The most impressive trait about the Jelvix team is that you can't give them a task or idea too large. No matter how grand a vision you may have, they'll always have a solution or means to accomplish it.
Thank you, Jelvix, making our vision into a reality. You executed, delivered and were responsive through the whole project. The finished product has an awesome look, feel and user experience that will change the way physical therapists and patients interact between visits.
Our application was finished and able to generate revenue within one year as the Jelvix team adhered to the required timeline efficiently and professionally. They were communicative, responsive, and always available to take on feedback and make tweaks or changes as required.
Jelvix delivered digital products that are fit for purpose and, in the case of the mobile apps, award-winning. Led by an engaged project manager, communication with the development team is smooth and purposeful. They contributed conceptually to the solutions and were excited to problem-solve.
Our goal is to build software solutions that truly matter, making the world a better place for everyone while helping entrepreneurs succeed in their journey.
For 15 years, Jelvix has been a strategic tech partner for global leaders and innovators. We leverage high-end design, rigorous QA, and expert consultancy to engineer scalable solutions that turn complex business challenges into market-leading products.
We built a production-grade real-time ETL infrastructure on AWS and an EV data management portal, giving managers and vehicle owners a single source of operational truth, delivering a full-cycle enterprise software development engagement.
The client is a US-based company in the Electric Vehicles and Connected Mobility space, helping EV owners extract value from their vehicles through data-driven services and analytics. The business depends on continuous access to connected vehicle data from several major automotive OEM APIs used for customer features, support, and monitoring.The company had no stable electric vehicle database or EV fleet management software infrastructure to handle real-time data ingestion from multiple providers. This project combined expertise in automotive software development, cloud infrastructure, and real-time data engineering.
The client’s business runs on vehicle data. Without a connected vehicle platform with feeds from multiple global automotive brands, their service to EV owners did not work. Operational painData availability was inconsistent through three separate manufacturer APIs, each with different formats and frequency of updates. Disconnections were random, leading to missing data, duplicate data, and latency issues. There was no existing tool that could enable the support team to find and act on EV telematics data when needed.
Technical gapThe client had no AWS infrastructure or OEM API integration expertise. They needed a partner with Big Data automotive experience. They also needed an architecture capable of handling three OEMs, normalizing their data into a single model, sustaining 99.9%+ uptime, and surfacing everything through a web portal for managers and users.Business riskEach failed event translated to a poor user experience. An alert about a low battery not being sent out or a malfunctioning system going undetected meant an unsatisfied customer. Expansion of the company without a solid data infrastructure was impossible.
Jelvix’s SaaS app development process involved two separate solutions.Layer 1: Real-Time ETL Infrastructure on AWSThe key challenge was real-time data ingestion from telematics devices made by three separate vendors. Jelvix opted for an event-driven architecture running on AWS rather than a regular batch ETL process.Ingestion is performed using Amazon Kinesis Data Streams, where each stream corresponds to a manufacturer. Critical events are sent through priority streams.AWS Lambda functions normalize and transform each OEM’s payload into a unified electric vehicle dataset.Amazon S3 stores raw and processed records; Amazon RDS holds structured data for the application layer. AWS API Gateway served as the unified entry point for all OEM integrations.The most complex engineering work centered around the OEM integrations. The proprietary connected services APIs of the respective automakers all require dedicated connectors with custom authentication handling, retry logic, error classification, and monitoring. This architecture enabled 99.9%+ pipeline uptime in production with zero data loss. AWS CloudWatch provided continuous monitoring and alerting across the entire pipeline. Layer 2: EV Data Management PortalThe second product was a two-role web application built from scratch, from wireframes through production deployment.For operations managers, the connected vehicle platform replaced manual workflows with a unified dashboard showing real-time vehicle status across all three OEM integrations, with search by VIN, event history, analytics, and automated alerts.For EV owners, the portal provides a personal cabinet with current vehicle status, battery charge, trip history, and diagnostics, plus notifications for low charge and upcoming maintenance.
