Case study • Automotive • Safety Tech
Real-Time Connected Vehicle Platform Revolutionizes Automotive Safety for a Leading Innovator
Our client aimed to enhance road safety by building a real-time vehicle data platform that detects risky driving behavior and delivers instant alerts. We developed a scalable, cloud-based system integrated with in-vehicle hardware and automotive protocols — reducing accidents, cutting operational costs, and accelerating time-to-market.
Success Highlights
Key Details
Industry: Automotive / Safety Tech Geography: Global
Platform: Real-time connected vehicle data platform integrated with in-vehicle hardware
Business Challenge
Our client’s vision required more than traditional telematics — they needed a platform capable of responding to live data in real time, adapting to driver behavior, and scaling without compromise.
Full support for OBDII, CANBUS, and J1939 protocols was essential for hardware interoperability.
A streamlined, map-centric interface was required to simplify navigation and encourage driver engagement.
Our Solution Approach
We engineered a connected vehicle platform that transforms raw data into actionable insights — powered by real-time analytics, feedback-driven workflows, and scalable cloud infrastructure. The platform was designed to help drivers self-correct behavior while giving administrators visibility into fleet-wide performance and safety.
1 · Analyze
Assess Hardware Integration & Protocol Compatibility
We analyzed the client’s vehicle hardware setup and identified integration challenges. This included aligning with industry protocols like OBDII, CANBUS, and J1939 to ensure seamless communication between in-vehicle systems and the cloud platform.
2 · Architect
Design Scalable Cloud Infrastructure
We designed a scalable, cost-efficient cloud architecture capable of handling over 15 million data packets daily. The system was built to support thousands of connected vehicles and automatically scale based on load.
3 · Activate
Implement Real-Time Monitoring & Feedback Loops
We enabled real-time detection of high-risk driving behaviors like speeding, hard braking, and distracted driving. These events triggered instant alerts and fed into behavior-scoring systems that encouraged safer driving.
4 · Optimize
Deliver Measurable Outcomes & User Engagement
We gamified the platform experience and implemented instrumentation for tracking ROI. With simplified UX, actionable analytics, and safety-driven feedback, the platform reduced accidents by 86% and cut operational costs drastically.
Technical Highlights
Real-time vehicle data processing (15M+ packets/day)
Protocol support for OBDII, CANBUS, J1939
Scalable cloud infrastructure with real-time analytics engine
Behavioral scoring and alert system
Map-centric, gamified user interface
// function processVehicleData(vehiclePacket):
if isValid(vehiclePacket):
parsedData = parseProtocol(vehiclePacket, protocols=[OBDII, CANBUS, J1939])
riskEvents = detectRiskBehaviors(parsedData)
if riskEvents:
sendRealTimeAlert(vehicleID, riskEvents)
updateDriverScore(vehicleID, riskEvents)
logEventToFeedbackLoop(vehicleID, riskEvents)
storeToCloudDB(parsedData)
return status: “processed”
else:
return status: “invalid packet”
Business Outcomes
By combining protocol compatibility, scalable cloud architecture, and real-time behavior analytics, the platform delivered tangible and measurable business outcomes.
86%
Reduction in Accidents:
Real-time behavioral feedback led to dramatic improvements in driver safety.
3X
Faster Go-To-Market:
Solution was deployed in just 10 weeks, enabling rapid traction and client acquisition.
25%
Reduction in Risky Behavior:
Real-time alerts and gamified UX reduced distracted and aggressive driving across the fleet.
Ready to Build a Real-Time Vehicle Safety Platform That Delivers Results?
Let’s build intelligent, data-driven solutions that measure what matters, scale effortlessly, and make roads safer — one data packet at a time.