The ORIGIEN AI Development and Service Platform is an efficient, low-threshold, open and secure one-stop enterprise-level AI middle platform. Using industry-leading technologies, it builds a full-link, end-to-end AI algorithm development suite and tools. It integrates complex model research and development with service delivery, supporting full-stack machine learning, deep learning, and lifecycle management of large model training and reasoning. The platform helps enterprises achieve the goal of "managing computational power, building models, and utilizing services effectively."
Under the context of intelligent transformation, industries need to empower enterprise decision-making, process automation, and ease of interaction through AI technology, yet still face many issues and challenges.
Repetitive Construction, Unstandardized ProcessesAI models for various business departments number in the hundreds or even thousands, with each department building and managing independently. The inconsistency of modeling environments leads to redundant development, making unified model management and capability reuse difficult.
Scattered Assets, Difficult to ManageThe outputs of each stage of the model lifecycle lack unified management. It is common to find model code stored locally, making effective management of model resources such as code, data, documents, and models a challenge.
Lack of Continuous Monitoring and Early Warnings, Uncontrollable RisksThe dimensions for daily monitoring of models are often incomplete or prone to omission. Real-time monitoring, timely iteration, updates, and early warning alerts are necessary to prevent risks.
Based on the new MLOps concept and using industry-leading technologies, the ORIGIEN AI platform offers a full-link, end-to-end AI algorithm development suite and tools. It integrates the development of complex models and services, supporting full-stack models, machine learning, deep learning, and lifecycle management of large model training and reasoning. By providing enterprise-level AI service capabilities, the platform ensures the unified management and standardized service of AI models, enabling “small and large model collaborative” management and meeting common industry needs such as "easy algorithm development, computational power centralized management, ultra-large-scale AI training, AIPaaS services, and AI security and trustworthiness." It helps enterprises achieve intelligent upgrades.
Intelligent Risk Control| Targeting financial risk control scenarios, the platform supports risk control modeling, scoring cards, and quantitative evaluation and application for pre-loan, mid-loan, post-loan, and anti-fraud activities.
Intelligent Marketing| AI-driven recommendation for precision marketing, deeply analyzing and understanding customer, product, and behavioral characteristics to build AI models that support a digital marketing ecosystem.
Intelligent Services| Serving as a foundational platform for NLP, CV, and multimodal AI-human interaction technologies, it helps build applications for intelligent customer service, smart conversations, and unmanned banking.
Intelligent Operations| The platform provides deep learning capabilities, integrating RPA for wide application in intelligent order auditing, automated financial reimbursement, and other large-scale operations replacing manual tasks.
Intelligent Audio-Visual| Built on the platform, computer vision applications enable internet content review, video recognition and analysis, and digital twin scenarios like digital avatars.
Driven by business scenarios, the platform supports a standard process for data exploration, from data mining, model development to AI application. It brings qualitative improvements to the efficiency and effectiveness of business processes, offering users a new experience and progressively supporting the innovation of business scenarios. Over time, this process builds a repository of modeling features, an algorithm library, and a financial scenario model library with intellectual property rights owned by the bank.
Building a Shared AI Capability Center for the Entire Bank
By connecting the data ecosystem to the AI ecosystem, the platform supports data operations, feature operations, and model operations, ensuring data security and privacy, and fully supporting personalized big data mining and applications.
Clear Architecture Positioned on Enterprise Resources
By integrating a large amount of internal and external data from the bank’s data middle platform, the system supports the integration and management of external general-purpose models (with low complexity) and the personalized AI capabilities for the banking and other key industries.
Empowering Business Scenarios with AI
The AI middle platform supports the application of full-scenario innovation, driving various business roles within the bank to participate in data value transformation. It builds an AI platform that is accessible and analyzable by everyone, establishing a positive AI culture for business scenario innovation.
- Full Lifecycle
Supports the entire process of data, modeling, management, service, and operations.
- Inclusivity
Low-code modeling techniques such as automation and drag-and-drop.
- Centralization
Unified management of computational power, elastic scheduling, and continuous monitoring.
- Financial Expertise
Financial models, real-time capabilities, and security features.
