Success stories

Analytics Done Smarter

Guavus innovation solves real-world problems

What we do

Drive more value from your data using AI and Advanced Analytics

Collect data at scale
Enrich & fuse in real time
Leverage AI based analytics
Initiate action & decisions

Collect data at scale

Enrich & fuse in real time

Leverage AI based analytics

Initiate action & decisions

Guavus at Scale

$500M saved

by our customers annually!

84% reduction

in mean-time-to-understand

real-time

response to complex queries

510 Billion

real-time records analyzed daily

Up to 90%

reduction in data stored

500 Million

devices monitored in real-time

Press

IoT Evolution podcast interview with David Yates, VP, Tech Product Management & Marketing at Guavus

Guavus Plus SQLstream Means Broad And Deep For IoT Data Science, on the TeleInterActive Press

The Application of Machine Learning to Alarm Management — article in the SCTE Network Operations Journal, by Doug Junkins, Guavus Field CTO

Guavus named as 1 of the top 50 Most Impactful Companies by insideBIGDATA

Blog

Four Ways CSPs Can Use AI to Gain New Subscriber Insights, Out-Market OTT Competitors and Deliver a Better Customer Experience

Most CSPs know they need to harness their valuable data, but struggle with how to do it. Putting AI and analytics tools to work alongside their deep-packet inspection (DPI) classification engines, providers can learn a lot more about their customers, then categorize them in understandable ways that allow the provider’s marketing department to approach them with targeted, personalized and meaningful service offers. Let’s examine a few ways CSPs can succeed.

5G: Too Good to be True?

5G promises both tremendous opportunity and challenges. Leveraging AI and analytics, CSPs can take the volume of data generated by the network and turn it into useful, consumable information that helps them grow their business and increase their top line.

Spinning Data into Pure Gold

Expect to see companies start monetizing big data as technologies emerge to 1) boost the productivity of data scientists, 2) automate a key aspect of machine learning, and 3) spur communications service providers (CSPs) to start riding the digital wave and exit the low-margin, pure-pipe business. These trends will make the job of turning data into more accurate decision-making and actionable business outcomes possible.