We use all of the buzzwords you’ve heard of to detect what’s in a picture: deep learning, artificial neural networks, computer vision, pattern detection, big data – it all combines to give you a quick way to get the quantitative data you need for success.
After the Observa system is shown what to look for (e.g. your products, your competitor’s products), it can detect them in an image and give you a full set of numerical analytics.
For example, this could detect what percentage of a grocery section is your products, or if the retail planogram is being adhered to.
The more you use Observa, the more valuable the data becomes. Our machines can spot trends in your data and make recommendations. Those recommendations can take the form of increased vigilance on our part (more observations) or on yours (deploy the sales team).
You get a text in the middle of a Wednesday afternoon from your credit card company asking about suspicious transactions. How did it know?
Maybe it was because your card purchased a burger in Ohio and then, 30 minutes later, bought a Mai Tai in Honolulu. Maybe your card was used to buy 85 gallons of gas and you normally only buy 15.
Observa uses technology similar to the credit card industry to flag incoming data that is suspect. We look at locations, behavioral patterns, image recognition, and more to make sure data is reliable.
Human in the Loop
Machines are getting better, faster, and ‘smarter’, but they can still make mistakes. Our machine decisions keep humans in the loop, ensuring that data is consistently checked for accuracy and no major decisions get made without a second level of verification.