Integrated OEM streams
Engagement length
In one solution
The platform runs on an event-driven AWS IoT connected mobility architecture designed to ingest, normalize, and serve connected vehicle data from multiple OEM providers.Data Ingestion LayerAmazon Kinesis Data Streams receives live data from all three providers via AWS API Gateway. Custom OEM connectors handle authentication, rate limiting, and failure behavior independently, with retry logic and error handling built in.Processing LayerThe AWS Lambda serverless real-time ETL functions normalize, validate, and transform all incoming streams according to the unified model, regardless of the format used by OEM providers.Storage LayerRaw data lands in Amazon S3 with lifecycle policies. Normalized data flows into Amazon RDS, query-ready for the application layer.Application LayerOperation managers and end users benefit from using the React.js portal through the REST API. While operations managers have access to dashboards, search, and monitoring tools, EV owners have their personal vehicle cabinet in the portal.Monitoring and ReliabilityThe real-time ETL pipeline is monitored by AWS CloudWatch. Custom alerts track OEM connection status and flag processing errors or data anomalies before they reach users.
The delivery team included specialists in cloud infrastructure, backend engineering, frontend development, and UI/UX:Project Manager: Maintained delivery schedule, handled communication with the customer, and focused on the sprint backlog.Solution Architect: Took care of AWS architecture design, OEM API integration, and solving difficult technical decisions in the infrastructure.Backend Developer: Created ETL Lambda functions, OEM connectors, REST API, and database.Frontend Developer: Implemented management portal, user cabinet, and dashboard.UI/UX Designer: Provided full interface design from sketches/UI kit to finished dual role management portal.
Rather than delivering everything at once, the project evolved through structured iterations — each producing working, testable software.Infrastructure Foundation: AWS architecture design and a proof of concept: connecting the first OEM API and validating stable data flow through the Kinesis pipeline. The goal was to ensure the foundation could handle production workloads before scaling.ETL Development and OEM Integrations: Integration of the production APIs of multiple global automotive manufacturers that includes authentication, retry logic, rate limiting, lambda normalization, and storage in S3 and RDS database. Web Application: Jelvix experts developed the backend API and the first version of the management portal with dashboards, search, and filtering tools. The UI/UX was designed from scratch for EV support workflows.Feature Expansion: Analytics, event history, alerting, and the user vehicle cabinet were connected to live data. Dual-role architecture validated with real users.Stabilization and Ongoing Development: Pipeline optimization, monitoring instrumentation, and production hardening. Development continues on a T&M basis per client priorities.
The solution combined cloud-native infrastructure with a scalable frontend and backend:Front-end: React.js, TypeScript.Back-end: Node.js, Express, REST API.Database: PostgreSQL (Amazon RDS).Cloud Infrastructure: AWS Kinesis, Lambda, S3, RDS, API Gateway, CloudWatch, IAM.Data Processing: Python (Lambda functions), ETL transformations, data normalization. OEM Integrations: Proprietary Third-Party Automotive Telematics APIs (Major US and Asian OEMs).
Jelvix built a production-grade connected vehicle platform that gave the client stable, real-time control over OEM vehicle data across multiple automotive brands.
Real-time ETL pipelines replaced unstable OEM data flows with a resilient infrastructure capable of processing connected vehicle data without interruptions or loss.
Data from three separate OEM APIs was standardized to provide the customer with a unified electric vehicle database.
Managers received a centralized EV fleet management software portal with live vehicle search, monitoring, and diagnostics tools, reducing manual investigation time during support requests.
The event-driven AWS architecture made it possible to add new OEM integrations through separate connectors without redesigning the core platform.
EV owners gained direct access to live vehicle status, trip history, battery information, and service alerts through a dedicated user cabinet.
Monitoring, retry mechanisms, and pipeline monitoring kept uptime at 99.9%+ and ensured no data loss during all production OEM integration services.
The EV data management portal and infrastructure became the operational backbone of the client’s EV services business.
Continuous, uninterrupted data connections to all integrated OEM providers in production.
Every vehicle event from every OEM provider was processed and stored correctly.
Multiple major automotive platforms are running simultaneously in a single normalized data model.
ETL infrastructure + management portal — architecture through production deployment.
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