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 8.8 out of 10
N/A
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.
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Community Pulse
H2O.ai
Microsoft 365 Copilot
Considered Both Products
H2O.ai
Verified User
Anonymous
Chose H2O.ai
I have used Knime, RapidMiner, and Weka before I heard about H2O, but amongst all I really liked H2O. However, nowadays Googles AutoML and AWS SageMaker AutoML platform are really competitive, but more costly than H2O.
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 …
H2O provided all the needed features such as Linear Modeling, Targeted Learning, Predictive Analytics including GLM, Trees, Neural networks and ensemble with ease. We are also able to pick and choose what we want without deploying all the bulky tools unlike others. Able to …
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.
I love Bing Copilot because it is integrated to Bing, I can have the answers easily using my phone or my laptop. The answers show the links just in case one needs to have further information about a topic, and somehow the tool feels friendlier than the other tools such as …
All data remains within the company, in the tenant. Customer data must never be leaked to an unprotected environment, not even targeted customer issues. That's why Copilot is much better suited for this.Copilot is also a Microsoft product, and its integration with all other …
I think It lost the race for now. I don't think Microsoft will keep investing on it since we have better tools outside their environment. In my opinion, Microsoft Copilot is not even in the benchmark tools and in the race for AGI. I think Microsoft is way behind and Microsoft …
they work beautifully in their own ecosystems. since my organization mostly uses Microsoft products, Microsoft Copilot is user to navigate compared to gemini
Microsoft Copilot is a serious competitor to ChatGPT in the corporate world, due to its heavy and well implemented integration across the Microsoft 365 suite. It produces comparable results, but provides data security, controls, customisation and options that ChatGPT can't …
Copilot is dominates ChatGPT in business related capabilities, like the listed below: - Email content recommendation making it more professional and in business language - Copilot creates more accurate and better looking custom images per my instructions
Since we use Microsoft 365 apps in our day-to-day work, we didn't have to choose Copilot over any other AI. It just came with the subscription. However, I would still use it over ChatGPT because Copilot is integrated with all the major Microsoft apps that we use. We dont need …
I find that ChatGPT offers better image quality than Copilot, and creating custom GPTs in ChatGPT feels more intuitive than generating agents in Copilot Studio. However, Copilot provides more reliable sources for research compared to ChatGPT, which sometimes returns …
Use H2O.ai whenever you need easy to use tool, when you must be cost efficient (you can not charge the client extra money for software licenses used), need a tool with lots of algorithms that are normally used in data analytics, or need to work on one machine (it is either not allowed to move data to cloud storage or simply not necessary to connect to Hadoop, etc.). Also, you can call H2O directly from Python which makes analysis more efficient.
In my experience, if you're using within the Microsoft office suite, it has the best integration. The usability is great and the user has to put little effort to get a task done. On the other hand, in my experience, coding within Visual Code is unreliable and the results are not consistent. You can't use with different programming languages and ask for complex tasks. Pitty because I think the VS integration is great.
This is not really a drawback, but rather a warning - the Drivereless AI is not a replacement for a data scientist yet, and will not replace data scientists in the next decade neither. The Driverless AI feature delivers reliable results only if the analyst is sure about the meaning of input data. The data quality is usually a major issue and no tool can detect the meaning of data in the input. Data scientists are also required for business interpretation of the findings. So be careful, and do not rely on this feature without a good understanding of what it really does in each step.
Like all other AI systems, Copilot suffers from hallucinations. You have to be very careful with the output it generates. It could be completely wrong. It needs to be checked and rechecked to see if it is correct.
Copilot sometimes struggles to formulate accurate responses to complex queries. It will either provide an incomplete response or generate a response that would be completely wrong.
Right now, I am unable to customize Copilot for my specific needs. Hopefully, in future versions of the AI, this will be taken care of.
It's integrated well across the Microsoft 365 suite of applications, without getting in the way, and providing useful tools. Some of the integrations need development, e.g. the Outlook add on is quite basic, and the excel and powerpoint ones can't do much yet. The implementation in Teams is really fantastic, significantly improving the experience of recording, transcription, and summarising meetings and action points.
I have used Knime, RapidMiner, and Weka before I heard about H2O, but amongst all I really liked H2O. However, nowadays Googles AutoML and AWS SageMaker AutoML platform are really competitive, but more costly than 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
Service desk employees resolve some tickets much faster thanks to Copilot support. This percentage, according to current knowledge, is between 20% and 30%.
For administrators, creating scripts and automations with Copilot support saves them a significant amount of time. This currently stands at between 20% and 40%.
If you don't give the copilot proper instructions, you'll also get answers that aren't valuable. You do need some knowledge or training to get the right answers from the copilot.
