14 disease-specific AI modules. 95%+ sensitivity. <90 second analysis. Replacing the slow, glass-slide-and-microscope model with a fully automated, AI-augmented, cloud-native diagnostic workflow designed specifically for India's 1.4 billion people.
Fewer than 8,000 pathologists serve 1.4 billion people — a ratio 25x worse than global benchmarks. 70% of cancers are detected at advanced stages due to inaccessible pathology.
Prana Pathology AI integrates whole-slide imaging (WSI) hardware, fourteen disease-specific AI diagnostic modules, real-time teleconsultation, and an ABDM-compliant LIS — all through dual-mode on-premise and cloud deployment.
Each layer is independently scalable and communicates through a standardised HL7 FHIR v4 / DICOM v3.0 compliant API gateway.
WSI slide scanning & pre-processing via Prana OEM, KFBIO, or Motic scanners. 0.22 μm/pixel at 40x, 60-second scan, 80-slide batch loading.
DICOM SR • OpenWSI API7-stage automated DAG: QC, stain normalisation (Macenko/Vahadane), tissue segmentation, multi-resolution tile extraction.
Python • OpenSlide • PyVips • OpenCVMulti-module disease detection using Attention-Based MIL. Foundation models (UNI, Virchow2) + task-specific classification heads.
PyTorch • ONNX Runtime • TensorRTPWA-based LIS, enhanced OHIF Viewer v3, one-click NABL/CAP-aligned reports, teleconsultation with 8 concurrent viewers.
React 18 • Node.js • PostgreSQL • OHIFABDM/ABHA native integration, HIS bridge (Practo, eHospital, HMIS), research analytics, federated learning.
HL7 FHIR R4 • Apache Kafka • ElasticsearchFor government & large private hospitals requiring full data sovereignty.
For Tier 2 clinics & district hospitals. Scanner on-site, AI in cloud.
Compact on-device AI for MSR Health AI Pod Clinics. Nurse-operated.
Every whole-slide image traverses a DAG of microservices orchestrated via Apache Airflow with real-time Kafka event monitoring.
OpenSlide + dcm4che5 converts raw WSI to DICOM WSI objects
ResNet-50 classifier detects blur, folds, air bubbles
GPU-accelerated Macenko/Vahadane for consistent colour space
U-Net tissue vs background model avoids blank tile processing
PyVips multi-resolution tiling at 5x, 10x, 20x, 40x
UNI / Virchow2 foundation models extract high-dimensional embeddings
Disease-specific attention MIL model classifies entire slide
100K+ WSIs, 20+ tissue types. Primary feature extractor for Tier 1 hospitals.
3.1 million WSIs from Memorial Sloan Kettering. EAGLE framework for cloud inference.
1.17M pathology-language pairs. Report generation NLP alignment.
India Pathology Dataset (IPD) + MSR slides. India-specific fine-tuning for IHC, TB, H. pylori.
Each module is independently deployable, licensed, and updatable. Modules 11 and 14 are India-exclusive with no equivalent in any global platform.
India contributes 26% of global TB burden. No other commercial platform has this. Automated AFB detection, ZN bacilli counting per field (scanty/1+/2+/3+). Direct Nikshay portal integration.
India has the world's highest oral cancer burden (tobacco/betel nut). Classifies OSCC, verrucous CA, mucoepidermoid patterns adapted for South Asian oral mucosa morphology.
Cervical cancer is #2 cancer killer in Indian women. YOLOv9 cell detector (180K annotated cells) + EfficientNet-B5 classifier (2.1M cells). 15 cell types classified.
High incidence in iodine-deficient Indian population. 6-category classification from non-diagnostic to malignant.
Bladder cancer rising from tobacco and industrial exposure. NHGUC, AUC, SHGUC, HGUC, LGUN classification with atypia flags.
India has world's highest TB burden — AI TB flag is critical. Detects malignant cells, atypical squamous, adenocarcinoma clusters, small-cell clusters.
Common in advanced cancer + TB. Classifies reactive mesothelial, mesothelioma, metastatic adenocarcinoma, lymphoma, TB clusters.
H. pylori prevalence >60% in India. 8 lesion types including gastritis, intestinal metaplasia, dysplasia grades, and gastric carcinoma types.
Colorectal cancer rising sharply in urban India. 6 lesion types: normal, IBD, LGD, HGD, adenocarcinoma (tubular/mucinous/signet).
Correlates with MOD-01 for combined cervical screening pipeline — unique Prana strength. CIN1-3, HSIL, invasive SCC, adenocarcinoma.
Endometrial cancer rising with India's obesity epidemic. Classifies atrophic, proliferative, secretory, hyperplasia, EIN/AH, endometrioid adenocarcinoma.
#1 female cancer in India. B1-B5 classification, phyllodes, lobular/ductal CA, DCIS, ER/PR/HER2 status flags. Transformative at district hospital level.
Replaces manual cell counting. ER, PR, HER2 (0/1+/2+/3+), Ki-67%, PD-L1 (TPS), ALK, ROS1, BRAF, MMR proteins. Enables IHC at Tier 2 hospitals.
