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Technologies

The modern tools we use, and when we recommend each one

Our stack

A technology stack chosen for your project, not ours

The right technology stack depends on your budget, your scale, your existing systems and your team. That is why technology selection is the first thing we do in the Conceptual Phase of every project.

We work across a deliberately broad range of modern tools so that we can recommend what genuinely fits, rather than steering every project towards a single favourite. Below you will find the technologies we use, grouped by area, with a plain-language explanation of when we recommend each one.

  • Flutter
  • Xamarin
  • Microsoft C# / .NET
  • PHP
  • Laravel
  • Django (Python)
  • jQuery
  • JavaScript
  • Machine Learning
  • Artificial Intelligence
  • Cloud Migration
  • Azure
  • AWS
  • SEO

Mobile

Mobile application technologies

Flutter

Flutter is Google’s open-source toolkit for building apps for Android, iOS and other platforms from a single codebase. Its own rendering engine produces smooth, consistent interfaces across devices.

When we recommend it: for most new cross-platform mobile apps, particularly where a polished, branded interface and a single codebase for both platforms are priorities.

Mobile Applications

Xamarin and .NET MAUI

Xamarin allowed C# developers to build mobile apps on the .NET platform. Microsoft ended support for Xamarin in May 2024, and its successor is .NET MAUI (Multi-platform App UI).

When we recommend it: for organisations invested in the Microsoft ecosystem, for apps sharing code with existing .NET systems, and for migrating existing Xamarin apps to .NET MAUI.

Compare frameworks

Web

Web application technologies

PHP and Laravel

PHP powers a large share of the web, and Laravel is a mature, expressive framework with strong conventions for routing, authentication, queues and database access.

When we recommend it: for business web applications, portals and e-commerce solutions where fast development, wide hosting compatibility and a large talent pool matter.

Python and Django

Django is a “batteries included” Python framework with a built-in admin interface, a powerful ORM and strong security defaults.

When we recommend it: for data-heavy applications, internal tools that benefit from the admin interface, and projects that will integrate machine learning, where Python’s ecosystem is a natural fit.

JavaScript and jQuery

JavaScript brings interactivity to the browser. jQuery remains widely used in established applications and content management systems.

When we recommend it: JavaScript for every modern web interface; jQuery mainly when maintaining or refactoring existing applications that already depend on it.

Microsoft C# and .NET

.NET is Microsoft’s cross-platform framework for web APIs, enterprise systems and services, with strong typing, excellent tooling and close integration with Azure.

When we recommend it: for enterprise applications, organisations standardised on Microsoft technologies and systems with demanding performance or integration requirements.

Weighing up the two most common choices for business web apps? Read Laravel vs Django, and see our Web Applications service.

Cloud

Cloud platforms

Microsoft Azure

Azure offers hosting, databases, identity, serverless functions and DevOps tooling, and integrates naturally with Microsoft 365 and .NET.

When we recommend it: for businesses already using Microsoft products, for .NET workloads, and where integration with Microsoft identity services is important.

Amazon Web Services

AWS provides a very broad catalogue of cloud services, from virtual servers and managed databases to storage, messaging and machine learning.

When we recommend it: for workloads that benefit from its breadth of managed services, for teams with existing AWS experience, and for many open-source based stacks.

Both platforms operate data centre regions in South Africa, which can help with latency and data residency considerations. Our Cloud Migration service and cloud migration roadmap explain how we plan a move.

Intelligence and visibility

AI, machine learning and SEO

Machine Learning and Artificial Intelligence

Machine learning finds patterns in data to make predictions or classifications; AI more broadly includes language models, assistants and document understanding.

When we recommend it: when there is a clear business problem, such as forecasting, document processing or customer support, and enough quality data to support it. We handle personal information with POPIA in mind.

ML for small businesses

Search Engine Optimisation

Technical SEO ensures search engines can crawl, render and understand your web application, while performance and structured data improve how it appears in results.

When we recommend it: for every public-facing website, web application and online store. It is built in during development rather than added later.

Technical SEO guide

At a glance

Technology comparison

This summary shows where each technology typically fits. Every project is assessed individually, so treat it as a starting point for conversation rather than a fixed rule.

Technology Area Typical use Best suited to
Flutter Mobile Cross-platform Android and iOS apps New apps needing a consistent, branded interface
Xamarin / .NET MAUI Mobile C# mobile and desktop apps Microsoft-centric organisations; Xamarin upgrades
PHP / Laravel Web Business web apps, portals, e-commerce Rapid development and broad hosting options
Python / Django Web Data-driven apps and internal tools Projects with data science or ML components
JavaScript / jQuery Web Interactive interfaces All web front ends; jQuery for existing systems
C# / .NET Web and enterprise APIs, services and enterprise systems Enterprise integration and performance needs
Azure Cloud Hosting, identity, DevOps Microsoft ecosystems and .NET workloads
AWS Cloud Hosting, storage, managed services Broad managed-service needs; open-source stacks
Machine Learning / AI Intelligence Prediction, classification, automation Clear problems backed by quality data
SEO Visibility Crawlability, performance, structured data Any public-facing site or application
Key principle: we choose technologies based on your budget and the scale you need to reach. If your team already maintains a particular stack, that is an important factor, and we will weigh it carefully.

How we decide

The factors behind every technology recommendation

Technology decisions have long-lasting consequences. They affect how quickly your software can be built, how much it costs to host, how easily it can be maintained and who you can hire to support it in future. In the Conceptual Phase we weigh the following factors before recommending a stack.

  1. Budget

    Some technologies allow faster delivery of a first version; others cost more up front but reduce long-term maintenance. We match the choice to what you can sensibly invest now and later.

  2. Scale

    The expected number of users, volume of data and growth trajectory all influence architecture, hosting and framework choices.

  3. Existing systems and skills

    If your organisation already runs on Microsoft technologies, or your in-house team knows PHP or Python, building on that knowledge usually lowers risk and cost.

  4. Integrations

    Payment gateways, ERP and CRM systems, identity providers and third-party APIs each have preferred platforms and libraries that can tip the balance.

  5. Long-term support

    We favour mature, actively maintained technologies with healthy communities, so your software is not left stranded when a tool reaches the end of its life, as happened with Xamarin.

Further reading

Not sure which stack is right for you?

Our Discovery & Architecture Workshop recommends technologies and an architecture tailored to your budget and scale.

Let’s Talk View the workshop