ROCKSHOX SID ULTIMATE RACE DAY2 3P FLIGHT ATTENDANT 29" Fork 15x110mm Boost Axle Black
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Description
Climb the mountains, descend the slopes: the ROCKSHOX SID Ultimate Flight Attendant fork is designed to push the limits of cross-country riding. Its stiff 35 mm chassis ensures unwavering stability even at high speed, while its 120 mm of travel gives you all the margin you need to tackle technical terrain.
Equipped with the Flight Attendant electronic system, this smart fork anticipates your needs thanks to sensors that analyse the terrain and your effort. The Charger Race Day 2 damper automatically adjusts compression between three modes (Open, Pedal, Lock), delivering uncompromising pedalling efficiency and comfort.
Flight Attendant features a tool that allows the algorithm to learn how you ride in order to continuously personalise your suspension: Adaptive Ride Dynamics. The algorithm collects fresh data to precisely calculate your personalised effort zones throughout the season. Bias Adjust technology gives you the power to fine-tune how Flight Attendant responds to your personal riding style in automatic mode.
The SID Ultimate also stands out with its DebonAir+ spring, optimised for sensitivity on small bumps and consistent support mid-stroke. Maxima Plush oil reduces friction for lasting performance, even during the most demanding rides.
Finally, its compatibility with the SRAM AXS ecosystem and its lightweight design make this fork a concentrated blend of technology and performance. Get ready to reach new heights.
Ref: 15207094288764
Points forts
Chassis with 35 mm stanchions
Debonair+ spring, linear and sensitive on small impacts while providing better support throughout the travel
Ultra-lightweight Charger Race Day 2 cartridge with 3 positions to permanently adapt to the terrain
Maxle Stealth Boost axle standard improving stiffness
Maxima Plush oil and SKF seals to reduce friction
Bottomless Tokens to adjust the fork air volume and fine-tune its behaviour based on your riding style
The Flight Attendant system relies on an algorithm using a series of sensors to understand the rider's effort and the terrain, and to anticipate the ideal suspension position.
