LLMOps
consulting services
Key Components of the LLMOps
process at ELEKS
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Data engineering and management
Our data engineering specialists implement robust data collection, preparation, and storage processes explicitly optimised for large language models. We build efficient data pipelines that ensure high-quality training datasets through labelling, cleaning, and augmentation techniques. Our data management approach creates the foundation for reliable model performance while addressing privacy concerns and regulatory requirements.
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Experimentation and model evaluation
We test, evaluate, and fine-tune large language models against performance standards and business objectives. Our experimentation frameworks enable controlled testing environments, where we refine prompt engineering techniques and analyse model outputs. We use evaluation metrics to ensure your LLM-powered custom applications deliver accurate and relevant results across different use cases.
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Model deployment and monitoring
Our LLMOps experts ensure the smooth deployment of large language models into production environments. We establish robust model monitoring systems that continuously track model performance and alert teams to potential issues before they affect users. Our approach incorporates human feedback loops for ongoing improvement while maintaining the operational stability of your AI systems.
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Pipeline management
Our team designs and implements end-to-end pipelines to orchestrate data flow, model training, evaluation, and deployment processes. Our pipeline management approach enables consistent reproducibility of results while supporting continuous integration practices that accelerate development cycles. By automating complex workflows, we help you dcale your LLMOps capabilities efficiently while maintaining thorough quality controls throughout the entire model lifecycle.
Why choose ELEKS for LLMOPs consulting
