The Grids and Guides Blog
Technical depth on RAG pipelines, LLM development, MLOps, and enterprise AI adoption. Written by the team at Grids and Guides based on real production experience.
How to build production document AI pipelines — OCR, LLM-based extraction, structured output, validation strategies, and accuracy measurement for enterprise document processing.
MLOps guide for production ML systems — model serving, CI/CD pipelines, experiment tracking with MLflow, drift monitoring, and operational practices that keep models accurate.
Realistic breakdown of enterprise AI costs — compute, APIs, data engineering, team, maintenance, and the hidden costs that blow AI project budgets. A guide for CTOs and tech leaders.
How to build enterprise AI agents that work in production — agent architectures, tool design, multi-agent systems, failure modes, and when agents are the wrong choice.
When and how to fine-tune LLMs for enterprise use — LoRA vs QLoRA vs full fine-tuning, dataset preparation, evaluation, and production deployment considerations.
End-to-end guide to building a production RAG pipeline — chunking strategies, embedding model selection, vector databases, retrieval optimisation, and evaluation with RAGAS.
How EdTech platforms scale AI from pilot to millions of users — data pipelines, MLOps architecture, governance patterns, and production lessons from real deployments.
Build a fully on-premise AI DevOps stack for manufacturing — open-source tools, hardware specs, GDPR compliance patterns, and production deployment lessons from real factory implementations.
