Rental Announces 2026 Editor's Choice Award Winners

Find new equipment and technology solutions to improve safety and equipment rental ROI with these innovations.

Sep 25, 2026

The Rental Editor's Choice Awards were chosen based on submitted nominations and their potential impact on the general tool and equipment rental industry. The entry form requested companies to describe their product and the key features that make it unique for rental businesses.

Rental presents the winners below, grouped by category: Equipment, General Tool, Generator & Power Equipment, Lifting Equipment, and Software & Technology. Click through to find more information on each winning product.

Based on nominations and their potential impact on the general tool and equipment rental industry, Rental 2026 Editor’s Choice winners were selected from new releases or updates to products announced between June 2025 and June 2026.

Of this year’s total entries, 95 percent were new releases, with 5 percent of the entries being enhancements to a previously announced asset. Ultimately, these updated equipment represent roughly 10% of the winning selections. An overwhelming majority (90%) of the winners are new product and solution announcements.

The equipment and general tool industry is relentless in solving the problems of its pro and DIY customers; this year’s winning products were designed to keep equipment rental businesses successful for years to come – from in-office solutions to on the construction site. Rental is proud to congratulate the recipients of the 2026 Editor’s Choice Awards.

Featured

Front Load View Dual Camera System with Human Form Recognition

From Brigade Electronics Inc.

Brigade Electronics Inc.Front Load View is a dual camera system with advanced AI human form recognition software designed for equipment with front load mechanisms such as wheel loaders, forklifts, and reach stackers, regardless of the load they are carrying. This is especially critical for companies that rent these machines, as it provides less experienced operators with audible and visual alerts when a pedestrian is in the vicinity, as well as complete vision at all times in front of the bucket.

Intuitive interface to eliminate training requirements, utilizing triggers to eliminate the need for operator intervention; all processing is housed in-camera, no additional hardware ECU needed
Intelligent firmware and AI human form recognition provide a clear view in front of the front-load mechanism, regardless of the bucket's location or load