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An Integrated Deployment Ecosystem

Our solutions are available as backend APIs, offering flexible integration options for frontends. Organizations can integrate these APIs with existing frontends or have a custom frontend built and connected by our team.

The diagram outlines a Scalable ML Architecture with three components: **Data Acquisition & Integration** (RDBMS, NoSQL, Hadoop), **Model Fitting, Training, and Evaluation** (scalable model processing), and **Apps Deployment** (web, mobile, desktop, PWA). APIs connect these stages, supported by platforms like AWS, Microsoft, and Google Cloud.

Given the significance of big data and machine learning, data protection and privacy are our foremost priority. Our systems can operate flexibly on cloud, on premise, offline, without connecting to external APIs, ensuring they meet organizational security requirements. Additionally, we partner with leading cloud providers for seamless deployment.

The image shows a three-tier infographic outlining key machine learning stages: **Deployment to Apps** (deploy models to various platforms), **Model Fitting, Training, and Evaluation** (scalable model training and evaluation), and **Data Acquisition & Integration** (efficiently handling diverse data sources).
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