Building an App with AI is Easy. Simply provide Knack AI builder with your app’s goal, target users, main data tables (e.g., customers, products), and basic features. In just seconds, AI will generate a starting point for your no-code app, complete with data models and user interfaces.

Leverage Knack AI to expedite your new app with just a few sentences and save hours of time. Safeguard data, control access, and ensure robust system reliability for peace of mind. Organize, import, and manipulate data efficiently to make informed decisions and drive success.

SAAS workforce innovation platform reinventing the job application and using training to refresh the candidate experience. View contacts for Knac to access new leads and connect with decision-makers. We are reinventing how people apply and prepare for jobs.

At its core, Knack is a powerful online database. Knack provides a secure location for you to collect and manage your data. Knack makes it simple to design your Live App to put your data to work. With Knack you can: Display your data with searches, maps, and calendars. Automate your data with workflows and tasks.

2023年5月8日 · There are several ways in which AI can be used to further workplace DEI efforts. These include improvements to hiring and performance management processes, bias detection in content, and...

2025年2月27日 · “AI can be leveraged at almost every point in the recruiting process, from onboarding to pipeline management to employee experience and engagement,” shared Ariel Lopez, founder and CEO of Knac. AI recruiting tools can help companies balance the pool of candidates by improving the inclusivity of language used in job descriptions, and by ...

2022年11月23日 · Instead, KnAC can serve as an augmentation of an arbitrary clustering algorithm, making the approach robust and a model-agnostic improvement of any state-of-the-art clustering method. We demonstrate the feasibility of our method on artificially, reproducible examples and in a real life use case scenario.

2021年12月16日 · Instead, KnAC can serve as an augmentation of an arbitrary clustering algorithm, making the approach robust and a model-agnostic improvement of any state-of-the-art clustering method. We demonstrate the feasibility of our method on artificially, reproducible examples and in a real life use case scenario.

Industrial automation involves using control systems like robots, sensors, and AI to operate machinery and processes with minimal human intervention. Software testing ensures the quality, functionality, and reliability of applications by identifying …