Technology — Backend Engineering
Server-side systems built for scale and reliability.
.NET Core, Node.js, Python, Go, and PHP backend development. REST and GraphQL APIs, microservices architecture, and database design. Senior engineers who have maintained enterprise backends under production load.
Backend Capabilities
Backend engineering led by CTO Imran Gondal (30 years) and Senior Engineer Rizwan Hanif (10 years backend). We've built BPM platforms with 2,300 global installations, fintech APIs processing millions of transactions, and AI inference backends at enterprise scale.
.NET Core & C#
Enterprise .NET Core applications, ASP.NET Web APIs, Entity Framework, and Azure integration. Our team has 30 years of Microsoft stack experience — from early .NET Framework through the full modern .NET ecosystem, including .NET 8, minimal APIs, and CQRS patterns.
Node.js
High-throughput, event-driven Node.js services using Express, Fastify, and NestJS. Excellent for real-time applications, API gateways, and microservices that demand low latency and high concurrency without heavy JVM or CLR overhead.
Python
Python backend services with FastAPI and Django REST Framework. Ideal for data-intensive APIs, ML model serving endpoints, scripting-heavy workflows, and rapid API prototyping. Type-annotated, Pydantic-validated, and async-capable.
Go
High-performance Go services for workloads where throughput, latency, and small binary size matter. Used for API gateways, background workers, and utility services where Go's concurrency model and compilation speed provide a genuine edge.
REST API Design
API-first development with OpenAPI specifications, versioning strategy, consistent error response formats, pagination, and authentication (OAuth2, JWT, API keys). APIs that third-party teams can integrate against without your engineers on a call.
GraphQL
Schema-first GraphQL with Apollo Server, Hasura, and Hot Chocolate (.NET). Resolver optimisation, DataLoader for N+1 prevention, subscriptions for real-time data, and federation for multi-service graphs.
Microservices Architecture
Domain-driven decomposition, service boundary definition, asynchronous communication with message queues (RabbitMQ, Azure Service Bus, Kafka), distributed tracing, and saga patterns for distributed transaction management.
Database Design
Schema design, indexing strategy, query optimisation, and migration management for SQL and NoSQL databases. We model for the read and write patterns your application actually has — not for theoretical normalisation.
Technology Stack
Architecture Approach
Backend systems built to outlast the team that built them.
The most common problem we're asked to fix is a backend that was fast to build and impossible to extend. Logic scattered across layers, no separation of concerns, database queries embedded in controllers, and no tests because "we'll add them later." We've been brought in to rescue several systems in this state.
Our approach is the opposite: API contracts defined before implementation, domain logic isolated from infrastructure, SQL queries reviewed for index usage before they reach production, and test coverage as a build requirement — not a nice-to-have.
Senior Engineer Anis Ahmed's 18 years of integration experience means our APIs are designed to be consumed — by humans, by automated systems, and by teams who weren't in the original design meeting.
API-First Design
OpenAPI spec written before implementation. Consumer teams can stub against the contract while we build. No surprises on integration day.
Domain-Driven Structure
Business logic lives in a domain layer — not in controllers, not in ORMs. Changes to how you store data don't cascade through your business rules.
Async by Default
Background work done asynchronously via queues. Long-running operations don't hold HTTP connections. Retries, dead-letter queues, and idempotency designed in.
Database Design Review
Every schema gets an index review before deployment. N+1 queries are caught in code review. Slow query logs monitored from week one.
Security in Every Layer
Input validation, parameterised queries, JWT expiry, rate limiting, and OWASP Top 10 review are built-in requirements — not post-launch checklist items.
Testable Code
Dependency injection throughout. Services are mockable. Integration tests run against real database instances in CI with automatic cleanup.
Choosing the Right Backend Language
We work across five backend languages. The choice depends on your team's existing skills, performance requirements, and long-term maintenance considerations — not on what we happen to have capacity for.
.NET Core / C#
Enterprise applications, Windows-adjacent infrastructure, teams with existing .NET investment. Best ecosystem for Azure integration.
Node.js
Real-time applications, API gateways, teams with strong JavaScript skills who want to share code between frontend and backend.
Python
Data-heavy APIs, ML model serving, and rapid prototyping. Shares a language with your data science team.
Go
High-throughput services, CLI tools, infrastructure components. Compiles to a single binary with minimal resource footprint.
PHP / Laravel
Content-driven applications, e-commerce, and teams with existing PHP infrastructure. Laravel's ecosystem is mature and productive.
Polyglot
Microservices often benefit from different languages per service. We can design and maintain a mixed-language architecture with clear API contracts between services.
Need a backend that scales with your business?
Tell us about your system — we'll give you an honest architecture recommendation and a clear scope.