Systems | Development | Analytics | API | Testing

Why we ditched frontier AI agents and built our own

At Bitrise, our goal is to help developers speed up their builds and automate tedious processes, from first code commit all the way to production release. To advance this mission, we began exploring how AI can improve developer workflows. Over recent months, I joined a small, fast-moving tiger team focused on cutting through hype to identify valuable AI capabilities. Our goal: to design, develop, and maintain production-grade AI features that truly help developers.

Snowflake CEO Sridhar Ramaswamy Announces Snowflake Intelligence General Availability

Snowflake CEO Sridhar Ramaswamy shares details about how he uses Snowflake Intelligence every day to prepare for meetings, get real-time sales forecasts, review account details, and more. Learn how Snowflake Intelligence can help you get more from your data every single day.

Snowflake Intelligence: All Your Knowledge. One Trusted Enterprise Agent.

Snowflake Intelligence is an enterprise intelligence agent that puts insights at every user’s fingertips. It enables every employee to answer questions, no matter how simple or complex, in natural language. They can move beyond the “what” to uncover the critical “why,” fostering a new data culture where every employee can derive deep insights and take timely action for faster outcomes. Gain insights from structured and unstructured data with Snowflake Intelligence via this quickstart.

Unlocking Enterprise AI: How Qlik and Snowflake Intelligence Empower Data-Driven Decisions

The enterprise AI landscape is transforming rapidly. On November 4th, Snowflake Intelligence—a breakthrough agentic AI platform built on the Cortex AI suite—ushers in a new era of business insights. With support for natural language querying (NLQ) and generation (NLG), organizations can interact with their data conversationally, unearthing real-time intelligence directly from complex, multimodal sources.

LLM Observability Tools in 2025

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.