WATR

IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. IoT data comes from devices that often record fairly noisy processes (such as temperature, motion, or sound). The data from these devices can frequently have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of additional, third party data inputs. For example, to help farmers determine when to water their crops, vineyard irrigation systems often enrich moisture sensor data with rainfall data from the vineyard, allowing for more efficient water usage while maximizing harvest yield. AWS IoT Analytics automates each of the difficult steps that are required to analyze data from IoT devices. AWS IoT Analytics is a fully managed and pay-as-you-go service that scales automatically.

Sennos offers an AI-driven fermentation sensing, analytics, and optimization platform that combines precision in-tank hardware, cloud-based intelligence, and intuitive monitoring to give producers real-time visibility and predictive control over fermentation and fluidic processes. Sennos’s modular SennosM3 sensor modules continuously capture high-fidelity data, such as temperature, pH, pressure, density, dissolved oxygen, and other critical parameters, from fermentation tanks and send it to the cloud. There, the SennosIQ analytics engine applies AI to convert raw data into actionable, predictive insights that help users spot issues early, benchmark batches against historical performance, optimize outcomes, reduce waste, and improve consistency across production. The Sennoslink interface ties everything together, delivering real-time dashboards, alerts, and intuitive control from desktop or mobile devices so operators can monitor and manage operations from anywhere with clarity.