severe mechanical system break that forces immediate platform failure. In contrast, psychiatric conditions behave like thousands of microscopic structural layout inconsistencies across a dynamic environment—no lone variation prompts system collapse, but their aggregate liability breaks function under stress.

Linear Risk Architecture Formula
PRS = M j = 1 β j G j
Where M marks the total tracked single nucleotide variations, β_j configures the locally translated ancestral statistical weight adjustments, and G_j maps the raw single-patient sequence allele count values.
GENIATRY INTERACTIVE INSIGHTS ENGINE

Neurodevelopmental / Risk Decile Stratification

Elevated Risk Tier
Assessed Core Target Condition: Bipolar Status / Schizophrenia Overlap
Engine Metric Accuracy Profile: AUROC Optimized
92nd Percentile
Low Base Variant Profile Median Population Mean High Risk Layer
🧬 Engine Translation Result: Variant sets correlate directly with high-odds liability distributions, verifying a **2.3x to 3.0x higher clinical risk profile** compared to baseline sequence configurations.

The Delivery Integration Architecture

operating as a high-margin data interpretation engine. Wet-lab physical operations are delegated to standard diagnostic centers while Geniatry controls the foundational analytics system.

01

Easy Ingestion

Standard home-based or clinic-centric saliva collection arrays requiring minimal technical support protocols.

02

Lab Processing

Partner NABL-certified genetic laboratories execute raw whole genome array reading down to 30x track depths.

03

Geniatry AI Engine

Proprietary multi-population models decode raw sequence tracks, calculating individual polygenic scores and drug-gene calibrations.

04

Intuitive Dashboard

Frontline healthcare specialists receive clean, color-coded, actionable drug compatibility indices directly inside active point-of-care dashboards.

Market Dynamic & Commercial Advantage Moat

Positioned uniquely at the specialized integration overlap of high architectural psychiatric focus, customized local genotype tuning, and an asset-light cloud delivery grid.

$5.3 Billion
Total Addressable Market
The absolute aggregate scale of domestic psychiatric healthcare diagnostics, clinical screening matrices, and general consumer health genomics sectors.
$750 Million
Serviceable Addressable Market
The urban and semi-urban middle-to-high income psychiatric customer framework seeking data-driven mental healthcare infrastructure.
$3.75 Million
Serviceable Obtainable Market
Targeted near-term validation goal tracking a 0.5% market share capture via platform API plugins embedded into corporate Employee Assistance Programs.
Strategic Performance Metrics Geniatry Foundational Layer Standard Genomics Hubs Broad Consumer Wellness Apps Horizontal Diagnostic Chains
Subcontinent Genomic Calibration ✓ Native AI Model Integration ✗ Global ACMG Baselines Only ✓ Partial Shared Allele Pools ✗ Basic Reference Mappings
Psychiatric Path Specificity Focus ✓ 100% Core Specialty Focus ✗ Diluted (Oncology Panel Target) ✗ Non-Specific Fitness Focus ✗ Standard Panel Queries Only
Operational Delivery Framework ✓ Pure SaaS Layer / Flex API ✗ Capital-Heavy Physical Machinery ✗ Capital-Heavy Physical Machinery ✗ Heavy Outpatient Sample Logistics
Clinical Point-of-Care Integration ✓ Real-time Embedded Dashboards ✗ Static Multi-page Document Files ✗ Direct Consumer Coaching Portal ✗ Standard Paper Parameter Logs

Household Out-of-Pocket Cost Metric Matrix (9-Month Baseline)

Initial Diagnostic/Genomic Array Test Traditional: ₹0 | Geniatry Engine: ₹7,500
Specialist Clinical Consultation Rounds Traditional: ₹12,000 | Geniatry Engine: ₹6,000
Medication Trial Cycles & Side-Effect Counterparts Traditional: ₹18,000 | Geniatry Engine: ₹9,000
Overhead Structural Blood Panel Audits Traditional: ₹8,000 | Geniatry Engine: ₹3,000
Indirect Absenteeism Caregiver Loss Rate Traditional: ₹20,000 | Geniatry Engine: ₹6,000
Aggregate Operational Out-of-Pocket Expense Traditional: ₹58,000 | Geniatry Engine: ₹31,500
Net Family Direct Value Save
₹26,500 (45.6% Direct Reduction)
Systemic Family Investment Yield
3.5x Savings Velocity ROI
Clinical Stabilization Timeline Reduction
From 24 Weeks down to < 4 Weeks

The Five-Year Strategic Roadmap

A rigorous operational framework built to capture sovereign genomics clinical data moats and align directly with emerging national public healthcare ecosystems.

Phase 01 | Months 00 - 12

Incubation MVP Setup & Transfer Learning Tuning

Establish formal platform structural alignment profiles matching the FITT - IIT Delhi program evaluation mandates. Gather baseline public genotype lines from the government-backed GenomeIndia dataset repository via the Indian Biological Data Centre (IBDC) framework, calibrating cross-ancestry transfer modeling pipelines without capital-heavy physical installations.

Phase 02 | Months 12 - 24

Clinical Validation & Medical Site Pilots

Deploy collaborative observational clinical trials checking 500 patient sequence setups against designated control segments inside prominent psychiatric hospital lines (such as AIIMS or related specialized facilities). Structure all database storage clusters to secure total compliance with the Digital Personal Data Protection (DPDP) Act and ICMR healthcare AI guidelines.

Phase 03 | Months 24 - 36

Enterprise B2B API Scaling & Digital Portals Launch

Deploy automated cloud API plugins connecting Geniatry risk assessment logic straight into leading domestic tele-psychiatry interfaces (such as Amaha or Wysa) and corporate employee wellness pipelines. Formally activate the deep polygenic screening portal tracking early childhood neurodevelopmental statuses (ADHD/Autism).

Phase 04 & 05 | Months 36 - 60

Sovereign Genomics Moat & National Health Integration

Exceed a repository framework scale milestone of 25,000 distinct domestic patient profiles, moving past global baseline data sets. Interconnect platform diagnostic summaries straight to citizen ABHA account metrics under the Ayushman Bharat Digital Mission parameters, scaling accessible low-cost configurations across the active Tele-MANAS national public service network.

The Technical Leadership Directorate

Cross-disciplinary innovators bridging clinical neuropsychiatric expertise with advanced Johns Hopkins data systems engineering architecture.

Dr. Akanksha Ayushi Singh

Founder & Chief Executive Officer

Specialist clinical director coordinating platform pathology models, medical site validation trials, and user interface translation matrices designed for active point-of-care clinical diagnostics.

Credentials: MBBS, MD Psychiatry Contact: akanksha@geniatry.ai Whatsapp: +91-96851 88800

Utkarsh Singh

Chief Technology Officer

Advanced data systems specialist handling cross-ancestry mathematical optimization layers, cloud database architecture execution, and high-throughput computational pipeline design.

Credentials: Johns Hopkins University Alumni, Worked in Computational Genomics Awards: Forbes 30 Under 30 Contact: usingh@geniatry.ai Whatsapp: +91-70424 34285

Deploying Precision Medical Code to Eliminate Diagnostic Uncertainty

Connect with our computational technology division to review operational API pilot files, integrate high-margin diagnostic dashboards, or review institutional research alignments.