This paper presents Brillio’s LLMOps suite for building scalable, reliable LLM solutions across the full lifecycle: model selection, cost estimation, data preprocessing with PII masking and annotation, prompt engineering, distributed training, fine-tuning, deployment, and monitoring. It highlights accelerators for fine-tuning, inferencing, model health, responsible AI, and cost estimation, plus a governance framework spanning data, code, model, and domain pillars. A telecom case study shows a centralized LLM gateway that standardizes pipelines, speeds onboarding, and improves access management.

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