1. Organizations have moved beyond pilots and are embedding LLMs into production workflows across customer support, finance, security, and software delivery. 2. LLM observability mitigates risks like hallucinations, bias, compliance breaches, and runaway costs. 3. LLM observability requires prompt/response tracking, hallucination detection, drift monitoring, RAG pipeline visibility, and long-term context tracing. 4.

Fivetran powers the data foundation behind Snowflake’s next-generation AI-driven analytics, enabling users to talk directly to their data.

At this year’s Big Data London, Keboola CEO Pavel Doležal sat down with data expert Christina Stathopoulos on EM360Tech’s Don't Panic, It’s Just Data podcast to explore what’s next in enterprise data automation. The conversation centered on a quiet but powerful shift in how AI, particularly large language models (LLMs), is changing the way organizations interact with their data platforms - not just by querying them, but by acting on them.

Disclosure management has traditionally relied on Microsoft Office products like Excel and Word as workhorses for finance teams. However, the modern business landscape demands a more efficient and integrated approach to ensure accurate and timely financial disclosures.