Make complex vehicle analysis easier to work with.
The context
FLEDEM is FEV Software GmbH’s internal fleet-analytics platform. Engineers use it to define, validate, and reuse analysis logic against CAN-signal telemetry from connected vehicles.
My work focused on reducing friction in configuration-heavy workflows: bringing analysis tools into the product, simplifying create and edit flows, and making shared patterns behave consistently across modules.
I owned assigned features across React, ASP.NET Core, and MongoDB, working within a distributed engineering team on analysis configuration, scripts, calibrations, and events.
Inside FLEDEM
A closer look at the workflows I contributed to.
FLEDEM is an internal product under NDA. This page uses an illustrative cover; private product screens and proprietary architectural details are not shown.
The Scripts module gives engineers in-platform authoring with Monaco and a way to connect script inputs to the vehicle signals they need.
Channel mappings, unit conversion, and persistence let analysis logic be reused across calibrations and analysis packages instead of living in disconnected external scripts.
Dense create and edit flows were refactored around consistent stepper and side-panel patterns. Shared fields and validation feedback reduced the number of local conventions a user had to learn.
Calibration files, managed attachments, channel mappings, and stable configuration identifiers give analysis inputs an explicit structure across revisions.
Events connect definitions, severity, evidence, filters, and statistics. The interface needs to preserve domain detail while making it practical to navigate and investigate.
React product surfaces, .NET services, Python analysis, and SignalR event delivery form the cross-stack context of this work.
The engagement also included automated testing, API documentation, security review, and build-quality improvements in the areas I touched.
Reusable confirmation, notification, and role-based access patterns help future modules follow the same product and engineering conventions.
Behind the interface
Shared interaction patterns reduce repeated frontend logic and give engineers a predictable way to build the next configuration flow.
Operational documents, telemetry output, and file assets use different storage formats, including MongoDB, Parquet, and Azure Blob Storage.
My work on FLEDEM
Multi-Brand HR SaaS
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