We are changing the future of traceability and transparency in the manufacturing industry where innovation meets efficiency with A.I.

Discover how our cutting-edge solutions revolutionize the way you manage and track your production processes.

Alat is building a revolutionary AI-powered Tracking Solutions, which not only enables manufacturers to extend the traceability of parts and products throughout the entire production chain as a reliable and scalable alternative to traditional methods but additionally provides capabilities to optimize production by identifying cycle times, piece counts and flow irregularities in real-time.

Problems We Are Solving


Traceability is one of the most critical strategies for bringing true transparency to the manufacturing environment and maximizes the benefits of Industry 4.0 solutions by linking datasets across the production stages.

Common issues encountered in traditional track and trace solutions include the marking of QR/barcodes for detecting assigned serial numbers at various stages. This approach presents several drawbacks:

  • In the initial stages of manufacturing, it becomes impractical to mark a code directly on the raw part since it is slated for reworking in subsequent stages.
  • During certain manufacturing phases, the part or product might be subjected to high temperatures or machining processes (e.g., milling), necessitating the application of markings after these stages.
  • Some materials used in production are not conducive to printing, posing a challenge for implementing traditional coding methods.
  • Products such as unpacked food or those sensitive to printing face limitations in adopting traditional track-and-trace solutions.
  • In instances where there is insufficient space or challenging access, printing or engraving codes directly onto the part or product becomes problematic.


Consequently, key stakeholders such as managers, supervisors, and workers often face the challenge of reporting dependable key metrics and statistics while also striving for a unified information structure to facilitate comparable data analysis. These challenges highlight the vulnerability of traditional automation systems to disruptions, emphasizing the importance of system robustness and the need for mitigation strategies to maintain data integrity.

Manufacturers employing traditional automation systems for data acquisition encounter several common situations that lead to the provision of low-quality production data and/or data shortages. These scenarios include:

  • Any breakdown in a single component within the OT/IT architecture, such as communication issues. The quality of data is significantly reliant on the overall health of the system
  • Manual intervention by workers, involving the removal or addition of parts or products at any intermediate stage
  • Overburdening the automation system with the collection and transfer of a substantial amount of production data which is not pertinent to process control
  • Inaccessibility of data due to data silos, inadequate integrations, and outdated systems, among others

Flow Monitoring

At present, there exists a bottleneck in obtaining immediate and thorough visibility into different facets of the manufacturing process. Some of these include:

  • Identifying human interventions in process, such a manual unloading, which leads to the loss of data
  • Detecting flow irregularities, such as production jams, or anomalies, such as missing parts
  • Measuring production flow densities and spacings between parts

Our Solutions

Traceability 5.0

AI Computer Vision-based solution to visually track the propagation of workpiece/part and its associated serial number virtually across the production line until code printers.



Food and Beverage



About Us

Alat is driven with passion by the motivation to deliver to manufacturers AI-based solutions, which offer opportunities for production traceability and optimization.

It has been our a long-term pursuit to find a simpler and cost effective alternative to the production data acquisition problem in the manufacturing industry for parts untraceable with conventional methods.

We want to help the sustainable growth of manufacturers while being part of reducing carbon footprint.

Innovation is a key ingredient, we want to harness the advancements and our expertise in AI combined with our industrial expertise, in creating something new, disrupt the market, and solve a crucial problem in Industry 4.0.

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