Kortical emerges as a robust AI platform engineered to expedite the delivery of AI solutions, with a focus on transparent AutoML, scalable deployment, ML Ops, and Auto Training AI/ML models.
Designed primarily for data scientists and coders, Kortical aims to streamline repetitive tasks and drive significant business value. The platform facilitates the rapid scaling of AI and ML solutions through intuitive UI and code interfaces.
Kortical offers a plethora of functionalities, including exploratory data analysis, custom data cleaning, and feature engineering. Users can conduct thousands of model experiments, either specifying every detail or leveraging the AutoML capabilities.
The platform also prides itself on advanced model explainability and provides one-click deployment options via UI or API. Additionally, Kortical enables the creation, deployment, and infrastructure management of ML applications and services, offering flexibility to build and deploy ML apps with code.
A key tenet of Kortical’s philosophy is its commitment to ease of use while providing granular control over AI solutions. The cloud-based platform facilitates swift adaptation to consumer and market behavior, fostering the development of self-learning AI systems.
In essence, Kortical stands as a comprehensive solution for accelerating AI delivery, empowering users to harness the full potential of AI and ML technologies with efficiency and agility.
More details about Kortical
How does Kortical speed up delivery of AI solutions?
By automating tedious processes like feature engineering, data cleansing, and data analysis, Kortical accelerates the delivery of AI solutions. It incorporates AutoML’s features, enabling automatic model selection and optimization for machine learning, accelerating the development of AI and ML solutions. Additionally, Kortical makes use of a code-based dynamic template system that makes it possible to create machine learning applications that can be quickly and readily modified, with a 30-minute startup time.
How does Kortical assist in scalable deployment of AI solutions?
The capacity to deploy machine learning models at scale, irrespective of the task’s size and complexity, is referred to as “scalable deployment” in Kortical. By introducing a one-click deployment functionality through its user interface or an API, Kortical has streamlined this procedure. Whatever the size of the machine learning models, Kortical offers a smooth way to quickly and easily deploy them.
How user-friendly is Kortical and why?
Kortical’s design places a strong focus on usability. Its guiding principle is to offer a user-friendly platform that is adaptable enough to take into account any changes in specifics. To meet the comfort and skill level of the user, it achieves this by providing two modes of operation, a completely guided no-code model creation interface, and a full code-driven SDK.
How does Kortical promote transparency with AutoML?
With AutoML, Kortical facilitates transparency by granting users complete control over the AI solutions. Users can choose to control every detail or leave it up to AutoML. Furthermore, Kortical places a strong emphasis on advanced model explainability, elucidating to users the inner workings of AutoML-created models and the factors that impact their predictions. Furthermore, the SDK is fully code-driven and transparent, guaranteeing that users maintain all control over their models.
