Was macht Kadasolutions?

Kadasolutions ist ein KI-Beratungsunternehmen, das Unternehmen weltweit bei der Implementierung von künstlicher Intelligenz unterstützt – von der Strategie über RAG-Systeme bis hin zu Prozessautomatisierung und Vibe Code Rescue.

Is Kadasolutions GDPR / EU AI Act compliant?

Yes. All Kadasolutions solutions are designed to be EU AI Act ready and GDPR / DSG compliant. We prioritize data privacy and security for every client.

What is Vibe Code Rescue?

Vibe Code Rescue is a security and code quality service for founders whose AI-generated codebases have vulnerabilities – including exposed API keys, insecure payment integrations, and data loss risks. We audit and fix the code within a fixed-price package.

Welche KI-Produkte bietet Kadasolutions an?

Kadasolutions bietet KadaRAG (offline/on-premise AI für Unternehmen), Kadasync (E-Mail zu ERP Auftragsautomatisierung) und LaneTracker (KI-gestützte Verkehrsüberwachung) an.

Case Study · AgriTech

Prevent machine failures before they happen

AgroSentinels is a real-time monitoring platform for agricultural machinery — AI-powered predictive maintenance that forecasts breakdowns before they threaten the harvest.

Platform:Web

Industry:AgriTech

Website:agrosentinels.com

Project overview

The challenge

Agricultural operations lose yields every year to unplanned machine failures. Traditional maintenance schedules are either too early or too late — there was no data-driven foundation for maintenance decisions.

Our solution

We built an IoT-based monitoring platform that captures sensor data from agricultural machinery in real time and uses machine learning to detect anomalies and predict failures — long before a breakdown occurs.

The impact

Operations can now plan maintenance precisely rather than reacting to failures. Unplanned downtime drops significantly, machines run more reliably, and harvest logistics stay on schedule.

Key features

Predictive maintenance, built for agriculture

Real-time monitoring

Sensor data from all machines streams into a central dashboard continuously — instant visibility across the entire fleet.

Predictive maintenance

ML models detect wear patterns and flag impending failures with enough lead time for targeted, planned maintenance.

Automated alerting

Critical anomalies trigger immediate notifications so the team can act before a failure occurs.

Maintenance dashboard

Maintenance history, open tasks, and machine status in a single view — no paperwork, no lost knowledge.

Design & UX

Built for farm managers, not data scientists

The dashboard was designed for people who manage machines and fields daily — not analysts. Complex sensor data is translated into clear status indicators and actionable alerts.

Mobile-first: alerts and machine status are accessible from the field without needing to be at a desk.

Technology

The tech stack

Flutter Web powers the web dashboard. Python microservices handle data processing and the ML model for anomaly detection. NB-IoT transmits sensor data energy-efficiently from the field, PostgreSQL stores machine and maintenance history, and TensorFlow trains the predictive maintenance models.

Flutter Web

Python

NB-IoT

PostgreSQL

TensorFlow

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