Critical for accurate staging. Detects micro-metastasis, isolated tumour cells, macro-metastasis. A single missed LN micro-met changes the entire treatment plan.
A purpose-built Laboratory Information System with AI-first data models, natively connected to Ayushman Bharat Digital Mission.
Barcode/QR printing, accessioning, chain-of-custody, ABHA-linked patient ID
CPOE integration, standing orders, reflex testing rules (auto IHC if invasive CA)
RFID/barcode-tracked physical slide journey from grossing to scanner to archive
Priority queue (STAT/routine), SLA tracking, workload balancing across nodes
HL7 FHIR, email, WhatsApp Business API, print, ABHA locker push
CGHS, PMJAY/AB-PMJAY, insurance TPA codes auto-tagged to test results
CAP checklists, NABL documentation, proficiency testing, QC dashboards
Full-text search, slide image search by metadata, WADO-RS from PACS
Native ABHA ID field, FHIR DiagnosticReport to HIE-CM, consent manager
| HIS Platform | Integration | Data Flow |
|---|---|---|
| Practo | REST API + OAuth2 | Bidirectional order/result |
| eHospital (C-DAC) | HL7 v2.5 ORM/ORU | Government hospital connector |
| HMIS (NIC/MoHFW) | ABDM HIE-CM FHIR | Public hospital national system |
| SAP Healthcare | SAP FHIR Adapter | Large private hospital groups |
| Insta HMS | REST API | Mid-market private hospitals |
| Custom HIS | HL7 v2 + FHIR R4 | Any HL7-compatible system |
| Regulation | Status |
|---|---|
| CDSCO MDR 2017 + SaMD 2025 | Filing Q3 2026 |
| DPDP Act 2023 | ✅ Compliant |
| IT Act 2000 + SPDI Rules | ✅ Compliant |
| ABDM HIE-CM Standards | ✅ Compliant |
| NABL ISO 15189:2022 | Roadmap Q4 2026 |
| IEC 62304 / 82304 | In Progress |
| ISO 14971:2019 Risk Mgmt | In Progress |
| HL7 FHIR R4 | ✅ Implemented |
Prana is not a Western clone. It is designed ground-up for Indian disease burden, reporting standards, and infrastructure realities.
| Feature | India-Specific Adaptation |
|---|---|
| TB Module (MOD-14) | RNTCP grading, Nikshay portal integration — no Western equivalent |
| H. pylori Scoring | Validated on Indian gastric biopsy atlas (>60% prevalence) |
| Oral Cancer (MOD-11) | Tobacco/betel nut OSCC patterns, South Asian morphology |
| Reporting Language | English, Hindi, Kannada, Tamil, Telugu (AI-translated) |
| Billing Codes | CGHS, PMJAY, ROHINI auto-populated |
| Low-Bandwidth Mode | Progressive tile loading, WebP compression for 4G/2G |
| Power Resilience | Offline-first tile caching, AI queue resumes after outage |
| Climate Adaptation | Scanner rated 15-40°C, 85% RH (Indian lab conditions) |
Generic AI models trained on Western datasets (TCGA, TCIA) show measurable performance drops on Indian tissue samples. Prana-IndoPath is trained on:
Collaborative research platform for medical institutions, IITs, ICMR labs, and pharmaceutical CROs.
Accelerating Biomarker Discovery & Clinical AI Validation
k-anonymity (k≥5) compliant cohort builder by diagnosis, institution, demographics
Multi-centre model training — only gradients shared, never raw slides
Survival analysis, ROC/AUC comparisons, exportable to R/Python
Distributed campaigns with Cohen's kappa inter-annotator scoring
AWS provisioning, DICOM/FHIR framework, scanner drivers (2 brands), QC pipeline, database schema
MOD-01 (Cervical) + MOD-12 (IHC), PathLIS basic, WSI viewer, report engine, ABHA integration
MOD-02 through MOD-07, Teleconsultation v1, all 10 scanner drivers, mobile app
MOD-11 (Oral), MOD-14 (TB/ZN), multilingual reports, CGHS/PMJAY billing, CDSCO SaMD filing
ResearchHub, federated learning, MOD-13, pan-India onboarding, ISO 15189 prep
Molecular pathology (NGS), Genomics AI (BGI), international SEA version
Class C SaMD pathway. All data localised within India. Algorithm Change Protocol from Day 1.
On-premise, cloud-hybrid, or edge pod clinic. Works air-gapped or with 2G connectivity.
Progressive tile loading, WebP compression, INT8 quantised edge AI at 60W power.
UNI + Virchow2 foundation models with India-specific fine-tuning on 50,000+ MSR slides.
OpenWSI Abstraction Layer: Philips, Zeiss, Leica, Roche, 3DHISTECH, Hamamatsu & more.
TB/AFB (MOD-14) and Oral Cancer (MOD-11) — no other global platform has these.
Volume discounts for hospitals >500 slides/day
PathLIS + viewer + report engine included
Government hospitals / CGHS procurement
15% margin on Prana Compact Scanner
Hub 70%, Platform 15%, Spoke 15%
Pharma CRO and academic research clients
Deploy Prana AI Pathology in your hospital network. Cut diagnostic turnaround by 90% while improving precision to 95%+.