MULTI·ON

Inabit.ai is a tool driven by AI that automates the process of creating professional presentations and visual data, allowing users to produce refined slide decks and adaptable analytics dashboards in mere moments. This platform removes the need for laborious manual design tasks by employing artificial intelligence to manage layout, formatting, and visual aspects, making it perfect for business professionals, educators, and anyone who needs to generate attractive visual content without needing design skills. Users select Inabit.ai for its effectiveness, professional-quality outcomes, and capacity to turn complex data into captivating visuals with minimal exertion.

CodeRabbit is an AI-driven code review tool intended to help development teams enhance their code quality and improve the efficiency of the pull request (PR) review process. It offers line-by-line change recommendations, PR summarization, chat interactions for codebase inquiries, and issue validation. CodeRabbit seeks to minimize the time invested in manual reviews, identify potential bugs before they reach production, and provide personalized feedback in line with developers' coding styles. Teams might choose CodeRabbit for boosting productivity, enhancing code reliability, and speeding up merge times by leveraging AI insights and collaborative features that seamlessly integrate with their version control systems.

Drawer AI is a smart online platform designed to automate electrical takeoffs and estimating by quickly extracting and calculating devices, fixtures, and circuits from PDF electrical drawings. Instead of taking hours, it completes these tasks in minutes. The software manages device counting, branch circuit routing, wire sizing, and report creation, allowing electrical contractors and estimators to finish bids as much as 70% quicker with enhanced accuracy. Those in the electrical industry opt for Drawer AI to boost their bid production, minimize expensive mistakes, and achieve a competitive edge in the marketplace with more efficient estimating methods.