Cubex Systems Pty Ltd

Legal name: Custom AI & Software Development on AWS

General business type: Technology services provider offering custom software and AI development

Headquarters country: Unstated

Regions of operation: Client list and service description indicate work with mid-market organisations across multiple sectors; geographic regions are not enumerated

Services and Capabilities

• Custom software development — design and delivery of cloud-native applications deployed on Amazon Web Services (AWS), including backend services and web APIs.
• AI and machine learning solutions — development and integration of machine learning models and AI-driven components into customer systems.
• Data platforms and analytics — implementation of data pipelines, data storage and analytics workflows for operational reporting and decision support.
• Systems integration — connecting existing enterprise systems, third-party services and cloud infrastructure to create end-to-end workflows.
• Automation and DevOps — automation of deployment, CI/CD pipelines, infrastructure-as-code and operational tooling on cloud platforms.
• Consulting and architecture — cloud architecture, solution design and technical advisory for digital transformation initiatives.

Industry Focus

• Fintech — development of software components and platform integrations suitable for financial services use cases.
• Health — delivery of cloud-based applications and data solutions for healthcare-related projects.
• Construction — software and systems to support construction workflows and project data management.
• Legal — development of software tools and integrations for legal services and case management.
• Agriculture — technology solutions for agricultural processes and data collection.
• Education — cloud applications and platforms for educational services and learning systems.
• E‑commerce and Ride Hailing — platform and application development for online commerce and mobility services.

Technology and Delivery Approach

• Cloud-first implementation with AWS as the primary deployment platform, using managed cloud services to host applications and data stores.
• Emphasis on data integration and building data pipelines to enable analytics and operational reporting.
• Use of automation and DevOps practices such as CI/CD pipelines and infrastructure-as-code to manage deployments and environment configuration.
• Application of machine learning and AI components where required, integrated into broader software systems.
• Delivery typically involves solution architecture, implementation of software and infrastructure, and integration with client systems.