// Knowledge Base

Insights

Technical deep-dives, implementation guides, and strategic perspectives on building production AI systems.

Choosing the Right LLM Architecture for Enterprise Applications

A practical framework for evaluating when to use fine-tuned models vs RAG vs hybrid approaches based on your specific use case requirements.

How to design and implement continuous evaluation pipelines that catch quality regressions before they impact users.

Advanced techniques for improving retrieval quality including hybrid search, query expansion, and re-ranking strategies.

Why traditional software estimation fails for AI projects and how to create accurate timelines that account for inherent uncertainty.

Lessons learned from deploying autonomous agents in production environments. Error handling, fallbacks, and graceful degradation.

Implementing privacy-preserving AI systems that meet regulatory requirements without sacrificing performance.

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