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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Salesforce CRM Analytics
Score8.5 out of 10
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Salesforce CRM Analytics (formerly Tableau CRM) is a cloud-based business intelligence solutions and analytics software. It provides users with automated data discovery, CRM-connected analytics, top-down views of data, augmented analytics, predictive insights, and customizable data visualization tools.
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
For us it really comes down to that book management and next best contact for our advisors. When we're thinking about a book of business that may range, depending on the advisor, from 400 clients to a thousand clients, how do they really optimize their time? Who do they call next? Who do they work with to make sure not only they're keeping those clients engaged, they're not leaving the firm going to other advisors who they haven't talked to in a while who might need their attention. That's really where that CRM analytics is really proven pretty powerful for us.
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
Implementation takes time and resources. It is a heavy lift to implement and at first, it can take a little bit of time to understand what you are looking at. But once it's implemented it's easy to get started.
Without any BI expertise or resources available to your organization, the implementation of this is difficult. If you aren't used to BI tools and don't have an expert in house, the terminology can be difficult to understand at first.
Their support is not on hand to help you if you encounter any issues, at least not on all the plans or the basic plans. Real-time support service is an add-on, so you'll need to be patient if you require help or pay extra money.
More functionality for the tool is needed to compete with other heavyweights in the arena like Tableau, Qlik, and Microstrategy. Still lacks the robustness, functionality, and flexibility other competing products possess.
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
For someone who don't have coding background, this could be a useful tool and fairly easy to learn and use given the good support. However, if you know other open source tools, it would be much easier to use the other tools and the knowledge is more transferable in the future.
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
I was not able to be in interaction much with Salesforce support team since every feature works the way it should be working. So far I have not experienced any bug or major glitches that would delay the result of my work and performance. There is also a hotline in our company for Salesforce issue but so far I have not used it.
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
An implementation partner would certainly result in greater output in a more efficient amount of time. However, I have found implementation partners to be extremely expensive for the output received (at least working for a non-profit company they are frequently unaffordable). Internal implementation does help with usable output though since internal knowledge would better know the data architecture and business processes
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
Tableau is the absolute top of the class when it comes to business intelligence, but it doesn't make sense for every business case. In our case, we needed a simple data visualization platform for our CRM platform and sales pipeline. Salesforce Analytics, while nowhere near as robust, did the job we needed it to do perfectly in a significantly more cost-effective manner.
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
I would say it's been positive just because as a company, anyone that has access to it can go in there and pull any company information and we're very up to date then on all of our client base. So I would say it's been a very positive impact.
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
