Transform your predictive maintenance and quality processes by generating automated AI models from your IoT data. Adapting seamlessly to production conditions, Time Reactor prevents unexpected downtime, reduces energy waste, and maximizes operational efficiency with its "Artificial Data Scientist" capabilities.

Time Reactor is a next-generation manufacturing analytics platform that processes IoT data flowing from production lines (machines, processes, supply chain) to automatically develop its own predictive models. It aims for non-stop factory operations, detects risks early, and empowers you to manage complex data processes with the ease of a teammate.

In the industrial world, human speed cannot keep up with the velocity of data. Time Reactor solves the critical problems arising from this speed gap:

  • Inefficient Response Cycle: Only being able to intervene after events occur because data cannot be processed instantly.
  • Unexpected Downtime: Approximately 11% of turnover is lost due to unplanned downtime.
  • Sustainability Challenge: Increased energy and raw material waste resulting from stoppages.
  • Human-Centric Errors: Decisions based on instincts or static threshold values instead of live data.

Industries & Roles

  • Automotive Industry: Mass production lines facing high quality standards and cost pressures.
  • Heavy Industry: Facilities with high downtime costs where Press and CNC machines are used intensively.
  • Manufacturing Engineers: Field professionals who want to generate value from data without needing to write code.
  • Smart Factories: Businesses aiming to realize Industry 4.0 and 5.0 transformations without drowning in a "hardware stack."

Features

  • Automated Model Generation (AutoML)

    The system develops and updates its own predictive models without the need for a data scientist.

  • Agentic AI & LLM

    Analyze data as if you are having a conversation. Leave exploratory data analysis and result interpretation to autonomous agents.

  • Adaptive AI

    Your model doesn't become obsolete even if your factory changes. Models remain resilient to shifting production conditions and continue to learn constantly.

  • Real-Time Risk Detection

    Predicts potential malfunctions in advance, offering the opportunity to intervene "before the failure occurs."

Related Frequently Asked Questions

Can I use TimeReactor without prior machine learning experience?

Yes, TimeReactor is designed for users without machine learning experience. It offers easy-to-use tools and automated processes to help you get started quickly.

How are you different from standard predictive maintenance or machine health solutions?

Standard solutions often require manual modeling or static rules. Time Reactor automates model generation using Agentic AI technology. It offers an "autonomous" structure that your manufacturing engineers can easily use without needing an AI expert.

Which sectors is it suitable for?

While our primary focus is the automotive sector, it is suitable for all smart factory scenarios—such as heavy industry, textile, and white goods—where machines like CNCs and Presses generate data.

What types of data can TimeReactor process?

TimeReactor handles time series data like sales, sensor readings, and electronic signals. The data can be univariate (single variable) or multivariate (multiple variables), and it can be read as structured tabular data from spreadsheets or databases (relational databases or time-series databases).

How does the system learn and improve?

The system is fueled by a dual feedback loop: ● User Feedback: Approvals given by operators and engineers regarding decisions. ● Data-Based Feedback: Automated verification of whether a predicted failure actually occurred. This ensures models remain constantly up-to-date.