Infotrik Technologies

Our stack

Technologies we work with.

We pick technology based on what your product actually needs — not what's trendy. Here's the full stack we work in, and why we reach for each tool.

Frontend

React

The industry-standard JavaScript library for building fast, component-based user interfaces. We use React as our default choice for complex, interactive front ends where reusability and a mature ecosystem matter most.

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Next.js

A React framework that adds server-side rendering, static generation, and file-based routing out of the box. We reach for Next.js when SEO, performance, and fast page loads are business-critical.

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Vue.js

A progressive, approachable framework that's easier to onboard teams into than heavier alternatives. We use Vue for projects where simplicity, a gentle learning curve, and fast iteration are priorities.

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TypeScript

A typed superset of JavaScript that catches bugs at compile time instead of in production. We use TypeScript across virtually all our frontend and Node.js projects to keep large codebases maintainable.

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Tailwind CSS

A utility-first CSS framework that lets us build custom designs quickly without fighting a rigid component library. We use it to move fast while still shipping pixel-perfect, on-brand interfaces.

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Backend

Python

A versatile, readable language that powers everything from web backends to data science and AI. We use Python where clarity, fast development, and access to a massive library ecosystem matter.

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FastAPI

A modern, high-performance Python web framework with automatic API documentation and native async support. We use FastAPI as our default for building fast, well-documented REST and GraphQL APIs.

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Django

A batteries-included Python framework with a mature admin panel, ORM, and security defaults built in. We use Django for content-heavy or admin-heavy applications where speed of delivery matters.

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Node.js

A JavaScript runtime that lets teams use one language across the entire stack. We use Node.js for real-time applications and services where JavaScript end-to-end reduces context-switching.

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Java

A battle-tested, strongly-typed language built for large-scale, high-reliability enterprise systems. We use Java when a client's existing stack, compliance needs, or scale demands proven enterprise-grade tooling.

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PostgreSQL

A powerful, standards-compliant relational database with strong support for complex queries and data integrity. We use PostgreSQL as our default relational database for most production systems.

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MongoDB

A flexible document database that adapts easily to evolving data models. We use MongoDB when schema flexibility and horizontal scalability matter more than strict relational structure.

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Redis

An in-memory data store used for caching, session storage, and real-time data. We use Redis to dramatically speed up applications and handle real-time features at scale.

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Mobile

Flutter

Google's UI toolkit for building natively compiled apps from a single Dart codebase. We use Flutter when a product needs pixel-perfect custom UI across iOS and Android with one shared codebase.

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React Native

A cross-platform framework that lets web-familiar teams ship real native mobile apps. We use React Native when a team already knows React and wants to reuse logic across web and mobile.

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Swift

Apple's native programming language for iOS, iPadOS, and macOS. We reach for Swift when a product needs full access to native iOS capabilities and the polish only a truly native app delivers.

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Kotlin

Google's preferred language for native Android development. We reach for Kotlin when a product needs full native Android capability, top-tier performance, or deep platform integration.

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Cloud & DevOps

AWS

The most comprehensive cloud platform, offering everything from compute and storage to managed AI services. We use AWS as our primary cloud provider for most client infrastructure.

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Google Cloud

A cloud platform known for its strength in data analytics, machine learning, and Kubernetes. We reach for GCP when a project leans heavily on AI/ML tooling or BigQuery-style analytics.

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Azure

Microsoft's cloud platform, deeply integrated with enterprise tools like Active Directory and Microsoft 365. We use Azure when a client's existing enterprise stack is Microsoft-centric.

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Docker

A containerisation platform that packages applications with everything they need to run consistently anywhere. We use Docker on virtually every project to eliminate 'it works on my machine' problems.

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Kubernetes

An orchestration platform for deploying, scaling, and managing containerised applications. We use Kubernetes for products that need automated scaling, self-healing, and multi-service orchestration.

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Terraform

An infrastructure-as-code tool that lets us define and version cloud infrastructure like application code. We use Terraform to make infrastructure changes repeatable, reviewable, and disaster-recovery-ready.

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Data & AI

TensorFlow

A widely-adopted deep learning framework with strong production deployment tooling. We use TensorFlow for machine learning projects that need to move from research to production reliably.

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PyTorch

A flexible, researcher-friendly deep learning framework favoured for rapid experimentation. We use PyTorch when a project needs cutting-edge model architectures or fast iteration during R&D.

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LangChain

A framework for building applications powered by large language models, handling prompt chaining, memory, and tool use. We use LangChain to build production-grade AI agents and LLM-powered features.

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Don't see your stack?

This is our core toolkit, not the limit of it. Tell us what you're working with — chances are we've already built on it.

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