Not all agents are the same, especially when it comes to enterprise tasks Building AI agents for CRM is much more than deploying a Large Language Model (LLM). An enterprise agentic system needs…
From Internet Wild West to Agent Interoperability Picture this: It’s 1981. In a university computer lab, a researcher sits before a glowing green terminal, attempting to access data from another institution. After hours…
The Challenge with Flows Today Salesforce flows sit at the heart of modern CRM automation, yet authoring them still requires a unique mix of declarative drag‑and‑drop and Apex know‑how. To ease this process,…
Behind every seamless customer experience is a complex, ever-changing codebase. When issues arise in that codebase, developers face a deceptively hard task: locating the exact part of the code that needs fixing. This…
In today’s world, where customer expectations demand instant and seamless experiences, Salesforce Data Cloud is redefining how businesses harness the power of their data. It transforms how businesses turn fragmented information into dynamic,…
We’re in the midst of a digital agent revolution — where AI is no longer just supporting tasks, but actively driving business processes, from handling service requests to closing complex B2B sales deals.…
Architecture, Training and Dataset Github Code: https://github.com/JiuhaiChen/BLIP3o Models: https://huggingface.co/BLIP3o/BLIP3o-Model Demo: https://huggingface.co/spaces/BLIP3o/blip-3o Motivation OpenAI’s GPT-4o has demonstrated state-of-the-art performance in image understanding, generation and editing tasks. Emerging hypotheses of its architecture suggest a hybrid…
As businesses increasingly turn to AI-driven customer relationship management (CRM) solutions, safeguarding user interactions from harmful or inappropriate content becomes essential. Salesforce’s large language models (LLMs) are trained on vast datasets, which occasionally…
xGen-small is an enterprise-ready compact LM that combines domain-focused data-curation, scalable pre-training, length-extension, instruction fine-tuning, and reinforcement-learning to deliver Enterprise AI with long-context performance at predictable, low cost.