Kortical is an end to end AutoML platform that greatly accelerates the creation, iteration, explanation and deployment of world class machine learning models. Being a code based solution, where you can edit the models the platform automatically creates, means that it is easy to get the best of data-scientist and AutoML and seamlessly provide mission critical enterprise grade deployment.

Languages supported: English

10.0/10 (Expert Score) ★★★★★
Product is rated as #10 in category Data Science and Machine Learning Platforms
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Kortical is an ML platform that is giving the data scientists control and putting them in the drivers seat while Kortical does all the heavy lifting. It is AutoML and more, with full control and transparency, enabling fast experimentation across a large breath of models, easy deployment with fully hosted and scalable models in the platform and facilitates collaboration and sharing of compute easily across a team.

It assists data scientists with data prep, feature engineering, building ML models, deploying and hosting models that scale, with fully explainable ML. Data Scientists can edit the outputs of the models to add their knowledge to the AutoML for full control. With Kortical you get the best of data scientist and machine.

Kortical gets better results than Google AutoML, Azure, Datarobot and more. It helps you experiment fast and deploy with ease. It is built by data scientists, for data scientists.

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Customer Reviews

Kortical Reviews

Simon J.

Advanced user of Kortical
★★★★★
AI and machine learning platform that can democratise data science

What do you like best?

Kortical's auto-ML platform accelerates the time it takes to move from explorational to deployment as a data scientist. By automating the vast majority of steps in a machine learning pipeline, Kortical enables a data analyst to build production ready machine learn solutions. There are a wide array of supervised learning algorithms to tackle different problems.

What do you dislike?

For the more advanced data scientists, there is probably a desire to hand craft machine learning solutions from scratch and to be incomplete control of the workflow. There is also a need to conduct most feature engineering prior to ingesting data into the platform.

Recommendations to others considering the product:

If you are looking for a machine learning platform for analysts who don't have PhDs in AI or machine learning, Kortical is an excellent platform for demoncratising the availablity of AI/ML solutions. It builds models and makes deployment easy. You will probably still do you data preparation in advance of using the platform.

What problems are you solving with the product? What benefits have you realized?

The most problem we are solving is the ability to build prototypes with little domain knowledge on a particular subject. This unlocks the benefit of reducing time to production (reducing effort 3-10x). It permits more time to experiment at the beginning of a project and there is no time wasted in provisioning the appropriate cloud environment. Typical business problems include binary classifiers for event prediction (cross-sell, churn) and regressors for forecasting.

Review source: G2.com

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