How One of India’s Largest Commercial Vehicle Manufacturers achieved Kafka-Native Sovereignty with Condense

A leading OEM migrated from rigid, generic streaming infrastructure to a Kafka-native, vertically Industry specific optimized real-time data platform achieving full control, faster innovation, and significant operational gains without compromising scale. 

Description 

As one of India’s most recognized commercial vehicle OEMs, this manufacturer has been at the forefront of connected mobility. With a fleet of over 250,000+ vehicles generating high-frequency telematics data, the need for a scalable, real-time streaming backbone became critical. But their existing data platform couldn’t keep up. 

Legacy systems lacked mobility-specific features, forced a tightly coupled cloud dependency, and introduced friction at every step, from ingesting data to building applications. The OEM needed more than Kafka-as-a-service. It needed a domain-aware platform built for speed, scale, and sovereign control. 

Condense, with its Kafka-native architecture and Bring Your Own Cloud (BYOC) deployment model, enabled the OEM to gain full control over its infrastructure, simplify engineering, and accelerate real-time innovation across its connected vehicle ecosystem. 

TLDR;

• Industry: Commercial Vehicles & Connected Mobility 

• Fleet Size: 250,000+ vehicles 

• Previous Stack: Generic managed streaming platform 

• Deployment: Condense on OEM's cloud (BYOC) 

• Scale: 197 TB/month processed, 120–500 Mbps dynamic throughput 

• Latency: Sub-500ms end-to-end of pipeline 

• Availability: 99.95% SLA 

• Cloud: Fully cloud-agnostic (GCP) 

Highlights 

• Migrated from a cloud-locked vendor to Condense Kafka-native BYOC model 

• Achieved full data sovereignty with zero infra lock-in 

• Reduced cloud spend by 20% through elastic resource scaling 

• Cut development and ops effort by 40% 

• Accelerated GTM by 6 months using Condense verticalized mobility modules 

• Enabled continuous, large-scale ingestion from 500+ telematics protocols 

Executive Summary 

A leading commercial vehicle OEM was scaling fast, with over 200,000 connected vehicles and an increasing demand for real-time applications such as predictive maintenance, driver scoring, and route optimization. But their existing data infrastructure had become a bottleneck. 

The incumbent platform offered limited flexibility, lacked domain specialization, and imposed operational complexity that slowed development and inflated cost. Kafka usage was growing but building, scaling, and maintaining custom microservices outside the pipeline introduced friction the OEM could no longer accept. 

The OEM needed to rethink its foundation: move faster, operate leaner, and reclaim control. 

Condense provided that foundation. 

With a fully managed, Kafka-native platform deployed directly inside the OEM’s own cloud environment (BYOC), Condense delivered domain-optimized ingestion, built-in mobility logic, low-latency pipelines, and full operational abstraction. The result was a streaming system the OEM didn’t have to manage, yet could fully control. 

About the Company 

This OEM is one of India’s largest commercial vehicle manufacturers, with a legacy in both long-haul and intra-city logistics solutions. In recent years, it has significantly expanded its connected mobility capabilities, offering integrated digital services to fleet operators nationwide. Its transformation from hardware-centric to real-time, data-first required a platform that could handle streaming workloads at scale without compromising agility, observability, or operational simplicity. 

How Did Condense Help? 

The Challenge 

As vehicle connectivity expanded, the OEM faced mounting pressure across four critical areas: 

1. Rigid Infrastructure and Cloud Lock-In 
   The incumbent streaming platform tightly coupled compute and storage to a single cloud vendor. This restricted performance tuning, inflated regional costs, and limited deployment flexibility. 
   
   

2. Lack of Mobility-Specific Capabilities 
   Real-world needs such as parsing telematics data, evaluating geofences, or integrating with TMS systems required custom code and extra services. There was no built-in support for mobility use cases. 
   
   

3. Fragmented Development Model 
   Writing application logic involved building and maintaining external microservices. This increased development time, introduced scaling complexity, and delayed use case rollout. 
   
   

4. Manual Scaling and Infrastructure Burden 
   The system couldn’t elastically respond to traffic bursts, requiring engineers to constantly balance overprovisioning with performance trade-offs. 

Each of these gaps compounded into a larger systemic issue: the platform was slowing down innovation at a time when real-time was becoming business-critical. 

Solution Architecture with Condense

Condense offered the OEM a complete Kafka-native, mobility-specialized platform without asking them to manage any of it. 

1. Kafka-Native BYOC Deployment 

Condense was deployed directly into the OEM’s cloud account, giving them full control over compliance, data locality, and compute costs without running a Kafka ops team. 

2. Mobility-Specific Data Stack 

With built-in support for 500+ telematics protocols, Condense enabled direct ingestion from the OEM’s fleet. Prebuilt modules for geofencing, driver behavior scoring, and trip intelligence accelerated rollout of real-time applications. 

3. Git-Based Streaming Development Environment 

Instead of building logic as external microservices, the OEM used Condense inbuilt Git-enabled IDE to write, version, and deploy logic directly within the streaming pipeline. This simplified CI/CD workflows and removed integration friction. 

4. Operational Abstraction and Observability 

Kafka scaling, topic management, and patching were handled by Condense. Built-in observability tools gave engineers real-time visibility into latency, throughput, and performance bottlenecks, without needing separate monitoring stacks. 

What was the Result?

Beyond technical outcomes, the OEM regained architectural freedom. The BYOC model means they can deploy across AWS, Azure, or GCP marketplaces with full compliance, zero lock-in, and total operational sovereignty. 

Switch to Condense, Now!

Scaling connected vehicles? Building real-time mobility applications? 
Don’t let infrastructure complexity hold you back. 

Condense delivers Kafka-native streaming, mobility-specific logic, and zero-touch operations all deployed in your own cloud, at your pace. 

Book a technical walkthrough and see how Condense powers real-time mobility transformations at fleet scale.