For a machine learning startup the fourth time was a charm.
When the sensor-as-a-service company came to CloudFactory they had worked with two other vendors who couldn't achieve the accuracy they needed for their business intelligence platform.
They had also tried to do the work themselves. None of the options were working like the Chief Technology Officer wanted.
Use Case: Business Intelligence | Image Annotation
"We have been through a full production cycle of data sent through CloudFactory. We’ve fed that back into our model, trained it, deployed it and seen much, much better results and model accuracy."
Once the company collects sensor data, it needs to be manually analyzed and then run through its machine learning algorithm. They tried three options before turning to CloudFactory.
“When we started the company, it was me sitting in a cafe all day tagging pieces of data and drawing boxes around relevant objects and doing that kind of thing. Obviously, that wasn't scalable,’’ the CTO says.
Next came attempts to use on-site contract workers. The contract workers came and went and were inconsistent even with the CTO there to train them. The crowdsourcing vendor they chose next wanted the work done in their tool, while the company had their own. None of the methods provided reliable results.
“With crowdsourcing, we would explain the task and kind of throw it over the fence and hope it was done correctly,’’ the CTO says. “But the accuracy was just horrible because it’s a task that requires just enough context and understanding of it.’’
Frustrated with these efforts, a company employee suggested checking out CloudFactory as he had a positive experience with the company in a previous position. “When I heard about CloudFactory, it seemed like a perfect fit because of the dedicated workforce,” the CTO says.
CloudFactory provides a managed workforce with a team lead 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.
Their workforce can ask questions easily, which is helpful because some of the work is very nuanced. “We needed trained people to talk with and who could ask us questions like, ‘I saw this weird case, what should I do here?’ That just was a really important element of the process,” he says.
The CTO was thrilled by how quickly the CloudFactory workforce ramped up. “The team’s output has almost outpaced our ability to keep them fed with data. It’s making us look at what else we can do.”
“It’s easy to discount how hard it is to find people that are good, affordable, consistent and reliable. It’s hard to hire for. CloudFactory has it figured out. Not only is it way less expensive than if we did it ourselves, it just takes so much pain off our plate.’’
The tagged data is fed into the company’s model, and the results have been exactly what the CTO sought. “We have been through a full production cycle of data sent through CloudFactory. We’ve fed that back into our model, trained it, deployed it and seen much, much better results and model accuracy.’’
The CTO says he also feels confident that as the company grows, he’s got a partner that can help him grow. “The CloudFactory team can support any big customer use cases that might come up, as opposed to trying to come up with a mechanism for scaling up some other service ourselves.”
Even more importantly, it’s freeing the company to expand its horizons.
“We want to recommit to being a machine learning company, to go back to our roots of offering a do-it-all sensor, the CTO says. “CloudFactory, is not just the catalyst but the support to help us refocus on our vision. That is a cool story.”