FLEDEM
Fleet-analytics platform for FEV Software GmbH
Contracted as a full-stack engineer to help transform FEV's fleet analytics platform into a more reliable, usable, and scalable product. Worked on core analysis workflows, data configuration flows, and engineering-facing tools — across a large React + ASP.NET Core + MongoDB codebase processing CAN signal data from connected vehicle fleets.
4
core modules contributed
Cross-stack
frontend + backend + infra
4 months
Sep 2025 – Jan 2026
Enterprise
scale & complexity
Overview
Making complex fleet data feel usable
FLEDEM is FEV's internal fleet-analytics platform — used by test engineers to define, validate, and reuse analysis logic against CAN-signal telemetry from connected vehicle fleets. Before this engagement, configuration-heavy flows were fragmented and engineers leaned on external scripts to get things done.
My contract focus was reducing that friction inside the product. I built features that let users define and reuse analysis logic directly inside the platform, simplified complex create/edit flows, and standardized UI patterns across configuration-heavy screens so the platform felt consistent end-to-end.
Beyond shipping features, the engagement included a meaningful amount of platform-quality work: contributing to automated testing, API documentation, security review, and build-quality improvements across the large frontend/backend codebase, plus role-based access patterns, reusable notification/confirmation systems, and design-system alignment for future modules.
Modules
Four interconnected modules
As a contractor inside a distributed engineering team, I owned features across these four modules — each bridging user-facing flows, REST API contracts, and the data layer.
Scripts module
User-facing CRUD for Python analytics scripts — Monaco editor for in-platform editing, channel-mapping UI for binding inputs to CAN signals with unit conversion, and fleet-scoped access so scripts only run against authorized vehicle data.
React · Monaco Editor · ASP.NET Core API · Python runtime
Calibration module
Calibration management linking calibrations to projects, scripts, and analysis packages. Backend schema design, REST endpoints, and a React UI with file-storage integration so engineers could attach, version, and reuse calibration files alongside analysis runs.
MongoDB · ASP.NET Core · React · Azure Blob Storage
Events module
Event detection and management — severity classification, attachment handling, configurable definitions, filtering system, and statistics visualization. Built the event-definitions UI and the supporting REST contracts.
React · SignalR · Chart.js · PDF export
Analysis Package module
Integration layer connecting analytics scripts to CAN signal configurations. Built the signal-mapping UI (unit conversion, logger slot management) and the configuration-GUID resolution layer using a URN/UUID scheme so signals stay stable across config revisions.
React · TypeScript · CAN signal configuration parsing
Engineering Challenges
The hard parts I worked on
Configuration-heavy flows that confused users
Solution · Refactored dominant create/edit patterns into a consistent stepper + side-panel model, deduped form components, and aligned validation feedback so the same edit primitives behaved identically across modules.
Outcome · Reduced cognitive load on configuration-heavy screens — engineers stopped relying on external scripts for routine setup work.
Bringing analysis logic inside the platform
Solution · Built the in-platform Scripts module — Monaco-editor authoring, channel-mapping UI for binding script inputs to CAN signals with unit conversion, and persistence so scripts could be reused across calibrations and analysis packages.
Outcome · Analysis logic moved from one-off external scripts into a versioned, reusable, fleet-scoped resource inside the product.
RBAC across modules without repeating yourself
Solution · Contributed to role-based access patterns and reusable confirmation/notification components so new modules inherit the same RBAC + UX guardrails by default rather than reimplementing them.
Outcome · Future modules align with the same access-control + design-system patterns from day one.
Quality bar across a large codebase
Solution · Beyond features, contributed to automated testing, API documentation, security review, and build-quality improvements across the frontend/backend codebase — especially around the modules I touched.
Outcome · Modules I owned shipped with the test, docs, and security review needed for handover.
The Stack
How it's built
Enterprise-grade stack chosen to handle real-time CAN telemetry, Python analytics, and multi-tenant fleet operations end-to-end.
Backend
- ASP.NET Core (.NET 8)
- SignalR — real-time hubs
- Python — analytics runtime
- JWT authentication + RBAC
Frontend
- React + TypeScript
- Tailwind CSS
- Monaco Editor
- Chart.js
Database
- MongoDB
- Binary UUID indexing
- Apache Parquet — time-series
- Fleet-scoped access patterns
Infrastructure
- Azure Blob Storage
- Webpack
- Python simulation tooling
- Visual Studio 2022
What I Delivered
Outcomes from a 4-month contract
- 01
Reduced workflow friction for fleet engineers by enabling them to define, validate, and reuse analysis logic directly inside the platform — instead of relying on fragmented external scripts.
- 02
Improved platform usability and consistency by simplifying complex create/edit flows, standardizing UI patterns, and making configuration-heavy screens easier to operate.
- 03
Strengthened product reliability by contributing to automated testing, API documentation, security review, and build-quality improvements across a large frontend/backend codebase.
- 04
Supported enterprise readiness by contributing to role-based access patterns, reusable notification/confirmation systems, and design-system alignment for future modules.
- 05
Operated as an independent contractor within a distributed engineering team, owning end-to-end delivery of assigned features.
FLEDEM is FEV Software GmbH's internal product. Screenshots and proprietary architectural details are excluded under NDA; the contributions described above are reflected in the engineering record and can be verified with the FEV team on request.
Need an engineer for your enterprise platform?
I take on senior contract work across React, .NET, MongoDB, Python, and SignalR — comfortable shipping inside large distributed engineering teams.