AI platform thrives with huge data intake
Customer Company Size
Large Corporate
Region
- Asia
Product
- Bixby
- Sumo Logic
- Google Stackdriver
- Google Cloud Operations
Tech Stack
- Log Analysis
- Machine Learning
- SaaS
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
- Digital Expertise
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
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 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.
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
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
.png)
Case Study
Improving Vending Machine Profitability with the Internet of Things (IoT)
The vending industry is undergoing a sea change, taking advantage of new technologies to go beyond just delivering snacks to creating a new retail location. Intelligent vending machines can be found in many public locations as well as company facilities, selling different types of goods and services, including even computer accessories, gold bars, tickets, and office supplies. With increasing sophistication, they may also provide time- and location-based data pertaining to sales, inventory, and customer preferences. But at the end of the day, vending machine operators know greater profitability is driven by higher sales and lower operating costs.
Case Study
Series Production with Lot-size-1 Flexibility
Nobilia manufactures customized fitted kitchens with a lot size of 1. They require maximum transparency of tracking design data and individual processing steps so that they can locate a particular piece of kitchen furniture in the sequence of processes.
Case Study
American Eagle Achieves LEED with GE LED Lighting Fixtures
American Eagle Outfitters (AEO) was in the process of building a new distribution center. The AEO facility management team decided to look at alternate options for lighting layout that could provide energy and maintenance savings. AEO would need a full-time maintenance employee just to replace burned-out fluorescent tubes.
Case Study
Revolutionizing Rodent Control
From pet- and child-safe traps, to touch-free and live-catch rodent control solutions, Victor continues to stay committed to producing superior products that meet the varying needs of today’s pest control professionals. And, with a long standing history supporting customers in the food processing, service, and retail settings, Victor knew that strict regulations were costing organizations thousands of dollars in excess overhead trying to manage their rodent-control solutions. Trap inspections in these environments are often difficult and time consuming, requiring personnel to manually check a trap’s status multiple times per day, amounting to over six hours of manual labor. Victor is looking for an innovative way to increase operational efficiencies with the use of technology.
