Case Studies

From the initial stage of project incubation, self-developing the technical architecture, team establishment, and full-chain commercialization implementation, we have abandoned the general audio diffusion models with poor adaptability and constructed an exclusive healing audio technology system. Relying on RAVE neural audio synthesis, physical acoustic simulation, and high-precision audio feature engineering, combined with the principles of brain nerve regulation, we quantify the non-standard chanting gong healing experience into modifiable acoustic parameters such as MFCC spectra, overtones, and spatial reverberation. We innovatively established an AI guardrail parameter constraint mechanism, and consolidated industry professional experience into model generation thresholds and rules. We established standardized research and development iteration and A/B testing processes, connected the closed loop of users' implicit feedback data, and through incremental fine-tuning of the model, built a self-iterative data flywheel to achieve high-precision, low-computing power, and low-latency personalized healing.

Based on the IFS integrated financial system, an integrated bottom-level architecture for business and finance is established, and the all-domain intelligent treasury management middle platform is implemented. The cross-channel bank-enterprise direct connection links are connected, the multi-level group fund pool system is restructured, and the unified governance of account ledgers, intelligent fund collection, and dynamic balance adjustment are achieved. Through the data platform, multi-source heterogeneous data integration and main data standardization governance are completed, achieving the same-source interconnection of business, funds, information, and contracts. Core capabilities such as LSTM time series prediction, AI rule risk control engine, and OCR intelligent parsing are embedded, and scenarios such as rolling cash flow prediction, automatic bank-enterprise reconciliation, risk quantitative warning, investment and financing optimization, and foreign exchange intelligent hedging are implemented. A full-closed digital and intelligent system for pre-event prediction, in-event control, and post-event traceability is constructed, promoting the transformation of fund management from compliance guarantee to lean operation and value creation.

Based on the AI RAG retrieval and enhancement generation technology, a private financial knowledge base for enterprises is built, collecting all-dimensional data such as financial regulations, latest tax and finance policies, historical difficult cases, and practical templates. Structured classification and version iteration management are completed. The enterprise OA, reimbursement, and accounting systems are connected, and five core capabilities are deployed: permission-based intelligent question answering, pre-compliance pre-review, policy intelligent push, audit traceability evidence, and experience accumulation reuse. A lightweight implementation path is adopted to quickly complete data collection, knowledge base construction, system integration, and function launch. The model accuracy and knowledge content are continuously iterated and optimized. Financial work is upgraded from manual事后纠错 to an intelligent, standardized pre-risk control and all-staff self-enabling mode.

Build an exclusive Agent intelligent operation platform for foreign exchange, and construct a standardized and iterative AI treasury technology system. Through hierarchical structured prompts to standardize and define the professional output model for foreign exchange exposure estimation, risk hedging, and compliance accounting, and by integrating domestic and foreign local regulatory rules through a hierarchical RAG policy knowledge base, break down information barriers and eliminate model illusion issues. Relying on the configurable Skills skill engine, standardize and automate complex scenarios such as exchange rate stress testing, cross-border funds settlement, and hedging accounting. Combine the model iteration mechanism to enhance the accuracy of business operations. Optimize hedging plans and cross-border transfer paths through dynamic risk reward strategies. Continuously align with the group's risk-neutral control requirements based on expert feedback, and build a comprehensive and closed-loop intelligent control system for foreign exchange, covering pre-event prediction, in-event control, and post-event iteration.

Relying on the IFS integrated business and finance platform and the standardized master data base, combined with advanced AI algorithms to reconstruct the full-chain control system of supply chain finance, achieve compliance efficiency, risk controllability, and asset appreciation. Connect multiple source interfaces of ERP, SCM, logistics, taxation, and banks, build a supply chain finance data lake, complete the governance of all-domain master data, and realize the source-based collaboration of the four flows of business, capital, goods, and tax. Unify the business processes and internal control norms of all scenarios such as order financing, receivable financing, and inventory pledge, and achieve centralized and online operation of scattered businesses. Build an AI dynamic credit rating system, iteratively adjust the enterprise credit limit in real time; combine the industrial cycle, risk factors, and market interest rates to build an intelligent pricing model, achieving precise matching of risks and returns.Relying on AI anomaly screening to intercept false trade and capital risks in advance, form a full-closed system of standardized control and intelligent decision-making, and comprehensively improve the efficiency of fund turnover and asset quality in the industrial chain.

Based on the IFS end-to-end control system, a three-layer AI fund management platform with capabilities of penetration visibility, intelligent decision-making, and dynamic collaboration is built to achieve digital and intelligent upgrades in the group's investment and financing as well as liquidity management. The penetration visibility layer relies on bank-enterprise direct connection and RPA automation capabilities to achieve real-time aggregation of all bank accounts, credit lines, debts, and wealth management data within T+0 period, and to complete unified control of the entire fund pool. The intelligent decision-making layer is equipped with an LSTM time series prediction model, combined with business order data to generate rolling fund gap warnings, and relying on NLP large models to intelligently parse financial contract texts, it builds a financing comparison and quantitative scoring engine. The dynamic collaboration layer deploys an ALM (Asset-Liability Management) asset-liability management engine. Through Monte Carlo simulation, it can real-time calculate core indicators such as LCR (Liquidity Coverage Ratio) and interest rate gap, automatically output investment and financing portfolio adjustment strategies and multi-scenario stress test results, and achieve controllable fund risks and optimal returns.

