{"id":3467,"date":"2025-07-08T09:00:00","date_gmt":"2025-07-08T16:00:00","guid":{"rendered":""},"modified":"2025-07-07T08:41:33","modified_gmt":"2025-07-07T15:41:33","slug":"model-ml-leverages-azure-for-innovative-agentic-service-in-highly-regulated-markets","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/startups\/blog\/model-ml-leverages-azure-for-innovative-agentic-service-in-highly-regulated-markets\/","title":{"rendered":"Model ML leverages Azure for innovative agentic service in highly regulated markets"},"content":{"rendered":"\n

The rapid pace of innovation in AI is unprecedented\u2014new models, techniques, and tooling emerge at a frenetic pace, demanding constant adaptation and ongoing iteration to stay competitive. That’s why Microsoft is always on the lookout for companies who keep pace with the latest technologies, even in the most challenging markets.<\/p>\n\n\n\n

Take Model ML<\/a>, an AI native workspace for financial services which not only keeps up with the incredible pace of evolving technology\u2014it drives it, deepening its offering with agentic capabilities and expanding integrations and automation layers with every release.<\/p>\n\n\n\n

With a flexible user interface (UI) and advanced agentic system, Model ML enables users to automate thousands of tasks and perform research at unprecedented speeds, across open data sources, financial data providers, internal documents, call transcripts, and more.<\/p>\n\n\n\n

In the world of finance, however, mitigating risk is often more important than the maintaining the speed of innovation. Enterprise customers\u2014especially in financial services\u2014have strict requirements around security, privacy, and compliance. That’s why Model ML\u2019s technology infrastructure is set up to push the boundaries of innovation while still meeting the rigorous standards through a two-layer approach:<\/p>\n\n\n\n

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  1. A hardened base of architecture, security controls, and change management procedures.<\/li>\n\n\n\n
  2. A rapid development layer that maintains security as a first principle.<\/li>\n<\/ol>\n\n\n\n

    Just as important, Model ML empowers teams with tools that allow them to drastically reduce time spent on routine analysis, slide deck review, and report generation as well as perform new kinds of analysis that were previously unfeasible at scale. All within a workspace that feels familiar to any modern office worker.<\/p>\n\n\n\n

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    Model ML has the potential to entirely transform the financial services industry. By combining a simple, user-friendly interface with a powerful agentic system that integrates seamlessly across all your data sources, Model ML helps you work smarter, uncover deeper insights, and significantly improve efficiency.<\/em><\/p>\nSir Noel Quinn, Group CEO at HSBC<\/cite><\/blockquote>\n\n\n\n

    Security at the core<\/h2>\n\n\n\n

    Using a flexible single-tenant deployment model on Azure tailored for the security and operational needs of enterprise customers, Model ML provides each single-tenant client with a dedicated environment based on private Azure Virtual Networks, supplying private, customer-specific instances of databases, in-memory cache, secure Azure Blob Storage, and Azure Service Bus for asynchronous messaging\u2014ensuring total isolation and compliance with SOC 2 and ISO 27001.<\/p>\n\n\n\n

    Critical enterprise requirements\u2014such as encryption-at-rest, high-availability clusters, automated backups, role-based access control, and private endpoints\u2014are fully implemented across the architecture. Monitoring and analytics are handled through Azure Monitor and Log Analytics, providing real-time insights, alerting, and audit trails for all activity.<\/p>\n\n\n\n

    With this foundation, onboarding a new customer can be achieved in as little as one hour\u2014from provisioning through to full operational status\u2014while maintaining robust security, compliance, and performance guarantees. With Azure\u2019s deep commitment to enterprise security and innovation, Model ML empowers organizations to adopt state-of-the-art AI at the speed their business demands, without compromising on trust or control.<\/p>\n\n\n\n

    Azure Kubernetes Service (AKS) and Virtual Machine Scale Sets power the application layer, enabling zero-downtime deployments and seamless horizontal scaling. In so doing, Model ML can grow from serving a single team to an entire division or business vertical without disrupting its existing customers.<\/p>\n\n\n\n

    Security is at the core of Model ML\u2019s approach to rapid innovation. The development process has been engineered to encourage and enhance innovation within tight security boundaries. This approach has three steps: Guard, Evaluate, and Control.<\/p>\n\n\n\n