GTMScale
B2B Health-Tech ERP Platform
A production B2B SaaS ERP serving 500+ healthcare orgs with real-time operational and KPI data at scale.
A microservice-based B2B SaaS ERP (MERN + AWS) powering 500+ healthcare organizations, with 24+ features, real-time dashboards and sales trackers, hardened by JWT auth and automated testing across 750+ CI/CD deployments.
Engineering Brief
- My contribution
- Microservice architecture, product features, API and query optimization, authentication, and automated release testing.
- Engineering difficulty
- Ship independently across a multi-tenant healthcare ERP while controlling query cost and release risk.
- Outcome
- A production ERP with customer adoption, frequent releases, faster APIs, and fewer bug reports.
Engineering questions
The Problem
Healthcare organizations needed a reliable, fast, multi-tenant ERP for day-to-day operations and analytics, shipped continuously without breaking production.
System Architecture
Architecture design
Illustrative paths, not live telemetry.
Architecture overview. No node selected.
Full network reference
500+ Orgs
B2B tenants
Kind: client
Healthcare organizations are the reported tenant population; the public portfolio does not contain a customer ledger.
Incoming (0)
None in this diagram
Outgoing (1)
- API Gatewayflow
API Gateway
JWT auth
Kind: api
Authenticate API access with JWT and route requests into the ERP services.
Outgoing (3)
- KPI Servicesflow
- Dashboardsflow
- Sales Trackerflow
KPI Services
Analytics
Kind: service
Serve operational analytics and KPI data as a separate service concern.
Incoming (1)
- API Gatewayflow
Outgoing (1)
- MongoDBdata
Dashboards
Real-time
Kind: service
Expose real-time operational dashboards backed by the platform's data services.
Incoming (1)
- API Gatewayflow
Outgoing (1)
- PostgreSQLdata
Sales Tracker
24+ features
Kind: service
Support sales-tracking workflows within the reported product-feature scope.
Incoming (1)
- API Gatewayflow
Outgoing (1)
- MongoDBdata
MongoDB
Operational
Kind: data
Store operational documents, with indexes and pagination used to control query cost.
Incoming (2)
- KPI Servicesdata
- Sales Trackerdata
Outgoing (0)
None in this diagram
PostgreSQL
Relational
Kind: data
Serve relational data alongside the MongoDB workloads.
Incoming (1)
- Dashboardsdata
Outgoing (0)
None in this diagram
CI/CD
750+ deploys
Kind: ops
Automate testing and service releases across the ERP's independently deployed services.
Incoming (0)
None in this diagram
Outgoing (1)
- API Gatewaydeploy
What I Engineered
- Architected 12+ microservices powering a production B2B SaaS ERP serving 500+ healthcare organizations.
- Championed 750+ CI/CD deployments with DevOps practices for dependable, continuous releases.
- Designed and launched 24+ features including real-time dashboards and sales trackers.
- Improved API performance by 60% through query optimization, indexing and pagination across MongoDB and relational data.
- Built secure MERN applications with JWT authentication and reduced bug reports by 50% via automated testing.
Impact & Scale
- 500+ organizations served in production
- 60% faster APIs and 45% faster end-user experience
- 50% fewer bug reports via automated testing
- 750+ dependable CI/CD deployments
Evidence & Scope
This case study covers service boundaries, query optimization, authentication, release testing, and ERP features.
Source is proprietary to GTM4Health. Architecture and trade-offs walked through on request.
Engineering Decisions
- 01
Decomposed the platform into 12+ focused microservices over a shared monolith.
Independent services let 24+ features ship on their own cadence to 500+ orgs without one release train blocking everything. The operational cost of running many services was absorbed by CI/CD automation.
- 02
Won latency back through indexing and query tuning before scaling hardware.
The 60% API improvement came from indexes, query optimisation and pagination across MongoDB and relational data: a cheaper, more durable fix than adding infrastructure to mask slow queries.
- 03
Gated every one of 750+ deploys behind automated tests.
Continuous deployment to production healthcare tenants only works if releases are safe by default. Test gates cut bug reports 50% and let a small team ship continuously without breaking production.
Stack
- Node.js
- Implement the ERP's independently deployed backend services.
- MongoDB
- Serve operational data with query tuning, indexes and pagination.
- PostgreSQL
- Support relational data alongside the document-oriented workloads.
- CI/CD
- Make automated tests part of the release workflow for multiple services.
Source is proprietary to GTM4Health. Architecture and trade-offs walked through on request.
Related work
Shared engineering patterns across separate systems, not runtime dependencies.
- Hexus – Smart Log Manager
Both expose multi-tenant applications through APIs, with distinct documented trade-offs: Hexus centralizes tenant isolation in database policies; GTMScale separates service releases and tunes data access.
Enterprise Internal
- RapidDoc AI
CI/CD maintains different artifacts in each project: RapidDoc regenerates documentation on code changes; GTMScale tests and releases services.
Production Pilot
Open to AI Software Development & Platform Engineering roles
Need someone who ships systems like this into production?