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Predictive maintenance and Artificial Intelligence

Detecting possible process drifts in a preventive way, it makes more efficient the implementation of corrective measures in a predictive maintenance perspective, thus leading to higher quality standards of products and services over time. It enables predictive maintenance processes, reducing unplanned downtime and scheduling early preventive stops.

Data, analysis, processes: our solutions

THE PROBLEM
TOO MUCH DATA TO EXPLORE:
It's hard to spot good subsets of data and to perform analysis on them.
THE SOLUTION
FOCUS ON PROCESS DEVIATIONS:
identify anomalies allowing the client to prioritize the aspects capable of generating business impact. detectiv.ai comes with an intuitive and customizable alert system that will make warnings more informative, to let you act promptly.
THE PROBLEM
DIFFICULT TO SCALE THE ANALYSIS:
manual analysis, dashboards and traditional alerts are useful, but become insufficient as more data becomes available.
THE SOLUTION
AUTOMATIC ANALYSIS AND CONFIGURATION:
minimizing system setup and increasing the automation level of analysis allows you to scale to large amounts of data, decreasing the possibility of errors and improving the analysis effectiveness.
THE PROBLEM
LACK OF RELEVANT DATA:
anomalies are often rare events. For this reason the data useful to train a model are often very few compared to large amounts of data collected.
THE SOLUTION
TRAIN THE MODEL ON “NORMAL” DATA:
identifying process deviations from "normal" (non-anomalous) data reduces the amount of data needed for model training.
THE PROBLEM
LONG TIME-TO-VALUE:
data analytics and artificial intelligence are new topics for many companies. PoCs are often characterized by long-time-to-value, high costs, and significant difficulties in getting into production.
THE SOLUTION
EARLY DEPLOYMENT OF AI IN PRODUCTION:
with a low initial investment, detectiv.ai immediately begins to generate business value, increasing its performance over time and allowing you to easily scale to more complex problems and to explore different use cases. It's ready for deployment on a wide range of on prem, cloud and edge devices.

detectiv.ai makes possible to:

DETECT ANOMALIES

Through machine learning techniques, detectiv.ai identifies anomalies overlooked by traditional threshold systems, considering the interaction between all input variables. By training models only using "normal" (non-anomalous) data, detectiv.ai reduces the time spent collecting data and starts generating business value right away. In addition, it is possible to select an existing model or create one on specific data, minimizing the need for system configuration.

IMPROVE PERFORMANCE OVER TIME

detectiv.ai enables model continuous training as new data becomes available to improve performance over time.

CUSTOMIZE DASHBOARDS
AND ALERTS

Detectiv.ai displays the outliers through customized monitoring dashboards and configurable alerts, in order to have full observability on their evolution over time and the gravity of potential process drift.