The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business outcomes, that is available on the user's cloud platform-of-choice, on-premise, or as a fully-managed service. The solutions include tools providing data preparation enabling users to explore and…
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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…
Data Robot is a powerful tool for greatly reducing the time required to build powerful and accurate machine learning models. It then allows you to utilize these items. It is probably most appropriate for organisations looking to get into data science and incorporate Machine learning and AI into their decision making. Having dedicated resources that can be upskilled is perfect, as the expertise and software provided allows for a big jump from willing to able. For the to work effectively, organisations should really consider dedicating at least one resource to the ML and AI projects, and understsand that not every project will yield fruit. A lot of this is innovation and experimentation, so relying on data Robots insights in make or break situations is not recommended. You also need to manage expectations well as the data you have may simply not allow for a powerful model. Finally, the organisation must be open to change, this has to exist in tandem with the above. If the organisation's key stakeholders don't want to change, all the insights in the world won't help. So a willingness and ability to change effectively is required to maximize ROI.
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
DataRobot helps, with algorithms, to analyze and decipher numerous machine-learning techniques in order to provide models to assist in company-wide decision making.
Our DataRobot program puts on an "even playing field" the strength of auto-machine learning and allows us to make decisions in an extremely timely manner. The speed is consistent without being offset by errors or false-negatives.
It encompasses many desired techniques that help companies in general, to reconfigure in to artificial intelligence driven firms, with little to no inconvenience.
The platform itself is very complicated. It probably can't function well without being complicated, but there is a big training curve to get over before you can effectively use it. Even I'm not sure if I'm effectively using it now.
The suggested model DataRobot deploys often not the best model for our purposes. We've had to do a lot of testing to make sure what model is the best. For regressive models, DataRobot does give you a MASE score but, for some reason, often doesn't suggest the best MASE score model.
The software will give you errors if output files are not entered correctly but will not exactly tell you how to fix them. Perhaps that is complicated, but being able to download a template with your data for an output file in the correct format would be nice.
DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
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.
DataRobot provided the perfect balance of features and price points. The other tools we tried were very expensive and provided extra things that we really didn't need. Some of the other tools also required you to host them on a server at your institution or pay for their cloud service in addition to getting the software. This added to the expense without adding any additional functionality.
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.