Build a universal aggregated payment gateway, split the Payin deposit channel pool, achieve physical isolation of virtual rewards, subscription business and physical e-commerce business channels, connect local acquiring institutions to enhance transaction stability, simultaneously reuse the gateway base to complete the standardization of payout withdrawal message packets. Replace the WebView cashier mode with the native embedded payment SDK, implement the EMV-3DS2.0 certification system, dynamically realize transaction exemption and challenge verification, meet the PSD2-SCA compliance requirements, connect the card organization service to achieve intelligent card token renewal through card deduction. Build a rule and data-driven intelligent routing engine, precisely schedule based on multiple dimensions of factors, configure circuit breakers and stepwise retry mechanisms. Link the device fingerprint and risk control engine to build a two-layer risk control model, pre-emptively intercept transaction risks, unify the PSP message conversion and error code system, conduct full-link tracking and traceability, simplify the PCI-DSS compliance scope and reduce compliance costs.

Build a platform-level managed digital wallet core system, relying on the general ledger engine to establish a three-level segregated account system for users, creators, and merchants. Link and aggregate the payment gateway to uniformly manage the entire payment chain of deposit, refund, and withdrawal. Integrate virtual account management capabilities to achieve multi-currency netting settlement and real-time exchange, reducing cross-currency capital losses. Through standardized funds Open API, output general capabilities such as balance deduction, income entry, intelligent distribution, and subsidy distribution externally, unify the management of card token resources, realize the reuse of all business functions after one-time card binding, and reduce cashier friction. Implement refined control capabilities such as fund freezing and unfreezing, negative balance disposal, and priority deduction of balance. Use SAGA distributed transactions to ensure data consistency of the fund link. Pre-apply KYC/KYB authentication and AML risk control screening. Utilize the unique tracking ID and the funds event bus to achieve full-chain traceability. Through automated reconciliation scheduling, complete intelligent reconciliation and aggregation of internal and external bills, significantly reducing the cost of manual settlement.

Based on the BPR process reengineering theory, using the AI-native cloud intelligent financial platform as the carrier, relying on the cloud-native microservices and atomicized financial engine architecture, it integrates ERP, business, funds, and tax heterogeneous systems, implements the main data governance and business-finance standardization system, unifies the group accounting口径， process norms， and risk control standards， and realizes the closed-loop integration of the entire business-finance-capital chain. By integrating enterprise large model auditing， OCR intelligent recognition， and RPA digital employee capabilities， the traditional financial operation mode is restructured， and the invoice verification， document review， accounts receivable and payable settlement， voucher generation， year-end closing， and tax declaration processes are fully automated. A three-layer intelligent risk control system is established， including pre-event rule interception， in-process dynamic monitoring， and post-event traceability analysis. The flexible configuration of rules in the platform replaces the fixed ERP logic， builds a flexible and controllable compliance governance mechanism， and relies on data warehouses and BI models to accumulate data assets， promoting the transformation of finance from passive accounting to active management and value empowerment.

Build a cloud-native AI CLM intelligent contract management platform, deeply integrating the group's financial middle platform, ERP and fund systems. Relying on the legal vertical large model and NLP semantic understanding technology, restructure the integrated management system for the entire contract, business, finance, funds and risk control chain. Through the unified contract template and approval process engine, achieve full-quantitative and standardized governance of contract structure. Implement five core capabilities such as AI intelligent drafting, large model compliance review, OCR + NLP key field extraction, version intelligent comparison, and performance dynamic monitoring. Automatically identify contract risks, capture core financial data, and track the progress of performance and repayment. Relying on the data interconnection capability of the middle platform, drive financial automatic accounting, fund budgeting coordination, and precise control of receivables and payables with contract structured data. Completely change the manual bottom-line control model and achieve intelligent self-governance of contract industry-finance integration and pre-governance of the entire process risks.

We have independently developed a three-terminal integrated intelligent academic conference platform, which builds a full-chain closed-loop system covering pre-conference preparation, in-conference collaboration, and post-conference knowledge accumulation. Based on the SoundNet RTC, we have established a low-latency cross-border audio and video transmission foundation, and independently developed signaling scheduling, conference room management, and refined permission system, breaking free from the constraints of third-party general conference components. Before the conference, we can achieve registration review, manuscript management, role classification and intelligent seat scheduling; during the conference, we rely on ASR speech recognition and LLM large models to complete real-time transcription, automatic generation of bilingual subtitles, and intelligent summary of speech content. After the conference, we slice and clean the conference audio and video and text data, perform Embedding vectorization processing, combine vector databases and Redis high-frequency caching mechanism, and through the RAG architecture, build a conference-specific knowledge base, enabling structured archiving, intelligent retrieval and long-term reuse of academic content, and empowering the accumulation of academic assets.

