Digitizing Mining: How a Commercial Vehicle OEM Optimized Trips and Terrain Using Condense, Without Managing Infrastructure
Written by
Sachin Kamath
.
AVP - Marketing & Design
Published on
Jul 1, 2025
A mining-specialized truck manufacturer built a real-time, low-latency data backbone to orchestrate trips, optimize terrain, and unlock site-wide mobility insights by offloading all streaming complexity to Condense.
Description
Mining mobility is messy. The terrain shifts weekly. Dispatch sequences are fluid. Vehicle behavior depends on real-time coordination, not static logic. A prominent truck OEM, already known for its deep mining expertise, decided to address this head-on, not by scaling hardware, but by digitizing site operations at their source.
Their vision was clear : digitize mine-site operations by connecting vehicles, drivers, sensors, and systems into a single, real-time ecosystem. But equally clear was their boundary: they would not manage Kafka clusters, cloud provisioning, or data pipelines. Their expertise lay in solving mobility problems, not building infrastructure.
Condense, already deployed on their cloud for centralized vehicle data management, became the streaming backbone. It handled ingestion from over seven heterogeneous sources, vehicle telematics, industrial sensors, edge cameras, and apps. While delivering low-latency, high-throughput data to site coordination systems and operational dashboards. The result? A real-time decisioning layer for mine-site mobility that didn’t require a single infra engineer.
TLDR;
Domain: Mining mobility orchestration by a specialized truck OEM
Deployment Model: Condense on OEM-owned cloud (BYOC)
Data Sources: 7+ including telematics units, cameras, apps, and sensors
Operational Focus: Real-time trip coordination, terrain improvement, site-wide optimization and Increase in number of trip by +2 per shift per vehicle
Streaming platform Infra management ownership: Zero, fully offloaded to Condense
Impact: Higher trip throughput(+2 trip/vehicle/shift), lower fuel wastage, improved driver compliance, and OEM upsell stickiness
Highlights
Digitized a complex, unstructured mobility environment without building infra
Managed streaming ingestion from edge to application with no Kafka operation and maintenance
Enabled real-time coordination across vehicles and mining equipment
Supported feedback-driven terrain improvement suggestions
Delivered value to site operators, increased NPS, and improved vehicle loyalty
Executive Summary
Mining operations don’t resemble typical fleet environments. There are no fixed routes, no standard traffic signals, and no predictable terrain. Vehicles move dynamically based on excavation progress, shift changes, and equipment availability. In such a high-cost, low-tolerance environment, operational misalignment costs time, fuel, and safety.
A leading truck OEM, already known for building high-specification vehicles for such environments, realized that hardware alone couldn’t solve the coordination problem. They needed to digitize the movement of equipment, align driver instructions in real time, and continuously improve site workflows.
But they had no appetite for managing Kafka pipelines, cloud clusters, or operational patching. Their goal was to work at the use case layer, not the infrastructure layer.
That’s where Condense came in.
With Condense already deployed on the OEM’s cloud for vehicle data centralization, it was extended to handle site-wide streaming orchestration. Condense ingested data from seven different systems, ranging from on-vehicle CAN data to terrain-monitoring sensors and delivered enriched events to the application layer. The OEM’s engineering teams used this to build coordination logic, trip alignment tools, and terrain feedback dashboards.
Critically, the OEM deployed zero infrastructure to do this. Condense owned the Kafka layer, managed ingestion connectors, performed upgrades, and auto-scaled throughput based on vehicle count. The OEM’s engineers focused purely on designing smarter mine mobility, faster trip sequencing, more accurate terrain tuning, and better driver alignment.

