Tag: Data & AI

Context Relevance tells you whether retrieval handed the model the right chunks, so you can catch a bad answer at its source instead of blaming the prompt.

A RAG evaluation model scores retrieval and generation separately, so you catch bad answers in testing instead of hearing about them from an annoyed user.

A RAG pipeline turns documents into answers in four stages, and every stage is a chance for retrieval and permissions to fail while everyone blames the model.

Vector databases retrieve by meaning, not keywords, and building that layer once keeps every AI feature from starting over.

Progress intends to acquire Domo’s AI and data platform business, bringing together complementary strengths to help organizations get more value from their data and AI investments. By adding Domo’s cloud-native AI data readiness platform, Progress will help customers better connect, govern and act on enterprise data across systems, applications and business processes. Together, Progress and Domo aim to give organizations the trusted foundation they need to use AI more confidently, make better decisions and accelerate innovation.