Gemma 3

Dexit by 314e Corporation is an AI-native Intelligent Document Processing (IDP) engine tailored for healthcare document workflows. It ingests documents from any channel, fax, scan, email, upload, or API, and applies a purpose-built AI model to identify, extract, and interpret patient information from unstructured sources, scanned faxes, layered PDFs, and handwritten notes. It features a virtual fax server to eliminate paper workflows; automated classification and routing to match records to patient MPIs and drive documents into the right workflow; a drag-and-drop workflow builder enabling users to design complex, healthcare-specific processes with triggers, conditions, approvals, API calls, and communications; and governance tools for review, monitoring, and exception handling. Dexit aims to reduce labor burden, improve throughput, and let staff focus on higher-value tasks.

Xgen-small is an enterprise-ready compact language model developed by Salesforce AI Research, designed to deliver long-context performance at a predictable, low cost. It combines domain-focused data curation, scalable pre-training, length extension, instruction fine-tuning, and reinforcement learning to meet the complex, high-volume inference demands of modern enterprises. Unlike traditional large models, Xgen-small offers efficient processing of extensive contexts, enabling the synthesis of information from internal documentation, code repositories, research reports, and real-time data streams. With sizes optimized at 4B and 9B parameters, it provides a strategic advantage by balancing cost efficiency, privacy safeguards, and long-context understanding, making it a sustainable and predictable solution for deploying Enterprise AI at scale.