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This post is cowritten by Jeremy Jacobson and Rado Fulek from Ricoh. This post demonstrates how enterprises can overcome document processing scaling limits by combining generative AI, serverless architecture, and […]

Canvas in AI Mode is now available for everyone in the U.S. Plus, it can now help you draft documents or build interactive tools. ​ 

Learn more about Google DeepMind’s Project Genie and how to write prompts to create your own worlds. ​ 

Gemini 3.1 Flash-Lite is our fastest and most cost-efficient Gemini 3 series model yet. ​ 

In this first post in a two-part series, we examine how retailers can implement a virtual try-on to improve customer experience. In part 2, we will further explore real-world applications

This post was co-written with Davesh Maheshwari from Lendi Group and Samuel Casey from Mantel Group. Most Australians don’t know whether their home loan is still competitive. Rates shift, property

Organizations face challenges in quickly detecting and responding to user account security events, such as repeated login attempts from unusual locations. Although security data exists across multiple applications, manually correlating

Large language models (LLMs) perform well on general tasks but struggle with specialized work that requires understanding proprietary data, internal processes, and industry-specific terminology. Supervised fine-tuning (SFT) adapts LLMs to

Customer service teams face a persistent challenge. Existing chat-based assistants frustrate users with rigid responses, while direct large language model (LLM) implementations lack the structure needed for reliable business operations.

Are you struggling to balance generative AI safety with accuracy, performance, and costs? Many organizations face this challenge when deploying generative AI applications to production. A guardrail that’s too strict