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AI platform thrives with huge data intake
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
- Software
- Consumer Goods
Applicable Functions
- Product Research & Development
- Quality Assurance
- Business Operation
Use Cases
- Predictive Maintenance
- Remote Asset Management
- Machine Condition Monitoring
- Real-Time Location System (RTLS)
Services
- Software Design & Engineering Services
- System Integration
- Training
The Challenge
The data required to deliver a great user experience kept growing, as did costs and complexity, making it difficult to meet the demands of customers. Bixby’s deep-learning AI model understands the user’s voice and delivers more accurate results when user data accumulates. However, as Bixby required more data per user, the amount of data to analyze and manage increased, escalating data management costs to the development team. While the previously used cloud-based analysis system, Google Stackdriver and Google Cloud Operations supported simple search and debugging functions, the analysis team still had to go through additional processes and data format changes. There was room for improvement in producing meaningful results and enhancing customer experience, including debugging, data distribution, performance, and issue resolution.
About The Customer
Samsung Electronics Bixby is an artificial intelligence (AI) platform released in 2017. Bixby links to Galaxy, Samsung Electronics’ signature product line, and various gadgets and home appliances in the Galaxy ecosystem. Bixby leverages the user’s voice to perform daily tasks and control connected devices. Bixby’s deep-learning AI model understands the user’s voice and delivers more accurate results when user data accumulates. However, as Bixby required more data per user, the amount of data to analyze and manage increased, escalating data management costs to the development team.
The Solution
With the introduction of Sumo Logic, the overall quality and efficiency of the Bixby service operation improved, including cost savings from astutely maintaining and managing the data. Using log analysis and machine learning to address problems faster than simple searches, Sumo Logic improves debugging and performance issue resolution, leading to high-quality service delivery. Once up and running with Sumo Logic, the daily log ingestion volume averages 35 TB (terabytes). About 550 engineers and developers from the Samsung Electronics Bixby team use Sumo Logic; most of them are certified through Sumo Logic’s learning platform. By adopting Sumo Logic’s SaaS-analytics platform, the Samsung Electronics Bixby team successfully reduced management resources by improving the flexibility of the data analysis system. The developers, in particular, rated the platform highly because it does not require any additional storage space while offering powerful functions to analyze and process various forms of logs. This lets the developers generate more diverse insights for the service.
Operational Impact
Quantitative Benefit
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