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Sage AI
AI Ops Agent Workbench
AI Observability
Full-lifecycle AI observability
Dashboard
Unified visualization, one-screen insight
Monitors
Precise alerts. Zero noise. Fast response
The securities industry's complex, high-concurrency systems and fragmented monitoring cause data silos, slow fault localization, and unquantified user experience—under strict regulatory scrutiny. Bonree ONE delivers end-to-end observability, intelligent troubleshooting, and experience quantification.
Root‑cause localization time reduced from 2 hours on average to under 5 minutes – a 96% improvement.
Irrelevant and duplicate alerts reduced by 82%, O&M labor input decreased by 45%.
Proactive detection of quote/trading interface faults 30 minutes in advance, shortening business interruption duration by 70%.
Online user experience quantification coverage increased from 35% to 100%, customer complaints down 68%.
Meets regulatory requirements, reducing compliance self‑inspection time by 60%.
Collects real user access data from APPs, H5, mini-programs, etc. Trace IDs span frontend → gateway → microservices → database, enabling one-click decomposition of full-chain latency and precise fault layer identification. Expected outcomes: full quantification of terminal user experience, eliminating the need for cross-departmental coordination for complaint localization.
Integrates heterogeneous third-party data from multiple sources; a single platform consolidates various observability data types. When anomalies occur, automatically correlates corresponding logs, network latency, and service call stacks. Expected outcomes: no more multi-system switching; complete multi-dimensional fault review on a single page.
O&M observability from a critical chain perspective: covers 70+ brokerage business chains including trading, login, and search/query;
Cross-data-center deployment: enables joint query and analysis across data centers;
Visualized vertical deployment architecture and horizontal call architecture: improves cross-team fault coordination efficiency, supports future fault diagnosis and impact analysis.
Establishes a fault diagnosis framework, breaks down cross-specialty troubleshooting barriers, and enables comprehensive diagnostic capabilities.
Through troubleshooting workflow orchestration and O&M knowledge authoring, codifies troubleshooting experience for common fault scenarios in next-generation core systems, enabling automated diagnosis for common faults.
Combines AI large language models, RAG technology, workflow, and other advanced technologies to perform comprehensive synthetic analysis of troubleshooting results at each workflow node, improving both the speed and accuracy of fault diagnosis.
IDC China Semiannual IT AI Operation Software Tracker, 2025H2
Cycle™ for Infrastructure Strategies in China, 2026
Market Guide for Intelligent IT Monitoring and Log Analysis Tools, China