At the technical level, a complete vertical knowledge base architecture is established: based on vector databases, the brain science literature, experimental reports, and community research discussion contents are sliced and vector-embedded processed to convert unstructured research texts into high-dimensional vectors for storage; combined with Redis to cache high-frequency research questions and hot literature vectors for indexing, the search latency is significantly reduced. By integrating domain knowledge graphs and NLP semantic extraction technology, an RAG intelligent question-answering link is constructed to realize the research question-solving logic of "vector retrieval matching authoritative knowledge base + AI integration output". At the same time, it automatically completes the structured archiving and incremental update of community research content, builds an AI research assistant that operates 7×24 hours, freely opens the vertical intelligent empowerment capabilities, and breaks through the core barriers of global brain science researchers' knowledge accumulation, efficient search, and cross-regional collaboration.

Based on the BPR process reengineering and BPM full life cycle management theories, the entire bank's three-level standardized management process framework is reconstructed. Relying on the process engine and rule engine, the bank's compliance approval system is solidified to achieve intelligent process routing, parallel co-signature, and timeout warnings. Through the API integration gateway, the human resources, finance, and electronic archives systems are connected, and an end-to-end closed-loop circulation system is established. The low-code platform is equipped to achieve rapid process iteration, and the process operation cockpit is provided to realize full-process visual monitoring, data analysis, and continuous optimization. Intelligent tools are embedded to empower process efficiency improvement and risk prevention. The information technology innovation and hierarchical authority control system are implemented.

Build a unified digital and intelligent financial shared control platform that integrates all business scenarios such as travel expense reimbursement, expense verification, accounts receivable and payable settlement, and annual budget control. Integrate OCR, AI financial auditing, BPM, and bank-enterprise direct connection settlement. Through systematizing financial regulations and internal control norms, achieve pre-locking of budget amounts, rigid interception of expense expenditures during the process, and post-event review and analysis of data. Connect the business, finance, funds, and tax data links, and realize cost penetration tracking, dynamic monitoring of funds, and visualization of budget execution analysis. Build a standardized, compliant, refined, and intelligent financial control system.

Based on the product life cycle planning, end-to-end process reengineering, lean product development, risk shifting, user journey optimization, and product management theories, the lead role was responsible for completing the overall planning and implementation of the bank's digitalization system for image data. At the technical level, advanced technologies such as mobile terminal architecture, OCR, BPM, electronic image certification, data tagging, reuse of middle platform capabilities, and encrypted distributed archiving were integrated. Through business architecture decomposition, demand hierarchical governance, scenario-based product design, gray-scale iterative implementation, full-chain quality control project management methods, the offline application product system was restructured. Unified PAD mobile operation standards were designed, including electronic form filling, real-time image collection, AI intelligent verification, pre-risk control preliminary review, total bank second-level synchronization, automatic process routing, and full-chain electronic certification and archiving product modules. Standardized and reusable retail application product capabilities were accumulated, achieving an upgrade from "offline manual circulation" to "digital, standardized, intelligent, and measurable" product operation.

Based on POS message parsing, payment route scheduling, distributed clearing engine and intelligent rate calculation model, combined with automatic netting, bank-enterprise direct connection, business-finance middle platform, risk control rule engine and full-chain traceability capability, the entire payment and business process of the acquiring business is restructured. Through domain modeling, business rule solidification, gray-scale iteration, full data point embedding, establish a standardized clearing and accounting system, realize real-time submission of offline POS transactions, automatic fund collection, intelligent clearing entry, precise calculation and distribution of handling fees. Build a merchant self-service accounting portal, supporting bill verification, rate inquiry, voucher export, and打通 the merchant self-service reconciliation channel. Online， standardize the carrying of refund， adjustment， refusal correction， and transaction appeal processes， build a full-chain traceable， monitorable， and verifiable mechanism， realize standardized acquiring transactions， automated accounting， and regular risk control， meet regulatory compliance requirements.

Leveraging native smartphone sensors and headphone devices, we have built a lightweight, on-device AI healing closed-loop system that requires no external hardware. The system captures real-time body movement data via the phone's IMU accelerometer and extracts breathing rhythm features locally using the microphone, with raw sensor data immediately destroyed to ensure privacy and security. Based on an on-device temporal AI model, user arousal states are continuously inferred in real time, which then interacts with the quantized RAVE neural audio engine to dynamically adapt sound wave frequency, spectral parameters, speech rate, and volume, enabling smooth audio transitions. By integrating a local vector database to accumulate user auditory preference data, the system generates personalized meditation scripts using an on-device LLM. It also automatically switches between binaural beat and isochronic tone modes based on headphone insertion status, fully supporting offline operation with low latency.