Technologies
Back end and APIs
The back end holds your business rules: who can approve a purchase order, how GST is calculated, when a reminder goes out. We build these services in Node.js, Python, Java or .NET, expose them through REST or GraphQL APIs, and document them so other teams and vendors can connect without guessing.
5 tools
Node.js and Python
Node.js
API servers and background workers that share TypeScript with the front end.
NestJS
Structured Node.js services with modules, validation and tests built in.
Express
Small APIs, webhooks and lightweight services.
FastAPI
Python APIs for AI and data services, with typed request models.
Django
Data heavy apps that benefit from its admin panel and ORM.
3 tools
Enterprise frameworks
Spring Boot
Java services in banks, insurers and large enterprises.
.NET
C# services in Microsoft environments and Azure deployments.
Laravel
PHP apps and commerce back ends that need quick admin features.
4 tools
APIs, messaging and access
GraphQL
One flexible API for apps that pull data from several sources.
Prisma
Typed database access and migrations for Node.js services.
RabbitMQ
Job queues for emails, PDFs, syncs and other slow tasks.
Keycloak
Single sign on, roles and user management across several apps.
What we build with it
Typical work in this stack
- Business rule engines
- Approval chains, pricing rules, credit limits and tax logic kept in one place and covered by tests.
- Public and partner APIs
- Versioned, documented APIs with keys, rate limits and audit logs for dealers, vendors and apps.
- Integration hubs
- Services that sync orders, stock and invoices between your ERP, e-commerce store and accounts.
- Background jobs
- Scheduled reports, reminder messages, bulk imports and PDF generation that run without blocking users.
- Authentication and roles
- Login, OTP, single sign on and fine grained permissions so each person sees only what they should.
How we choose
We match the back end to the rest of your stack. A TypeScript front end usually pairs well with NestJS, so one developer can work across both. AI and data services go in Python with FastAPI. If you run on Java or .NET already, or your auditors expect it, we use Spring Boot or .NET. We prefer a well organised single service over many small microservices until there is a clear reason to split, because fewer moving parts means fewer points of failure in production.
Questions
Good to know
Other parts of the stack
Do you build microservices?
When there is a real need, such as separate teams or very different load. Most systems start better as one well structured service.
Will you document the APIs?
Yes. Every API ships with an OpenAPI or GraphQL schema and example requests, so others can integrate without a call.
Can you connect to our existing database?
Usually yes. We read the schema first, agree what we may change, and make every change through migrations.
Start a conversation
Tell us what you are trying to build.
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