coligo.ai

What It Is

COLIGO is an industrial Edge AIoT solution from BE.services GmbH, aimed at machine builders, automation engineers, and SPS/PLC programmers. It consists of SYNA EdgeBox industrial hardware, EdgeStack containerized firmware and applications, a configuration and monitoring app, and Cockpit for device, fleet, user, and patch management. Its positioning is clear: enabling industrial field teams to deploy AI analytics directly at the machine and production-line edge without needing AI specialists or a data science team.

Core Capabilities and Integrations

Based on the main materials, COLIGO is not focused on general-purpose generative AI, but on industrial edge analytics. The workflow includes collecting data from data sources via OPC UA, selecting and configuring AI models without code, training and running inference at the edge, and then distributing results via OPC UA, API, or MQTT. Its AI capabilities cover anomaly detection, time-series forecasting, Streaming ML, predictive maintenance, and, in the L tier, machine vision, multi-camera support, and on-device image processing. It emphasizes that cloud usage is not mandatory, making it suitable for industrial environments with requirements around latency, keeping data on-site, and operational stability.

Pricing and Plans

COLIGO uses a one-time hardware purchase plus an annual subscription. SYNA EdgeBox costs €1,200 per unit for 1-10 units, with volume pricing dropping to €600 per unit for 500+ units. Software is subscribed per device per year: S Standard, for monitoring, connectivity, dashboards, and basic predictive maintenance, costs €249 for 1-10 devices; M Advanced Analytics adds anomaly detection and forecasting, and costs €490 for 1-10 devices; L Machine Vision adds full machine vision capabilities, and costs €990 for 1-10 devices. The pricing table is fairly transparent, but no free trial information was found.

Pros and Cons

Its strengths include a complete industrial stack, no-code configuration, local training and inference, and support for industrial and IoT interfaces such as OPC UA, MQTT, and REST/API; it should fit well with traditional PLC projects. The limitations are that dedicated hardware must be purchased, and more advanced AI functions require higher subscription tiers. The materials do not disclose model accuracy, industry validation metrics, SLA details, Chinese-language support, or payment methods. Real-world results will also depend heavily on on-site data quality, sensor/camera placement, and integration experience.

Who It Is For and Access from China

COLIGO is better suited to European manufacturers, equipment vendors, automation integrators, and factory teams that want to quickly implement anomaly detection, predictive maintenance, or visual quality inspection. The materials do not provide information on access from China, so its status is unknown. Procurement may also involve cross-border payments, invoicing, hardware delivery, and local service response. For deployments in mainland China, it may be worth evaluating Siemens Industrial Edge, Azure IoT Edge, AWS IoT Greengrass, as well as domestic industrial edge computing and industrial AI solutions as alternatives.