Fluxus provides tailored Machine Learning solutions designed to solve real-world business challenges. Drawing on our extensive AWS expertise, we deliver end-to-end development that spans model creation, training, deployment, and seamless integration into your existing systems.
We believe that ML should drive tangible benefits, not theoretical gains. For instance, when working with True Digital Group in Thailand, our team developed an AI-based content moderation system for their In-Trend platform. This reduced moderation costs by 40x, cutting costs per article from $2 to $0.05, and increased accuracy over manual processes by 91%. Our pragmatic approach ensures that the models we develop are aligned with your business goals, delivering measurable outcomes from day one.
Our Machine Learning approach covers the full lifecycle. By blending Data Science and Data Engineering, we handle not just the creation of models but also their deployment and operationalization. We prioritize modular, scalable solutions built on AWS’s serverless architecture, resulting in ML pipelines that are resilient, cost-effective, and adaptable as your business grows. For instance, our work on image analysis for content moderation leveraged AWS Rekognition and custom-built filters, offering scalable, on-demand processing that fit seamlessly into True Digital’s infrastructure.
A key aspect of any effective ML system is its ability to learn and adapt over time. We implement automated, continuous learning processes that ensure models evolve alongside your data and requirements. In the case of our IoT-based fall detection system for elderly care, the model adapts to new data from edge device sensors, maintaining accuracy and improving safety without disrupting privacy - a practical example of ML continuously improving in the real world.
At Fluxus, we don't just build state-of-the-art ML solutions; we make sure they are sustainable, scalable, and directly relevant to your business needs—helping you extract real value from your data.
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