An open-source end-to-end GenAI platform for air-gapped, on-premises or cloud VPC deployments. Users can Query and summarize documents or just chat with local private GPT LLMs using h2oGPT, an Apache V2 open-source project. And the commercially available Enterprise h2oGPTe provides information retrieval on internal data, privately hosts LLMs, and secures data.
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ServiceMax
Score7.9 out of 10
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ServiceMax’s mission is to help customers with asset-centric field service management software. ServiceMax’s mobile apps and cloud-based software provide an overview of assets to field service teams. By optimizing field service operations, customers across all industries can better manage the complexities of service, support faster growth and run more profitable, outcome-centric businesses.
Most suited if in little time you wanted to build and train a model. Then, H2O makes life very simple. It has support with R, Python and Java, so no programming dependency is required to use it. It's very simple to use. If you want to modify or tweak your ML algorithm then H2O is not suitable. You can't develop a model from scratch.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Small deployments, where you have some specific need for ServiceMax and absolutely need offline capabilities, and are willing to deal with the problems. Otherwise, you may be better off looking at the built-in Work Orders and field service module that Salesforce is now providing. Their app is direct competition for ServiceMax and integrates much better with cases and knowledge articles.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Both are open source (though H2O only up to some level). Both comprise of deep learning, but H2O is not focused directly on deep learning, while Tensor Flow has a "laser" focus on deep learning. H2O is also more focused on scalability. H2O should be looked at not as a competitor but rather a complementary tool. The use case is usually not only about the algorithms, but also about the data model and data logistics and accessibility. H2O is more accessible due to its UI. Also, both can be accessed from Python. The community around TensorFlow seems larger than that of H2O.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
ServiceMax has an offline capability, and also integrates with our Salesforce side of business. At the time, Salesforce did not have a field service application so we could not consider it, but if we could now, we would probably go with that instead. ServiceMax is also expensive. But at the time, ServiceMax was the only offering out there that integrated with Salesforce, had mobile offline capability, and could operate at the scale we needed.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Positive impact: saving in infrastructure expenses - compared to other bulky tools this costs a fraction
Positive impact: ability to get quick fixes from H2O when problems arise - compared to waiting for several months/years for new releases from other vendors
Positive impact: Access to H2O core team and able to get features that are needed for our business quickly added to the core H2O product
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
ROI for ServiceMax is mostly dependent on how in depth the organization wants the software. Our ROI is expected within the second year of operation due to the complexity of integration and the initial training requirements for in-house programmers.
Inventory control ROI is expected within year three or four due to the number of technicians and creating the foundation of information to import into ServiceMax. Expectations are the front end programming will be complete and our programmers will be better acquainted with the modules and architecture to make the inventory integration smoother than the initial integration.
Our organization has been working with ServiceMax for ten months and beginning to incorporate the financials to the work orders. This process has not been as seamless as once projected and the root causes are under investigation. It appears the original fields available to track time between employees were not in depth nor segregated sufficiently for granularity.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
