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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Microsoft 365 Copilot
Score 8.1 out of 10
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For enterprises, Microsoft 365 Copilot (or just Microsoft Copilot) is a generative AI operating as an intelligent virtual assistant for work. Through a chat interface, business users can use it to solve a variety of complex tasks.
$31.50
per month per user
Pricing
H2O.ai
Microsoft 365 Copilot
Editions & Modules
No answers on this topic
Microsoft Copilot
$31.50
per month per user
Offerings
Pricing Offerings
H2O.ai
Microsoft 365 Copilot
Free Trial
No
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Pricing shown is based on an annual commitment. Discount available for annual payment.
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.
I highly recommend its usage in Teams meetings to prepare a session transcript, meeting minutes, next steps and recognize speech by person. Also within the meeting recording, there is separation between the people talking at the time. The Copilot image creation is very accurate and useful to customize my PowerPoint presentations and other documents
The quality of image generation in Microsoft Copilot could be improved. Compared to other AI platforms, Copilot's images often fall short in quality and frequently contain typos.
When generating agents and chatbots, Microsoft Copilot currently doesn't appear to support file download functionality.
The email reply function is useful, but the responses can sometimes be overly elaborate. It would be helpful to have more options for adjusting the tone.
I give this rating because of the utilization I do with the product and the level security it provides which is very good. In our organization it is best suited as we have all other Microsoft tools with us. The offering made by Microsoft is great, I gave 9 out of 10 as sometimes it hallucinates as well.
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.
We needed a tool where secure data was not submitted to servers to process as we have some health care related data to keep private. We also needed to be able to test this tool without committing first to see if it is a fit and Microsoft provided this easily to us.
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
