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aviral gupta

// SERVICE 08 — MERN APPS

Custom MERN stack applications that replace the spreadsheet your operation runs on.

High-availability internal operations systems, robust administration dashboards, and multi-tenant data structures that replace broken legacy workflows. Engineered across the full stack with separated authentication paths, stateless service profiles, and fault-tolerant queue topologies. At Mercedes-Benz R&D India I worked on an internal approval and audit platform of this kind; the six Node.js microservices behind three UAE brands are ones I designed and wrote the bulk of.

✓ 6 Node.js microservices in production · ✓ internal sign-off platform at Mercedes-Benz R&D · ✓ live payment gateways

Architectural focus
Production service boundaries mapped to team roadmaps: data model, API surface, deployment
System benchmark
Deployed service and the source repository your team owns
Verification gates
Vitest integration suites, API contract reference, test results enforced in CI

Full service list

// TECHNICAL OWNERSHIP

What does a custom MERN build actually include?

Data model before code

I map your entities, relationships and access rules into MongoDB collections with the right indexes and validation, so the schema still holds when your volume multiplies.

Express API with real auth

A documented REST API on Express with role-based access control, token or session auth, request validation, rate limiting and versioned endpoints your other systems can safely call.

A React interface people use

Dashboards, filterable tables, bulk actions and forms built in React and TypeScript around the actual job, with optimistic updates so the app feels immediate rather than merely functional.

Multi-tenancy and permissions

Tenant isolation at the query layer, per-tenant configuration, granular roles, and an audit trail recording who changed what and when — the pattern behind every sign-off system I have built.

Integrations and webhooks

Payment gateways, CRMs and third-party APIs wired in with idempotency keys, retries and dead-letter handling, so a failed call is retried and logged rather than silently losing an order.

Background jobs and queues

RabbitMQ and Redis handle imports, exports, scheduled reports and notifications off the request path, keeping the interface responsive while long tasks run and recover from failure on their own.

Deployment, logging and backups

Containerised services deployed to GCP or your own cloud through CI/CD, with separate staging and production environments, structured logs, health checks, and a tested database restore routine.

Tests, docs and ownership

Automated tests on the paths that matter, an API reference, a plain-language runbook, and a repository readable enough that another engineer can take it over without archaeology.

// PROCESS

How does it work?

  1. 1

    Map the process

    A working session on the spreadsheet or workflow you run today: the entities, the actors, the edge cases, and the parts that actually hurt.

  2. 2

    Scope and data model

    I write the schema, API surface and screen list down first, so there is agreement on what version one contains before any code starts.

  3. 3

    Build in slices

    Working software on a staging URL every week, in usable increments. You click it, comment on it, and change direction while changing direction is still cheap.

  4. 4

    Harden

    Access control, automated tests, error handling, backups and monitoring under realistic load — done before launch, not after the first incident teaches the same lesson.

  5. 5

    Ship and hand over

    Deployment to your infrastructure, documentation and repository transfer, then thirty days of support while your team settles into running it.

// PROOF

Where have I run this in production?

At Mercedes-Benz R&D India I worked on the internal homologation platform, the system of record for the technical and regulatory documentation a vehicle needs before market launch. The platform covered cross-department data capture, multi-level sign-off, a full audit trail and analytics across live vehicle programmes. At Thrifty I later built Cariva on six Node.js microservices with live payment gateways. Internal tool or customer platform, the engineering is the same: a data model that holds, and services that fail safely.

6 Node.js microservicesMulti-level sign-off + audit trailPayment gateways live in production9+ years on production systems

Read the full case study

// TOOL STACK

Which tools do I reach for?

MongoDBExpressReactNode.jsTypeScriptNext.jsRedisRabbitMQDockerGCPCI/CDN-Genius

The technologies and tools behind the work.

// FAQ

What should you know about how I work on this?

Both, and I will tell you which one you need before you spend anything. If an off-the-shelf tool covers eighty per cent of your process, configuring it beats building it. Custom MERN development earns its place when the workflow is the business itself — the approval chain, the pricing logic, the thing no vendor models the way you do.

Four to ten weeks for most first versions, depending on user roles, integrations and payment flows. A single-role internal dashboard over one data source sits at the short end; a multi-tenant SaaS platform with billing, permissions and third-party APIs sits at the long end. Version one is agreed as a screen, endpoint and integration inventory up front, and progress stays reviewable on a working branch rather than revealed at the end.

Yes — send it before the first call and I will sign it. I work with a small number of clients at a time, and I publish nothing about a project, whether product, data, screens or metrics, without written permission. The case studies on this site are limited to work I am allowed to describe.

Regularly. In my last role I worked inside a team of five, three developers plus DevOps and design, so I am comfortable working inside someone else's process: your branch strategy, your code review, your standups, your ticket board. On a shared build I usually take the backend and data model while your team keeps the front end, with the API contract agreed in writing first.

Thirty days of support are included with every build: bug fixes, deployment issues and questions from your team. After that, optional ongoing support covers dependency updates, security patches, monitoring and small changes. Hosting stays in your own accounts — GCP, AWS or wherever you prefer — so nothing is locked to me.

By designing for it in the schema, not by promising it in the pitch. Indexes and query patterns planned against realistic volumes, heavy work moved onto queues, stateless services that can run as several instances, and Redis caching where reads dominate. Cariva runs on six Node.js microservices for exactly that reason: the parts scale independently.

// OPEN TO WORK

Tell me what your spreadsheet is doing, and I will scope the application that replaces it.