FundedHere Header Logo
Rider Dome
Rider Dome uses Computer Vision & AI-Technology to keep riders safe.
Y% undefined $X,000,000
3 months ago

Investors, please reach out to [email protected] if you have any questions regarding this investment opportunity or indicate your soft commitment through the link above!

We want to invite you to join us for a pitching and Q&A session with the founders! Click on the respective link to sign up.

Pitch Session 

Q&A Session 

Access Data Room Here 

Recently featured in TechInAsia and TodayOnline, Rider Dome has raised a total of $1m for their current fundraising round from their own angel investors, FundedHere is excited and honored to help Rider Dome raise $300,000 to close their fundraising round.

Quick Pitch

Rider Dome is an Advances Rider Assistance System (ARAS) for motorcycle riders and fleets. It uses Computer Vision, Real-Time Alerting, Data Analytics, and Rider Profiling to offer end-to-end Rider Safety. 

Problem Statement

With more than 300 million motorcycles on the road, motorcycles account for 28% of all fatal accidents. Fatal accidents are 13x more likely to happen on a motorcycle than in a car.

Top Causes of Motorcycle Accidents

  • Front collision
  • Safe distance
  • Blindspot
  • Dangerous overtaking by cars


Rider Dome ARAS system is a Computer Vision and AI-based collision alert system providing motorcycle riders with real-time alerts against potential threats on the road to prevent accidents before they happen. 


Market Opportunity

  • Motorcycle market size shows an annual growth rate of 6.91% from 2019, resulting in a projected market volume of US$140b by 2025 (US$70b in Asia)
  • Motorcycle Safety Gear market size is expected to reach US$17.2b by the year 2025. 
  • Electric Motorcycle - Fast growing market opportunity which Rider Dome is targeting. Market size currently is US$30b, growing at a CAGR of 4% expected to reach US$40b in 2026. 

Product Summary

AI-based Riders Advanced Assistance Systems (ARAS) - With a proprietary patented computer vision algorithm that analyses real-time data from front and rear cameras to detect potential threats on the road. 

The system sends non-intrusive alerts, providing the rider with enough time to react and make the safest decision possible. 

Technology Components

  1. AI Processing Unit (APU) - Analyzes the video, detects scenarios where there may be an imminent danger, and alerts the rider.
  2. Wide Angle Cameras - Front and rear end of the motorcycle
  3. Alert Systems - Mounted on the motorcycles' mirror/dashboard



Rider Dome Analytics

For fleet management and insurance companies, the system collects data, provides analytics and reports on crucial safety features that produce advanced analytics on the rider's behavior and hazards on the road. 

  • Data Analytics - For insurance and fleet management, it provides analytics through reports for the rider
  • Rider Blackbox - Complete log of the rider's activity and reminder for maintenance
  • Added Value - Emergency beacon to trigger automatic rescue alert. 

Business Model (B2B)

  • Safety as a Service (SaaS), Fleet Management - Food delivery, logistics, ride-sharing, law enforcement, and posts.


  • Aftermarket and Integrated ARAS - Motorcycle manufacturers (OEMs) & tier-1 suppliers, distribution via dealers and brand agencies. Rider Dome can earn on per motorcycle royalties.


  • Pilot with a large logistics fleet in Singapore to start in Q4 2021
  • LOI for a pilot with food delivery company in Singapore in Q1 2022
  • Pilot with a top pizza delivery company in Israel in Q1 2022
  • Advanced the discussions with manufacturers, mainly with a well-known motorcycle manufacturer in the USA and a leading motorcycle and sports car manufacturer in Austria.

Competitive Landscape


Key Team Members


Fundraising Round

Rider Dome is raising a S$1.3m round through a SAFE note, of which S$300,000 have been allocated to FundedHere.


Mobility safety startup raises $1m to help prevent motorcycle accidents

Near Miss inspires Singapore-based entrepreneur to create a motorcycle collision alert system