About the Company
This OEM is known for building industrial-grade trucks tailored for off-road and specialized use cases, especially mining, quarry, and construction operations. Their product engineering teams have deep, field-tested knowledge of vehicle behavior under extreme conditions. Where uptime, coordination, and control room efficiency are non-negotiable. In 2023, they launched a parallel initiative to digitize mining mobility focusing on real-time coordination, intelligent trip routing, site-specific intelligence and terrain-based feedback systems.
How Did Condense Help?
The Challenge
Mining isn’t a typical logistics environment. Movement is reactive, the terrain deforms, and vehicle instruction happens at short notice. The OEM’s engineers had an intimate understanding of what goes wrong on mining sites:
Trucks queuing inefficiently
Equipment left idle
Delays in dispatch instructions
Terrain changes impacting route selection
Trip records fragmented across devices
Their goal: orchestrate the entire site in real time by
Streaming telemetry from all moving assets
Sending live trip instructions based on dispatch availability
Feeding back terrain patterns to suggest regrading or route tweaks
But,
They didn’t want to manage Kafka, clusters, ingestion logic, or deployments
They needed sub-second delivery latency
They couldn’t hire a team for infra observability, alerting, or versioning
They needed full abstraction of infrastructure, while retaining full control over use case design.
Solution Architecture with Condense

Condense, already running on the OEM's cloud, was extended to power this mine-site digitization initiative.
1. Ingestion from 7+ Sources
OEM-installed telematics devices (custom formats and protocols)
Tip down and up sensor mounted on vehicles like excavators and trucks
Third-party video edge analytics (camera-based event triggers)
Application-generated trip assignments (dispatch logic)
Environmental sensors (temperature, terrain vibration, pit monitoring)
Manual feedback entries (driver or supervisor input)
2. Stream Processing
Transforms for event timestamping, trip state recognition, and instruction routing
Trip replay segmentation and streaming joins across sources
Terrain anomaly detectors using slope + trip outcome correlation
Low-latency logic blocks (under 500ms event-to-app delivery)
3. Delivery Layer
Streaming APIs into custom-built operator dashboards
Webhooks for alerts and instruction dispatch
Archive sinks into OEM data lake for post-run analysis
All with sub-second median latency, no buffering, and high durability
4. Infra Operations (Offloaded)
Kafka provisioning, scaling, and partition tuning handled by Condense
Rolling updates, version upgrades, secrets rotation, and CI/CD integrated
FinOps dashboards allowed the OEM to see cost-per-vehicle in real time
No need for cluster engineers or cloud architects
Summing it up

Condense provided more than Kafka. It gave the OEM:
A real-time coordination layer
Connector abstraction for sensor and telematics diversity
Zero-touch operations via managed deployment
Multi-tenant, multi-environment isolation
Production-grade reliability at field scale
Condense became the operational backbone for mobility digitization:
Function | Handled by Condense |
Kafka provisioning | ✅ Yes (BYOC, with SLA-backed 99.95% uptime) |
Multi-source ingestion | ✅ Yes (vehicles, apps, sensors, cameras) |
Transformation + parsing | ✅ Yes (Git-backed and low-code logic) |
Application integration | ✅ Yes (APIs, WebSockets, webhooks) |
FinOps and autoscaling | ✅ Yes (dynamic compute allocation) |
Cluster ops and upgrades | ✅ Yes (zero-touch, fully managed) |
The OEM’s engineers never wrote a Helm chart, debugged a broker, or scaled a topic. They built a domain-specific solution that increased trip velocity, reduced idling, and informed future site layout, proving value not just in trucks, but in the intelligence running alongside them.
This abstraction enabled the OEM team to spend zero effort on infrastructure, and full effort on innovating for rare, high-impact operational use cases.
They were able to:
Improve round-trip throughput on mining sites
Reduce idle time across loaders and haulers
Recommend terrain changes to improve future trip efficiency
Increase vehicle uptime and prove value to site owners

Switch to Condense Now!
If your focus is industrial mobility like mining, construction, ports, or yards and your teams domain expertise lies in coordination, behavior, or logistics not infrastructure, Condense gives you everything between ingestion and insight, lets your engineers build what matters.
🚀 Book a deep-dive session to explore how Condense enables site-wide coordination, terrain tuning, and real-time action pipelines, fully Kafka-native, fully managed.
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