Why THB

The AI-Native Healthcare Data Cloud

Every healthcare CRM vendor says they have AI. Most of them bolted a chatbot onto a CRUD app and called it a day. THB is different -- we built the data pipeline first. Clinical intelligence is computed at ingestion, not queried at runtime. That's why it works.

0+
Healthcare clients -- production, not pilots
0M
Patients who received follow-up care
0K
Doctors on the platform
0.0x
Follow-up ROI -- platform pays for itself
<0h
Hospital go-live -- config, not a project
0M+
Recommendations delivered to patients

The Problem We Solve

India has 70,000+ hospitals generating clinical data in 150+ fragmented formats. The data exists. The processing layer does not. We built it.

The Problem

Hospital data is fragmented across dozens of systems with incompatible formats. No patient has a complete record. Follow-up revenue leaks continuously. Care gaps go undetected. And every hospital CRM in the market is a UI layer on top of broken data -- which is exactly why adoption fails. You can't engage patients you can't identify.

Our Insight

The data pipeline IS the product. Solve the data engineering problem -- ingestion from 150+ formats, identity resolution, clinical intelligence computation -- and the engagement layer becomes almost trivial. The CRM writes itself because the data is already clean, unified, and intelligent. Most companies start with the UI. We started with the pipe.

Production Scale

These are production numbers from hospitals running THB today.

150+

Healthcare Clients

Hospitals, chains, pharma -- 6 countries, paying customers

20M

Patients Delivered Care

Real patients. Real follow-ups. Real clinical outcomes.

600K

Doctors Engaged

Active on the platform, not just registered

5,000+

Data Partner Centres

Connected and processing data nationwide

100M+

Recommendations Delivered

Not impressions -- actual follow-up actions

60M+

De-identified Lives

Real-world evidence for pharma programs

The Healthcare Data Opportunity

India's healthcare digitization is at an inflection point. HIS adoption is accelerating. The data exists. The question is who processes it.

70,000+
Hospitals in India

Increasing HIS adoption means more digital data, but in proprietary, incompatible formats. The data exists -- the processing layer does not.

150+
Hospital Formats Mapped

Each format required understanding a specific HIS vendor's quirks. Every new hospital makes the library more valuable. Config-driven onboarding in under 48 hours.

ABDM
Regulatory Tailwind

Ayushman Bharat Digital Mission mandates digital health records and interoperability. Hospitals need a data platform that speaks ABDM. THB is built for this standard.

Why Vertical Integration Matters

Each layer is a product on its own. Together, they create a platform where data flows end-to-end without translation layers or sync jobs.

DC

DataCloud

150+ hospital formats in, one golden patient record out. Care gaps detected, cohorts segmented, follow-up journeys automated. No custom code per hospital -- that's the scalability story.

NH

NovaHub

Complete patient profile from a phone number in real time. Curated, resolved, intelligence-ready data delivered to any application -- CRM, HIS, EMR, AI agents. Zero-downtime updates across millions of records. Register a dataset, get an API.

PE

PEP + CRM

PEP turns clinical data into booked appointments -- cohorts, campaigns, journeys, ROI attribution. CRM Suite handles the operational side: tickets, leads, agent workspace, Patient 360. Both config-driven. One codebase for every hospital.

Why this is hard to copy: A CRM vendor needs to first solve the data engineering problem -- that's DataCloud, 2+ years of hospital format mappings. A data infrastructure vendor needs to build the engagement layer -- that's PEP + CRM Suite. And both need the serving layer that delivers curated data to every application -- NovaHub, our purpose-built real-time API gateway. We have all three. Integrated. Production-tested across 150+ hospitals.

Technical Architecture

Three layers, vertically integrated. Each layer has independent technical moats. Together, they create a platform that is extremely difficult to replicate.

Ingestion & Processing (DataCloud)
Schema Detection
150+ formats
MDM Engine
Golden records
Clinical Intelligence
Flags, scores, gaps
Cohort Engine
Automated segmentation
Serving & API (NovaHub)
Data Cache
Real-time reads
Arrow Flight
Column streaming
Identity Resolution
Real-time
Atomic Updates
Zero downtime
Engagement & AI (PEP + CRM Suite)
AI Agent Builder
Config-driven
Workflow Engine
Automation
Multi-Channel
WA/SMS/Voice
NL Analytics
Hindi/English

The Scale Story

Most healthcare CRM vendors send a team for every hospital. We send a config file.

Traditional Healthcare CRM

3-6 monthsper hospital integration
Custom ETLfor each hospital system
Engineering teamrequired per deployment
Linear scalingcost grows with hospitals

THB Config-Driven Approach

<48 hoursper hospital onboarding
YAML configsfor 150+ hospital formats
Zero engineersper deployment
Sublinear costeach hospital cheaper than the last

Technical Moats

Every claim below is demonstrated with running code. Not mockups. Not slides. Not "coming soon."

Instant Patient Profiles

Complete patient profile from a phone number in real time. Purpose-built storage engine with pre-assembled, curated records. Designed for high-volume production use -- because at scale, data delivery speed directly impacts staff productivity.

Real-Time Clinical Dashboards

Dashboards load in milliseconds, not seconds. Arrow Flight streams columnar data that arrives analysis-ready. No row scanning, no ETL lag, no "data last updated 24 hours ago."

One Patient, One Record

3 hospital records become 1 golden record. Phone number, name, date of birth, address — weighted probabilistic matching with manual review for edge cases.

No Code Per Hospital

This is the scalability thesis. The 100th hospital costs less than the 10th. Ingestion, clinical intelligence, care gap detection -- all config. No engineering team per deployment.

Self-Configuring Interface

Add a field to the entity schema. The CRM interface updates automatically -- forms, tables, views. Zero frontend code for routine changes. This is how we ship features in hours, not sprints.

Deployable AI in Hours

New AI assistant in 2-4 hours. Write the prompt in markdown, pick tools from the registry, deploy. No engineering sprint. Strict data contracts ensure the AI doesn't go off-script.

What Makes THB Different

150+ Hospital Formats Mapped

150+ hospital format mappings built over years of production integration. Each one required understanding a specific HIS vendor's quirks. Every new hospital makes the library more valuable.

Config-Driven Scale

Under 48 hours per hospital. Zero engineers per deployment. The 100th hospital is genuinely cheaper to onboard than the 10th. Config-driven architecture means scale without proportional headcount.

5.3x ROI on Follow-up Campaigns

The platform pays for itself in under a week. Care gap detection, AI-drafted follow-ups, and full-funnel attribution turn clinical data into measurable revenue. Hospitals see the return immediately.

Built for India and Emerging Markets

ABDM-ready. Regional HIS formats across India, South Asia, and the Middle East. On-premise and private cloud deployment options. Data residency compliance built in.

Full-Stack Ownership

We own every layer: ingestion (DataCloud), serving (NovaHub), engagement (PEP + CRM Suite), intelligence (AI Platform). No dependency on external data platforms or CRM vendors.

AI-Native, Not AI-Washed

AI is the architecture, not a feature checkbox. Clinical intelligence is computed at ingestion time, not queried at runtime. Pluggable LLM backend. Auto-generated tools from schemas. This is what AI-native actually looks like.

Production-Proven at Scale

150+ healthcare clients. 5,000+ data partner centres. 6 countries. These are production deployments processing real patient data daily.

Domain-Expert Team

200+ people across engineering, clinical, and product. Doctors who understand data engineering and engineers who understand clinical protocols. That combination took years to build.

See the Architecture Running. Not on a Slide.

25 minutes. Seven live demos. Real clinical data flowing through real infrastructure. Book a meeting and we'll show you.