A.I.-derived business insight provider Anodot announced on Tuesday, June 5, that Waze will integrate its autonomous analytics system throughout the community-based traffic and navigation app. Anodot’s machine learning system will beef up Waze users’ driving experience by detecting and reacting to user-reported abnormalities and problems.
Based in Israel with offices in Europe and Silicon Valley, Anodot’s systems act as a business data safeguard. Anodot’s analytics engine continuously monitors company data. When the machine learning-driven system detects problems or anything out of the ordinary for that company’s datasets, it signals an alert for further action.
What that means in plain English is that when Anodot’s machine language-based artificial intelligence software analyzes vast amounts of new data, it can tell immediately if something unusual occurs. A wide variety of businesses use Anodot’s analytics. When Anodot’s system identifies a glitch, an error, or anything outside the norm, the new data is integrated with the primary business’ systems. For various client’s seamless recovery from abnormalities can mean more on-time deliveries, increased manufacturing line uptime, or financial systems reacting to errors before too much harm is done.
The data Anodot will monitor for Waze’ will be the reports from millions of Waze users who share real-time information while traveling. Drivers use the navigation app to report traffic and road conditions, gas prices, speed traps, road construction projects, and more to help others save travel time and fuel expense. Users can find the best routes to follow on the maps Waze map editors update based on community-reported information.
With Waze’s real-time, community-driven travel information model, Anodot will be used to keep drivers moving. For example, if Anodot detects Waze member messages about traffic accidents, suddenly slippery road conditions, significant gasoline price changes, or anything else that its A.I. system determines differs from the norm, that data is instantly used to adjust local driver recommendations or notifications.
“Waze needed a solution that could quickly identify and alert us on potential app performance and user experience issues, helping us to minimize user issues,” said Waze’s head of analytics, Dr. Orna Amir. “Anodot helps us fulfill our most important goal: To constantly enhance and improve the driving experience for our users. And it does so by seamlessly analyzing millions of hyper-localized metrics.”
The variety of data types Waze receives and the speed at which it reports to drivers is at once its greatest value and biggest challenge. Turnaround time is crucial. When you add the element of location — which is anywhere Waze users drive — the complexity multiplies.
According to Anodot CEO and co-founder David Drai, however, its autonomous analytics engine is up to the task of making Waze’s processes more efficient and effective.
“With traditional BI (business intelligence) tools, it can take days or weeks for companies to learn of issues that can hurt reputation and profits,” Drai said. “Anodot’s autonomous analytics technology is capable of handling the speed, volume, and variety of data Waze generates, and provide actionable insight from these huge data sets.
“Whether this means better-suggested routes or fewer app hiccups,” Drai continued, “Waze users will enjoy a better app experience with Anodot working for them behind the scenes.”
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