Custom artificial intelligence solutions to automate processes and gain valuable insights.
What’s the point ?
At BlacX, we view AI Development & Integration as a holistic process that begins with understanding your organisation’s unique challenges and ends with the seamless adoption of intelligent solutions into your operational flow. We start by meeting the different teams and stakeholders in your organisation to identify where AI can deliver the greatest impact, whether it’s automating manual data workflows or predicting future trends for strategic planning. Once these goals are clear, we proceed with data collection and preparation, ensuring all relevant information—whether internal databases or external streams—is properly cleaned, structured, and annotated.
What you can expect
The core of our approach revolves around iterative model development, which involves prototyping machine learning or deep learning algorithms using frameworks such as TensorFlow or PyTorch. We then test these algorithms against your data to ensure their performance and reliability, making refinements as new insights emerge. After achieving a stable and accurate model, we integrate it into your existing systems by creating connectors and APIs that allow frictionless communication between the AI module and applications such as CRMs, ERPs, or specialised operational tools. This integration phase includes thorough performance checks and security reviews to uphold data sovereignty and meet compliance requirements.
Even after go-live, we remain closely involved to monitor how well the AI adapts to real-world conditions and shifting data patterns. Where necessary, we update the models and adjust system configurations, ensuring long-term continuity and scalability. Through this full lifecycle—from problem definition to ongoing support—our AI Development & Integration service empowers you to make better decisions, accelerate workflows, and discover new revenue opportunities.
Requirements Analysis & Feasibility Report
We begin by examining your business objectives, data availability, and technical constraints to identify high-impact AI use cases. This report outlines the project’s scope, model requirements, success criteria, and feasibility, setting the foundation for an effective AI solution.
Model Design & Prototyping
With goals in place, we develop initial machine learning or deep learning prototypes using your specific datasets. This deliverable demonstrates how the AI models will function, highlights performance metrics, and gathers critical feedback for refinements before large-scale deployment.
Systems Integration & Deployment
Once the models have been validated, we embed them into your existing technology ecosystem, whether on-premise or in the cloud. This stage includes building secure APIs, configuring microservices, and performing stress tests to ensure seamless operations under real-world workloads.
Maintenance, Optimisation & Handover
AI systems require ongoing attention to maintain accuracy and relevance. This deliverable covers routine model retraining, performance monitoring, and enhancements to accommodate new data patterns. Finally, we provide documentation and training so your teams can operate and iterate on the AI solution independently.
Explore our work
