For decades, digital transformation in regulated industries has focused on improving customer-facing interfaces, while backend systems have remained fragmented and inefficient. Ushur’s new Agentic Experience Framework (AXF) aims to change that by modernising the core architecture behind enterprise service delivery.
Rather than relying on traditional workflows or generic AI tools, Ushur’s AXF introduces a specialised, domain-aware approach tailored to the complex environments of healthcare, insurance, and financial services.
It embeds industry-specific knowledge directly into AI agents, enabling them to understand processes like claims, prior authorisations, and KYC requirements — not just process them.
Security and trust are built into the framework’s foundation. AXF aligns with global standards such as HIPAA, GDPR, SOC 2, and ISO 27001.
Its enterprise-grade guardrails protect data, enforce access controls, and proactively monitor for unsafe behaviours, enabling organisations to scale AI adoption with confidence.
At the heart of the framework is a Multi-Agent System (MAS), where individual agents collaborate to manage complex, end-to-end service journeys. These agents are powered by two protocols: the Model Context Protocol (MCP), which enables structured, secure data access and tool integration, and the Agent-to-Agent Protocol (A2A), which supports inter-agent communication and coordination across systems.
AXF also revolutionises knowledge work by using AI to process unstructured data, reducing manual tasks and freeing employees to focus on high-value activities. Its adaptive automation model, known as Agentic Declarations, moves away from static workflows and allows the system to dynamically plan and execute based on desired outcomes.
Ushur’s agentic approach offers a scalable, secure, and intelligent foundation for digital transformation in highly regulated sectors — redefining how enterprises deliver faster, smarter, and more human-centric service.
Read the full blog from Ushur here.
Source: https://fintech.global/
