お知らせ • Jun 04
Ruanyun Edai Technology Inc. Expands Cogni AI Into Private AI Platform For Archives, Institutional Records And Enterprise Data
Ruanyun Edai Technology Inc. announced an expanded strategic positioning for Cogni AI, the Company’s private-deployment AI document intelligence platform for archives, institutional records, enterprise data and knowledge transformation. Cogni AI is designed to transform scanned, handwritten, historical, administrative and enterprise documents into structured, searchable and workflow-ready data. The platform is intended for organizations that require AI-enabled document automation while maintaining customer-controlled data processing environments, including archives, schools and universities, public-sector service providers, regulated enterprises, legal departments, financial institutions, research organizations, and companies managing proprietary commercial, technical or development records. The Cogni AI product line is supported by approximately USD 1.73 million (RMB 11,700,082.00) in total contracted commercial activity across archive digitization, AI archive automation, software licensing, annual lease and deployment-related arrangements. Of such total amount, USD 415,947 (RMB 2,813,071.78) has been recognized as historical revenue in our books; USD 29,572 (RMB 200,000.00) is outstanding accounts receivable arising from a single annual-contract customer, and the remaining USD 1,284,481 (RMB 8,687,010.22) constitutes contracted but unearned deferred revenue subject to future revenue recognition. Company records reflect activity across both legacy digitization and newer AI archive automation use cases, including multiple signed customer contracts relating to the Company’s “AI large-model archive automation processing” software. Cogni AI’s product roadmap is built around a private-deployment architecture for intranet and customer-controlled environments. The architecture contemplates deployment through customer-owned servers or Company-provided appliances, internal data processing, multimodal OCR, automatic classification, desensitization, knowledge-base construction, graph databases, vector databases, object storage, local AI model inference, local license gateways, hardware dongles, local metering and offline update mechanisms. Cogni AI is being developed around four core modules: Intelligent Archive Factory, Archive Intelligent Q&A, Archive-Assisted Generation and Archive Knowledge Mining. Together, these modules are intended to support multimodal OCR, automatic catalog extraction, intelligent review, data desensitization, natural language search, cross-file association, evidence traceability, automated report generation, anomaly reporting and institutional analytics. Ruanyun believes Cogni AI can evolve beyond conventional OCR into a private data-refinery platform capable of converting legacy documents and dormant archives into structured institutional knowledge assets. Cogni AI may also complement the Company’s broader technology roadmap, including HanLink, YeeZo and future Formind platform initiatives, by providing a document-intelligence layer capable of transforming unstructured records, learning materials, institutional archives and legacy content into structured data that can be searched, analyzed, summarized and integrated into AI-enabled workflows.