The use case: how Cisco deploys H2O.ai
Cisco's advanced analytics team uses H2O's in-memory machine learning platform to build and score propensity-to-buy models for its entire database of companies. The models, built with methods such as GBM and deep learning, are rebuilt each quarter and used by marketing and sales.
More reported results
Figures published in H2O.ai’s case study. They are not independently measured by usedby.
Cisco deploys roughly 60,000 propensity-to-buy models every quarter across hundreds of millions of observations
Since its inception the factory has been associated with more than $3 billion in revenue.
In the customer’s words
We score every single one of the 160 million companies in our databases, and calculate the probability that they will buy each of the most important products and services we sell.Other AI tools used by Cisco
Other public relationships recorded on usedby.
CelonisConfirmed
MindtickleConfirmed
PrezentConfirmed
WorkatoConfirmed
AlphaSenseObserved
Automation AnywhereObservedH2O.ai users in Telecommunications
Companies in the same sector, with public evidence.
See all H2O.ai customers
Go straight to the source
Based on H2O.ai’s published case study. We check the public evidence; the results are reported by the vendor.
h2o.ai- Last checked
- Oct 24, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 15xChecked
Printed word for word on the page, near the name of Cisco.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Cisco.
- Cisco uses H2O.aiChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
What once took more than a month now takes two days, a 15x increase in speed, on a dramatically larger dataset.