Yalantis Machine Learning Services – Custom Solutions at Scale

Yalantis MLOps and Machine Learning Services help companies build intelligent, future-ready solutions that automate processes, uncover insights, and create competitive advantages — all powered by AWS. We combine deep ML expertise with end-to-end engineering to ensure your models deliver business value at scale and in production.

We cover the full machine learning lifecycle, using AWS-native services to accelerate time to value:

• Data preparation and feature engineering with AWS Glue, Amazon S3, and Amazon SageMaker Data Wrangler.
• Model development and training using Amazon SageMaker, supporting popular frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Testing, evaluation, and deployment with SageMaker Pipelines, SageMaker Model Monitor, and AWS Lambda for serverless model inference.
• Continuous integration and delivery (CI/CD) of ML models using AWS CodePipeline, Amazon CloudWatch, and Amazon EventBridge for automated monitoring and event-driven workflows.
• Generative AI Enablement using Amazon Bedrock to seamlessly integrate leading foundation models (Anthropic Claude, AI21 Jurassic, Stability AI) for use cases like intelligent document processing, conversational AI, and content generation.

Whether you're building predictive analytics for customer behavior, anomaly detection in supply chains, or intelligent automation for operations, our team tailors every solution to your business domain and technical stack.

Our services include:

• Custom ML Model Development: Build business-specific models using AWS-native ML environments and frameworks, ensuring seamless integration with your AWS data lake and enterprise systems. Leverage Amazon Bedrock for Generative AI use cases like document summarization, content creation, and natural language understanding.
• MLOps & Continuous Learning Pipelines: Automate model retraining, monitoring, and deployment with Amazon SageMaker MLOps, SageMaker Model Registry, orchestration through AWS Step Functions, and event-driven automation via Amazon EventBridge. We also integrate tools like MLflow and Kubeflow, with primary orchestration on AWS.
• AI Strategy Consulting: Identify high-impact AI use cases, ensure ethical implementation aligned with AWS Responsible AI Principles, and design scalable architectures following the AWS Well-Architected Framework.

We start every engagement with a feasibility analysis and Proof of Concept (PoC), progressing to robust architecture and full-scale deployment. Yalantis bridges the gap between model development and operational excellence, delivering ML solutions that are cloud-native, real-time responsive, and enterprise-ready.

By leveraging AWS services for data ingestion, processing, and model management — including Amazon Bedrock for generative AI — we help you unlock AI-driven innovation securely, at scale, and fully aligned with your business objectives.