← Back to projects2025-02-20
Azure RAG Specialist
Prompt-engineered chatbot for a regulated knowledge base using Azure OpenAI, Cognitive Search, and vector stores tuned for latency.
RAGAzurePrompt Engineering
Outcome
Cut retrieval latency by 90% while improving answer precision.
Stack
Azure OpenAICognitive SearchAzure FunctionsRedis Vector DBApplication Insights
Related service
RAG Systems
Enterprise retrieval systems, knowledge assistants, and response-quality work for teams that need grounded answers and lower latency.
Explore RAG Systems →Problem
Subject-matter experts needed bilingual answers referencing policy PDFs, Confluence articles, and SQL tables. Previous bots timed out or hallucinated under load.
Solution
- Built ingestion workers in Azure Functions that normalize data into embeddings stored in Redis.
- Crafted prompt templates with system tests for Spanish/English parity and fallback chains for missing context.
- Added telemetry with Application Insights and dashboards tracing cost per conversation.
Result
Response time fell from ~12 seconds to under one, and confidence scores improved thanks to adaptive reranking and automatic citation enforcement.
Projects
Need this kind of system in your team?
I help teams ship document agents, RAG copilots, computer vision pipelines, and operational automations without the usual prototype-to-production gap.