Building the Data Layer That Healthcare Has Been Missing
India's hospitals generate enormous clinical data in 150+ incompatible formats. Everyone focused on the CRM. Nobody built the data processing layer underneath. We did.
Our Mission
Turn fragmented clinical data into intelligence that changes patient outcomes.
Hospitals sit on enormous clinical data -- lab results, visit histories, medications, diagnostic reports -- locked in fragmented systems with incompatible formats. We build the infrastructure that unifies it, computes clinical intelligence from it, and delivers it to the right person through the right channel at the right time.
Not another dashboard. Not another CRM. The data pipeline is the product. When the data layer works, everything above it -- engagement, workflows, analytics -- gets dramatically simpler. That is the insight that started THB.
Our Story
We started with a broken data layer. Everything else followed from fixing it.
THB was founded on a simple observation: every hospital CRM in the market failed because the data layer underneath was broken. Hospitals capture enormous clinical data — lab results, visit histories, medications, diagnostic reports — but it sits locked in fragmented systems with 150+ incompatible formats.
We started by solving the hardest problem first: building a config-driven data engineering platform that could ingest any hospital format, resolve patient identities, and compute clinical intelligence automatically. Once the data was clean and unified, everything else — patient engagement, AI-powered follow-ups, clinical analytics — became dramatically simpler.
Today, THB serves 150+ healthcare clients across 6 countries, delivering care to 20 million patients through 600,000 engaged doctors. We process over 1 billion clinical parameters and have delivered 100 million+ AI-powered recommendations.
What We Believe
These are not values on a poster. They are architectural decisions.
Engineering Depth Over Feature Breadth
We solve data problems first. Features follow. A CRM built on broken data is worthless -- we have seen that movie. A clean data layer with a simple UI? Transformative.
Config Over Code
Every hospital is different. If onboarding a new one requires code changes, you cannot scale. YAML configs, not custom code. The 100th hospital should cost less than the 10th.
Proof Over Promises
Seven demos with running code. Not seven slides with projections. Every claim on this website is backed by working software across 150+ clients.
AI-Native, Not AI-Washed
We did not bolt a chatbot onto a CRM and call it AI. Clinical intelligence is computed at ingestion, embedded in every API response, woven into patient interactions from the ground up.
Hospital Workflow First
Morning briefs. Phone-number lookups. WhatsApp conversations. We build for how hospital staff actually work -- not how technologists think they should work.
Healthcare-Grade Security
Patient data is not something you move fast on. Column-level encryption, schema-per-tenant isolation, audit trails, LLM safety guardrails. No shortcuts. No exceptions.
The Journey
From a broken data observation to a platform serving 150+ clients.
Solving the Data Problem
Every hospital CRM we evaluated failed for the same reason: the data underneath was broken. So we built DataCloud -- config-driven ingestion from 150+ formats, MDM for identity resolution, clinical intelligence computed at ingestion time.
The Speed Layer
Data that takes 3 seconds to load does not get used. We built NovaHub: real-time API gateway, pre-materialized patient views, Arrow Flight streaming. The layer that delivers curated data to any application instantly.
The Patient Interface
PEP for marketing automation -- cohort campaigns, ROI attribution, multi-channel delivery. CRM Suite for operations -- tickets, leads, AI agents, Patient 360 workspace. Both built on the same clean data layer.
AI Woven In
Not bolted on. Woven in. Care gap detection from 200+ protocols. AI-generated follow-ups in Hindi and English. Voice AI. Natural language analytics. Config-driven agent builder.
Seven Demo Suite
We built seven demos with running code to prove every claim. Not a pitch deck exercise -- a forcing function that kept the engineering honest.
Enterprise Adoption
150+ clients. 600K doctors. 20M patients. 1B+ clinical parameters processed. Six countries. All running on the same config-driven architecture.
What We Have Built
Four layers. Each one exists because the one below it works.
DataCloud
Healthcare Data Engineering
- 150+ hospital format ingestion
- MDM with probabilistic matching
- Clinical flag computation
- Care gap detection (200+ protocols)
- Cohort engine & journey automation
- Config-driven, zero custom code
NovaHub
Real-Time API Gateway
- Purpose-built storage for fast reads
- Arrow Flight columnar streaming
- Identity resolution engine
- Config-driven: register dataset, get API
- Zero-downtime atomic updates
- Pre-materialized patient views
PEP + CRM Suite
Marketing Automation & Operational CRM
- Cohort-based campaigns with ROI attribution
- Multi-channel: WhatsApp, SMS, Email, Voice
- Patient, Doctor, B2B, Sales CRM presets
- Tickets, leads, SLAs, agent workspace
- 5 AI agents, 33 tools, telephony
- Metadata-driven UI, workflows, reports
AI Platform
Embedded Intelligence Layer
- Care gap detection (200+ protocols)
- AI-generated follow-ups in Hindi/English
- Natural language clinical analytics
- Voice AI assistant
- Config-driven AI agent builder
- LLM safety guardrails for healthcare
Media & Recognition
Covered by leading business and technology publications.
100+
Research Publications
ERWEJournal
Electronic Real World Evidence Journal
Join Us
We are building data infrastructure for healthcare that actually works. If you care about engineering depth over feature checklists, config-driven architecture, and solving hard problems -- reach out at hello@thb.co.in.
Backend Engineers
Python, Arrow Flight. You will build data infrastructure processing millions of clinical records daily.
Data Engineers
Python, dbt, clinical data modeling. Config-driven pipelines that handle 150+ hospital formats without custom code.
Full-Stack Engineers
Next.js, TypeScript, metadata-driven UI. The engagement layer that hospital staff open first thing every morning.
AI/ML Engineers
LLM integration, clinical NLP, Hindi/English. AI agents with safety guardrails that actually hold up in production.
See What We Have Built
25 minutes. Seven demos. Running code, not slides. Watch raw hospital data become measurable patient outcomes.