Unexpected failures and lack of stock of spare parts for industrial equipment decrease productivity and increase operational costs, due to the high costs and time required to repair or replace equipment. One of the causes lies in maintenance strategies, among which the most com- monly used are corrective, preventive, and condition-ba- sed offline maintenance. These strategies are not able to adequately foresee the occurrence of failures and there- fore lead to over-maintenance and overstock of spare parts.


JakSol delivers a comprehensive predictive maintenance and fault diagnosis solution for rotating equipment, which consists of a Virtual Maintenance Advisor as well as proprietary vibration and temperature sensors. Thanks to its machine learning algorithms and models, the Virtual Maintenance Advisor can predict the time and mode of equipment failure automatically and it is agnostic to the type and brand of equipment. The wireless sensors are easy to install and the algorithms do not require historical data from the equipment, allowing for simple implementation.


The predictive maintenance system is under develop- ment at TRL 8, which has been validated through pilots in different agribusiness production lines with positive results. Automatic diagnostic functionalities are at TRL 5.


The company has an Intellectual Property strategy based on trade secrets and a registered trademark.

  • Quick implementation (plug-and-play).

  • It does not require a vibration analyst for its use.

  • System agnostic to the model and brand of the equipment.

  • Automatic fault diagnosis capabilities.

Market size: USD 4.2 billion (2021)

Segment: Predictive Maintenance

Expected market size: USD 15.9 billion (2026)


JakSol is marketed as a SaaS predictive maintenance service implemented with its own hardware, mainly oriented to medium and large industries.