H2O.ai vs. Kortical

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
H2O.ai
Score 6.5 out of 10
N/A
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.N/A
Kortical
Score 10.0 out of 10
Enterprise companies (1,001+ employees)
Kortical is an end to end AI as a Service (AIaaS) platform designed to accelerate the creation, iteration, explanation and deployment of world-class machine learning models. The vendor describes the key benefits of Kortical is AutoML that writes custom machine learning solutions from the ground up in code. Getting hands-on with the code is optional but being able to edit code it makes it easy to get the best of data scientists and AutoML, while also getting the benefits of full…N/A
Pricing
H2O.aiKortical
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
H2O.aiKortical
Free Trial
NoYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
H2O.aiKortical
Top Pros

No answers on this topic

Top Cons
Best Alternatives
H2O.aiKortical
Small Businesses

No answers on this topic

Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
Medium-sized Companies
SAS Viya
SAS Viya
Score 7.0 out of 10
Posit
Posit
Score 9.0 out of 10
Enterprises
Dataiku
Dataiku
Score 8.6 out of 10
Dataiku
Dataiku
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
H2O.aiKortical
Likelihood to Recommend
8.1
(3 ratings)
10.0
(1 ratings)
Support Rating
9.0
(1 ratings)
9.0
(1 ratings)
User Testimonials
H2O.aiKortical
Likelihood to Recommend
H2O.ai
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.
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Kortical
Kortical is really widely applicable to many use cases, although it doesn't handle images or video it is great to help you build really great ML models without needing to plan ahead what you are going to try, you let the platform build you the best model. It is suited to beginner and more advanced data scientists as you can edit the code to narrow the search space which makes model creation more you build it without AutoML. Hosting the model behind an API that is ready to go is great as it saves so much time vs doing that dev work from scratch
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Pros
H2O.ai
  • Excellent analytical and prediction tool
  • In the beginning, usage of H20 Flow in Web UI enables quick development and sharing of the analytical model
  • Readily available algorithms, easy to use in your analytical projects
  • Faster than Python scikit learn (in machine learning supervised learning area)
  • It can be accessed (run) from Python, not only JAVA etc.
  • Well documented and suitable for fast training or self studying
  • In the beginning, one can use the clickable Flow interface (WEB UI) and later move to a Python console. There is then no need to click in H20 Flow
  • It can be used as open source
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Kortical
  • The NLP models results were much better than the ones that we did outside of the platform.
  • It is really easy and quick to build a good model with a lot of the manual boring tasks all done automatically like one hot encoding, etc.
  • Kortical shows the features and their importance for any model type as part of the platform which is great for understanding the models.
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Cons
H2O.ai
  • Better documentation
  • Improve the Visual presentations including charting etc
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Kortical
  • It would be ideal to have Jupyter built into the platform, they say it is coming.
  • Also while it is easy to use, at the start it would have been helpful to have more help guides.
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Support Rating
H2O.ai
The overall experience I have with H2O is really awesome, even with its cost effectiveness.
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Kortical
Their support is great as we use Slack and we have our own channel and they always respond really quickly. Data Science support is available to help unblock you as well as dev support as we're setting up the data feeds. It would be great if there were more FAQ or self-help guides in the platform but the personal touch is also really appreciated and probably gets us there quicker anyway.
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Alternatives Considered
H2O.ai
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.
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Kortical
No answers on this topic
Return on Investment
H2O.ai
  • 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
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Kortical
  • ROI is great as what we would spend on compute we get the AutoML for essentially the same price so it is cost neutral as Kortical comes with compute built-in.
  • The results mean that we can automate so much more than our previous model so that is key to the positive ROI.
  • The platform auto trains new models and lets us know when there is a better model so it has saved a lot of time so we can focus on new business problems to solve with ML.
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ScreenShots

Kortical Screenshots

Screenshot of Lab Screen is the main screen where you upload your data, select the target column and then hit start training for the AutoML to turn your data into machine learning data,  automatically build features and then generate the code on the screen (which you can edit if you wish) and leave it to train to find you the best model based on your data.Screenshot of The graphs show you how many iterations Kortical has gone through to find you the best model.Screenshot of You can explore any model in more detail.Screenshot of You get high level explanations for each modelScreenshot of Also row by row explanations - here is a passenger that is highly likely to survive the titanic, due to being female, first class cabinet and high fare but her age at 35 was counting against her surviving a little and you can get these for every row and future prediction.