Why your LLM needs its own version of MonitoringTL;DR: LLMs don’t behave like normal services. They’re creative, a bit moody, and change under the hood without warning. Left alone, they surprise you at the worst time. You need LLMOps Monitoring: evals to measure quality, tracing to debug runs, and...Aug 15, 2025 · 4 min readblog.datachef.co
Improving Information Retrieval with Knowledge Graphs: Comparing VectorDB RAG vs Graph-Powered RAG on AWSIntroduction Large Language Models (LLMs) have become ubiquitous, but their tendency to “hallucinate” non-factual details remains a challenge. Retrieval Augmented Generation (RAG) was introduced to ground LLM responses in actual data by retrieving re...Feb 10, 2025 · 6 min readblog.datachef.co
How We Built an AI Team Roaster and Roasted Ourselves! (Featuring Amazon Bedrock)Introduction: This Christmas, we tried something new for our ceremony: a roasting party with an AI twist! We called it "Chef Roaster," in keeping with our DataChef theme. The concept was simple—provide AI with some information and roasting ideas, the...Dec 18, 2024 · 5 min readblog.datachef.co
Security and Data Governance in the Age of Large Language Models (LLMs)What’s at Stake? As the AI wave reshapes the tech industry, companies are racing to use its potential—whether to improve operational efficiency or deliver shiny new features to their customers. For organizations lacking the resources to self-host mas...Nov 28, 2024 · 5 min readblog.datachef.co
The Symphony of AI: How We Deduplicate Our Databases in the Age of AIFirst Movement: Tackling "Almost-Duplicate" Records in Our Database Understanding Our Mission At Datachef, we are on a mission to build our own interconnected knowledge base on Notion, where we organize records of our Hiring Pipeline linked to our ...Nov 11, 2024 · 5 min readblog.datachef.co
