Anchored in Data Sovereignty, the Engagement Enables the Legal Sector to Adopt Generative AI Safely and Confidently
Ridger Delivers MUX Private AI Deployment to Shum Wong & Co., Solicitors in Hong Kong
SINGAPORE – Media OutReach Newswire – 30 October 2026 – Ridger, an AI infrastructure company, today announced the official delivery of its MUX private AI solution to Shum Wong & Co., Solicitors in Hong Kong. The solution features MIMO, the world's first AI-native storage system, making Shum Wong & Co., Solicitors the first law firm in Hong Kong Northern Metropolis to deploy it.
Representatives from Ridger, Shum Wong & Co., Solicitors, xFusion, and Fadada's RicheeAI team attended the delivery ceremony. During the event, Ridger presented the firm with the "Global AI Pioneer Law Firm" certificate in recognition of its forward-looking investment in private AI infrastructure.
The solution brings together AI-native storage and compute infrastructure, a dedicated large language model (LLM) environment, and AI applications tailored to legal workflows. Operating entirely within the firm's own security perimeter, it marks a significant step toward enabling Hong Kong's legal profession to harness the productivity of generative AI while safeguarding client data and meeting compliance requirements.
About the Deployment
In space-constrained Hong Kong, Ms. Careen H.Y. Wong, Founding Partner of Shum Wong & Co., Solicitors and Vice President of The Law Society of Hong Kong, set aside room in the Firm's latest office in the Northern Metropolis for a standard equipment rack, ready for on-premise AI. It is more than a space decision: it reflects her view of the future of legal services—that while harnessing AI to improve efficiency, a firm must retain control of its data and technology boundaries, so that sensitive materials are always properly protected.
Under the engagement, Ridger built a privately owned, independently operable AI foundation for Shum Wong & Co., Solicitors, comprising high-performance storage and data infrastructure optimized for AI workloads, together with a dedicated LLM platform over which the client retains full control of model weights and the inference environment. The platform supports use cases including contract review and risk flagging, legal research and case-law retrieval, large-scale document review in due diligence, drafting and multilingual translation of legal documents, and internal Knowledge Base question answering. It also provides role-based access control, tiered permissions, comprehensive audit trails and content provenance to meet enterprise-grade governance requirements.
Called MUX, the private solution lets the firm begin with no barrier and without capital-intensive build-out or a dedicated server room, scaling on demand; it natively supports Hong Kong's common law system and integrates seamlessly with existing systems such as email, document management and calendar, embedding AI into lawyers' daily work. MUX can be ordered directly through Ridger's website (https://ridger.tech), out of the box.
The delivery reflects the collaboration of legal expertise, AI infrastructure, compute platforms and industry applications: Shum Wong & Co., Solicitors defined the requirements for data confidentiality and on-premise deployment from its actual practice; Ridger provided the end-to-end MUX solution and led its design and integration; xFusion supplied the FusionXpark local AI compute platform and technical support; and Fadada provided the Richee Legal AI Agent Platform, leveraging specialized AI agents and skills to support lawyers in their daily work and improve workflow efficiency. Ridger notes that while an AI model determines capability for a moment, AI infrastructure determines long-term competitiveness.
Why Private AI Matters for the Legal Sector
1. Safeguarding client confidentiality and legal professional privilege
Client materials, transaction documents and dispute information handled by law firms are protected by legal professional privilege (LPP) and strict professional duties of confidentiality. Disclosure to third parties—including public cloud services—may be treated as a waiver of privilege, causing it to be lost and the materials to become disclosable in subsequent proceedings. Private deployment keeps storage, processing and inference entirely within the firm's own environment, with no disclosure to external providers, preserving privilege and confidentiality at source.
2. Embedding data sovereignty and regulatory compliance
The solution aligns with Hong Kong's Personal Data (Privacy) Ordinance (Cap. 486) and is designed with reference to the Privacy Commissioner's "Checklist on Guidelines for the Use of Generative AI by Employees" and the "Model Framework on AI: Personal Data Protection," as well as The Law Society of Hong Kong's 2024 position paper on the impact of AI on the legal profession and the Manifesto on "Legal Ethical Code of Conduct Regarding the Deployment of AI." It embeds the principles of lawfulness, transparency, traceability, interpretability, security and appropriate human oversight into a unified AI governance framework.
For a firm handling cross-border work, the same private environment also addresses the requirements of the major jurisdictions: for Mainland China, it aligns with the Personal Information Protection Law, the Data Security Law and data-export mechanisms such as security assessments and standard contracts; for Europe, it maps to the EU General Data Protection Regulation (GDPR) and standard contractual clauses; for the United States, it meets the confidentiality and competence duties under the ABA Model Rules of Professional Conduct and Formal Opinion 512 on generative AI. Because data always remains within the firm's own perimeter, the firm can confidently meet local data-confidentiality and regulatory expectations wherever its clients are based.
3. Eliminating the hidden risk of "shadow AI"
Where a firm offers no convenient, approved AI tool, individual lawyers may turn to consumer-grade public chatbots for work, creating "shadow AI" that sits outside IT and compliance visibility—unapproved, unlogged and unaudited, with unknown data flows and no clear accountability. MUX channels that demand into a single, visible, auditable controlled environment, giving lawyers the efficiency they want while bringing every use under the institution's governance and oversight.
4. Keeping institutional knowledge within the firm
The case law, templates and practical know-how accumulated by a firm are core competitive assets. A private platform continuously refined on the firm's own corpus keeps these assets within the institution and compounds their value over time, rather than depositing them with an external vendor.
5. Ensuring control and business continuity
Private deployment insulates the firm from external API changes, model versioning, service outages or shifts in vendor strategy, giving it full control over capabilities, upgrade timing, cost and availability — a foundation for durable, long-term AI adoption.
Executive Quotes
"For industries built on trust and confidentiality, such as the law, the value of AI should never come at the price of data sovereignty," said Ray Hu, General Manager Asia-Pacific Region of Ridger. "Private deployment lets a firm turn generative AI into auditable, governable and sustainable productivity without crossing confidentiality lines. We are proud to set this benchmark with Shum Wong & Co., Solicitors"
Ray Hu, General Manager Asia-Pacific Region, Ridger
"In Hong Kong, office space is scarce and precious, but data sovereignty is worth setting aside a place for. Building our own AI infrastructure lets us embrace AI while always safeguarding our clients' trust and the boundaries of our profession."
Careen H.Y. Wong, Founding Partner, Shum Wong & Co., Solicitors, Solicitors
Hashtag: #Ridger #MIMO #MUX #PrivateAI #LegalAI #AIInfrastructure #HongKong
https://ridger.tech
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The issuer is solely responsible for the content of this announcement.
Ridger Company Limited
Ridger is a technology company focused on data and storage infrastructure for the AI era. The company provides private, high-performance AI infrastructure and solutions that enable enterprises to deploy and run large models and AI applications within their own security perimeter. Through its proprietary storage and data management technologies, Ridger helps clients safeguard data sovereignty, security and compliance while fully realizing the business value of artificial intelligence.
