How Condense Transforms Vehicle Data into Fleet Decisions - On Demand Webinar

On June 26, 2025, Zeliot and iTriangle delivered a live technical demonstration that turned a bold claim into a tangible system: building a complete, real-time vehicle control pipeline, inside the customer’s own cloud, in less than 40 minutes. 

No mockups. No preloaded scripts. Just real data from a live iTriangle telematics device, a Git-backed geofence transform, Kafka topics running in BYOC (Bring Your Own Cloud) mode, and output to PostgreSQL and a connected FMS system. 

Watch the Full Webinar Here: Webinar Recording

What the Webinar Demonstrated 

This wasn’t a theoretical pitch. The live demo walked through the complete lifecycle of a real-time geofence control system: 

• Live Ingestion from an iTriangle STS-101 device installed in a demo vehicle 

• Periodic Parsing via prebuilt Condense transform to generate continuous telemetry 

• Geofence Logic deployed from Git using Condense’s custom logic framework 

• Alert Routing to PostgreSQL and Kafka-connected FMS tools 

• BYOC Kafka setup on AWS with zero-touch DevOps 

• End-to-End Observability through Condense unified UI (logs, metrics, traces) 

All configured live by Zeliot’s team in front of a technical audience, without relying on any auxiliary cloud orchestration or manual infrastructure setup. 

A Keynote That Set the Context 

Before diving into the technical build, the session featured a keynote by Vadiraj Katti, Managing Director at iTriangle. His remarks contextualized the collaboration between iTriangle and Zeliot, emphasizing their joint focus on scalable telematics, clean data, and cost-optimized real-time mobility applications. 

Vadiraj outlined iTriangle’s journey in building holistic telematics devices with a footprint of over 2.5 million installations across India, Middle East, and Southeast Asia. He highlighted their sector-specific product lines, from OBD and ADAS to EV compliance and OEM-centric edge solutions. 

Key innovations discussed included: 

• Vehicle Firmware Upgrade Over-the-Air (Aquila Edge): Letting OEMs remotely flash and debug ECU modules. 

• Edge-Level Computation: Deriving critical operational parameters (speed, trip distance, coolant temp, ignition status, etc.) in-device to reduce cloud dependency. 

• Vertical Focus: Supporting mining, logistics, passenger transport, and fleet management, all through tailored data points and compliance support. 

The keynote closed by reinforcing how the iTriangle <> Zeliot partnership delivers not just telemetry, but actionable value: cleaner data pipelines, enhanced observability, and faster go-to-market solutions for fleet intelligence. 

Technical Breakdown of the Live Build 

Here’s how the real-time control system was built live: 

1. Kafka + BYOC Foundation 

All infrastructure ran inside a customer-owned AWS account via Condense BYOC deployment. Kafka topics, Postgres database, and Git-integrated transforms were fully instantiated in the demo cloud. This ensured: 

• Data sovereignty 

• Zero vendor lock-in 

• Transparent cloud billing 

• Alignment with enterprise IAM policies 

2. Real Device, Real Data 

An iTriangle TS-101 device in a demo vehicle streamed TCP location data at high frequency. Condense protocol-aware prebuilt connector decoded this in real time, exposing structured payloads (latitude, longitude, speed, ignition, etc.) without manual parsing. 

3. Prebuilt Periodic Transform 

Condense low-code periodic transform created structured, heartbeat-style messages at consistent intervals. These acted as input for downstream applications, simplifying geofence state monitoring. 

4. Git-Based Geofence Logic 

A custom geofence application, written in Python and versioned in Git, was deployed live using Condense transform builder: 

• Input: GPS location from periodic output 

• Logic: Geo-boundary check using configured polygon radius 

• Output: Alert payload to PostgreSQL and Kafka for FMS visibility 

This containerized transform was CI/CD-ready, rollback-safe, and updated without restarting Kafka pipelines. 

5. PostgreSQL + FMS Integration 

Two output sinks were configured: 

• A Kafka-to-Postgres connector with schema control and retention policies 

• A Kafka-forwarder that pushed alerts to a connected Fleet Management System dashboard 

Together, they enabled historical storage for analysis and real-time visibility for operations. 

What Makes This Important 

This webinar didn’t just show a working demo; it modeled a fundamentally better way to build real-time systems: 

Final Takeaway 

By the end of this session, a fully operational geofence alerting system was running live, in a customer’s cloud, from raw GPS data to actionable FMS alerts. 

There was no simulation. No code editing during the demo. No dependency on SREs. Just a clear example of what’s possible when: 

• A domain-specific Kafka platform (Condense) 

• Meets hardware-aware device providers (iTriangle) 

• And skips the glue code chaos that burdens most real-time stacks. 

🔗 Watch the Full Webinar: Webinar Recording

If your teams are working on real-time mobility, geofence compliance, or vehicle intelligence systems, this session is worth watching, not just for the product, but for how it redefines execution. 

Let us know if you’d like a personalized walkthrough or want to replicate a similar system in your cloud.