Bytefabrik provides an on-premise IIoT platform that consolidates machine data from diverse industrial equipment into a unified, semantically structured data model. The platform combines an IoT Data Hub with Manufacturing Insights analytics and AI-powered tools like AI Notebooks, AI Pipelines, and a Manufacturing Analytics Copilot, enabling natural-language queries and automated monitoring. It supports protocols such as Siemens S7, OPC UA, MQTT, and Modbus, and is designed for both SMEs and large enterprises.
Funding
Funding not disclosed
Founders
Product
Problem
Industrial companies often struggle with fragmented machine data spread across different systems and protocols, making it difficult to consolidate information and gain a clear view of production performance. This leads to high integration efforts between OT and IT, delayed identification of production deviations, and inefficient root-cause analysis, ultimately hampering cost-efficient manufacturing.
Solution
Bytefabrik offers an integrated on-premise IIoT platform that connects machines, sensors, and shopfloor systems via standard industrial protocols, harmonizing signals into a consistent data model. The platform provides a common foundation for connectivity, analytics, and KPIs, enabling teams to investigate losses, downtime, and quality issues with full process context and parameter history. AI-powered features, including AI Notebooks, AI Pipelines, and a Manufacturing Analytics Copilot, allow users to query live and historical data in natural language, generate executable analysis logic, and receive automated anomaly detection and explanations. This approach reduces integration overhead and empowers production teams to make data-driven decisions without deep IT expertise.
Target Audience
Primary customers are industrial manufacturing companies, including both SMEs seeking a quick-entry MDE and analytics solution and large enterprises requiring governance, security, and distributed deployment across multiple sites.
Features
- Open connectivity for Siemens S7, OPC UA, MQTT, Modbus, REST, and Beckhoff protocols, with reusable connector templates for machine, line, and site rollouts
- Edge component for data acquisition and preprocessing within the OT network, supporting segmented or low-connectivity environments
- Semantic metadata model for data streams, measurements, units, and data types, enabling consistent structuring and retrieval of industrial data
- AI Notebooks that translate natural-language queries into readable, verifiable code for historical data analysis, with results as tables, visualizations, and shareable outputs
- AI Pipelines that convert natural-language requirements into executable logic for live data monitoring, alarms, triggers, and operational responses
- Manufacturing Analytics Copilot that generates AI-driven data stories, detects anomalies, and explains root causes in natural language
- Manufacturing Insights module for analyzing availability, quality, and performance, including detailed drill-down from OEE to process parameters, product traceability, and error pattern analysis
- On-premise, cloud, or hybrid deployment with role-based access control, governance, and an open-source foundation for extensibility