Edge and data ingestion layer
We structure data from cameras, sensors, IoT devices and field systems in a controlled and usable architecture.
AI-ready infrastructure
We design scalable infrastructure foundations for enterprise AI initiatives
We connect models, data, edge devices, cameras, sensors and business systems into manageable AI infrastructure that can move from pilot ideas to production operations.
Challenge
AI initiatives need more than model selection
Pilots struggle to reach production when data sources, edge devices and enterprise systems are not designed together.
Performance and cost control become difficult when compute, storage, network and security requirements are not planned early.
AI output creates limited business value when it is not connected to ERP, MES, CRM or field operations.
Approach
We build AI infrastructure together with data, systems and operations
Hades Elektronik evaluates data flows, edge and cloud components, integration points and operating processes as one architecture. The objective is not a disconnected AI experiment, but a secure, observable and scalable production environment.
Capabilities
Core building blocks for AI infrastructure
Compute and storage planning
We design infrastructure capacity around model workloads, data volume, latency expectations and growth plans.
Enterprise system integration
We connect AI outputs securely to ERP, MES, CRM, dashboards and notification systems.
Use cases
Infrastructure for operational AI scenarios
Manufacturing and quality control
A full data foundation for AI scenarios that require computer vision, production data and MES integration.
Field, retail and facility operations
Turning signals from cameras, sensors and edge devices into traceable operational workflows.
Deployment
From AI pilot to managed infrastructure
01
Discovery
Data sources, target scenarios and the current infrastructure are assessed.
02
Architecture
Edge, compute, storage, network and integration layers are planned.
03
Deployment
Required environments and data flows are prepared in a controlled way.
04
Integration
AI outputs are connected to operational systems.
05
Management
Performance, security and improvement needs are monitored over time.
AI infrastructure FAQ
Do you only develop AI models?
Our scope is broader than the model itself; we address data, infrastructure, integration and operations together.
Can this work with our existing systems?
Yes. Existing ERP, MES, CRM, camera, sensor and data sources can be assessed to define a practical integration architecture.
Let’s assess your AI infrastructure readiness
We can review your data sources, business goals and current infrastructure to create a practical AI infrastructure roadmap.