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Case Studies > Improving model results with quality data annotation

Improving model results with quality data annotation

Technology Category
  • Analytics & Modeling - Computer Vision Software
  • Analytics & Modeling - Machine Learning
  • Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
  • Retail
Applicable Functions
  • Product Research & Development
  • Quality Assurance
Use Cases
  • Machine Condition Monitoring
  • Predictive Maintenance
  • Remote Asset Management
Services
  • Data Science Services
  • System Integration
The Challenge
Once SSC collects sensor data, it needs to be manually analyzed and then run through its machine learning algorithm. The company tried three options before turning to CloudFactory. First, SSC attempted to use on-site contract workers, but they were inconsistent even with the CTO there to train them. The crowdsourcing vendor chosen next wanted the work done in their tool, while the company had its own. None of the methods provided reliable results. Frustrated with these efforts, a company employee suggested CloudFactory as he had a positive experience with them in a previous position. The CTO found CloudFactory to be a perfect fit because of the dedicated workforce.
About The Customer
For a machine learning startup, the fourth time was a charm. When SSC came to CloudFactory, it had worked with two other vendors who couldn’t achieve the accuracy needed for its business intelligence platform. SSC also tried to do the work on its own. None of the options were working like its Chief Technology Officer wanted. SSC is a sensor-as-a-service company based in California, USA, with a company size of 11-50 employees. The company specializes in collecting and analyzing sensor data to improve the performance of their machine learning applications.
The Solution
CloudFactory provides a managed workforce with a project manager located where the work is being done, providing a vital layer of management to make sure that the labeling teams have the needed instruction and business context. The workforce can ask questions easily, which is helpful because some of the work is very nuanced. The CTO was thrilled by how quickly the CloudFactory workforce ramped up. The team’s output has almost outpaced SSC's ability to keep them fed with data. This has led SSC to consider what else they can do with the additional capacity. The managed workforce from CloudFactory has provided the necessary support and flexibility to meet SSC's data annotation needs effectively.
Operational Impact
  • The tagged data is fed into SSC’s model and the results have been exactly what the CTO sought.
  • The CTO feels confident that as the company grows, CloudFactory can help scale up to meet any big customer use cases.
  • The partnership with CloudFactory is freeing SSC to expand its horizons and focus on other areas of growth.

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