Technology
The tools we use are only interesting for what they enable together: reliable industrial AI systems running in real factories.
Every ROBOMIND system follows the same architecture: industrial equipment is connected through standard protocols, data is collected and stored at the edge, AI models process it locally, and results reach people and systems through dashboards, alerts, and integrations. These are the building blocks we use at each layer.
Edge & Compute
The hardware layer that runs AI where the machines are.
NVIDIA Jetson
Orin Nano, Orin NX, and AGX Orin platforms for compact, energy-efficient edge inference and real-time video processing.
Industrial PCs & GPUs
Fanless industrial computers and GPU servers for heavier workloads, on-premise AI processing, and training.
Connectivity & Protocols
How we get data out of machines – directly and reliably.
OPC UA
The standard interface to modern PLCs, CNC controls, and machines – structured, secure machine data.
MQTT
Lightweight publish/subscribe messaging that moves edge data through the factory reliably.
Modbus TCP & PLC protocols
Direct communication with PLCs and older equipment, plus robot-specific protocols for major robot brands.
REST APIs
Integration with MES, ERP, quality systems, and any modern software over standard web interfaces.
Data & Storage
Where production data becomes structured and queryable.
InfluxDB
Time-series storage for high-frequency machine signals – currents, temperatures, states, cycle times.
SQL databases
Relational storage for production records, inspection results, traceability, and reporting.
Grafana
Dashboards and alerting on top of the collected data – from shop-floor displays to management views.
AI & Software
The intelligence layer – built and maintained by our engineers.
Web-based applications
We build web-first: every interface we deliver runs as a web application on an on-premise web server, so operators and engineers can access it easily from any browser on the secure local network – no client installation, no cloud dependency.
AI vision models
Object detection, segmentation, classification, anomaly detection, and OCR models – trained on your production images, validated against production criteria, and optimized for real-time inference on edge hardware.
Local language models
On-premise LLMs that power industrial AI agents without sending company data to public cloud services.
Python
The engineering language of our data pipelines, AI models, and integrations – maintainable and industry-proven.
On-premise AI
The principle behind it all: models run inside your factory, under your control, integrated with your systems.
How it fits together
A typical system: an NVIDIA Jetson or industrial PC sits next to the line, collects data over OPC UA and MQTT, stores it in InfluxDB and SQL, runs vision or anomaly-detection models locally, shows results in Grafana and custom dashboards, and reports decisions back to the PLC – all delivered as web-based applications served inside your factory network, easily accessible from any browser on the secure local network.
Interested in this solution?
Tell us about your machines and processes – we will propose a practical architecture and a pilot you can evaluate.
Discuss your project