Proximia: IoT platform.
A web app for connected devices, built with Django REST Framework, MQTT and Python. Field devices stream into one dashboard with history and alerting, so operators act on live data instead of site visits.
The challenge.
- Devices in the field reported into nothing coherent, so operators flew blind.
- Readings needed to stream to a dashboard operators could act on.
- The pipeline had to stay reliable across intermittent connectivity.
- Devices misbehave — duplicate readings, clock drift, gaps — and the data layer had to absorb that without lying.
Our approach.
- Built the monitoring dashboard with Django REST Framework for live readings and controls.
- Streamed device data through MQTT and Python.
- Stored time-series readings for history and alerting.
- Handled reconnection so gaps don't corrupt the picture.
- Hardened ingestion against duplicates, gaps and clock drift so history stays truthful.
The outcome.
- Operators see live device data on one dashboard instead of flying blind.
- Readings are stored for history and alerting.
- The pipeline holds up across flaky connectivity.
- History is trustworthy enough to base operational decisions on.
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Where AI fits in manufacturing & industrial.
Assistants that answer engineers' questions from manuals and maintenance history, visual quality checks, and procurement workflows that draft, compare and route supplier documents.
Explore AI developmentOne of their strengths is quickly building out a multi-disciplinary team to work on the development and delivery of features with different technical requirements. Their support has allowed us to accelerate our development work without building an internal team. They have also worked seamlessly with other third parties both during the acquisition of Dragonfly and development of our mobile app.
Let's build from here.
Thirty minutes with an engineer who builds. No sales, no drip campaign. If we're the wrong fit we'll tell you and point you somewhere better.