Integrating Large Language Models (LLMs) into existing enterprise systems requires more than simple API calls. Real-world applications demand complex orchestration strategies to handle state, memory, security, and context limitations.
Managing Prompt Contexts
To scale conversational context without exceeding model limits, we employ Retrieval-Augmented Generation (RAG) coupled with vector database indexes. Only the most semantically relevant documents are injected into the LLM prompt, reducing token overhead and minimizing hallucinations.
Prompt Security
Prompt injection vectors present serious security vulnerabilities. We recommend establishing strict guardrail classifiers that pre-filter user requests and post-filter model completions before executing database writes.
