Through our platform, collected data can be used to visualize real-time machine condition and performance and, with relevant data history, feed powerful predictive analytics, forecasting production bottlenecks and projecting preventive maintenance measures. By leveraging machine data talpasolutions' compelling and easy dashboards and powerful algorithms enable quick, targeted and intelligent actions that increase productivity and enterprise efficiency while enhancing safety.
Discover Patterns in Exceptions
IIoT provides three key benefits: industrial machines operate with more uptime; they provide more user feedback to increase efficiency and productivity, and they improve safety through process transparency. All of these are product of a successful transformation of data into tangible business value that ultimately creates higher margins for everyone involved.

It is time to collect and utilize valuable machine data. Instead of losing time by tediously gathering and verifying dispersed information and suffering from costly technical downtimes talpasolutions’ platform service offers powerful data management, predictive analytics and a platform for collaboration of heavy machine owners, users and manufacturers. Enabling fast and actionable insights based on machine data, our’ data expertise and domain know-how and your detailed process and asset expertise represents our deep conviction for joint success – an approach we call collaborative transformation.

The adoption of digital technologies is most efficient when it involves and integrates different users and activities/work flows throughout the value chain. By collecting and using data individually, different users create silos/islands of information. This leads to inconsistent and redundant data throughout the value chain. Organizations can make the most of big data by collaborating across the value chain. Big data of large machinery and facilities in the heavy industry is heterogeneous, as it comes from different systems, data sources, formats, standards, processes and tools. Integrating, normalizing and managing these data from the disparate sources is a crucial step to enable smart industry applications.
Machine data is omnipresent in daily work. A significantly increasing number of large equipment and facilities in the heavy industry are equipped with sensors and internal computing units which enable data-based controlling and monitoring. Such industries include mining, steelmaking, chemical and capital-intensive manufacturing industries.

However, for end users of such heavy machinery as well as their supplying OEM using large amounts of paper-based information or isolated excel files is rather the rule than the exception. Instead of voice over IP, 4G, email and messenger services the supervisors e.g. in many underground mines provide tasks to the operator by driving to the different workplaces or by two-way radio. Each morning it’s a challenge to find a mobile asset in a mine, as the last shift parked it somewhere and no localization data is available. Machines are used even though they urgently require planned or condition-based maintenance as a lack of transparency and diagnostics.

The problem of such capital-intensive industries is that they are using outdated rules of the game. Far too often a common approach is still investing in new machines and processes in an effort to improve end products. That’s a laudable aim, but it’s not enough. Especially at a time when volatile resource prices, shortages of skilled labor and increased supply chain and regulatory risks are accentuating an already volatile market. The answer for these heavy industries is the Industrial Internet of Things.

IIoT is embedding intelligence in industrial machines allowing them to be more efficient, self-detecting, safer, and connected, relieving mundane tasks from operators enabling them to focus on their remits and providing engineers and service personnel with hot data of machines’ condition and performance.
Transform data into business value
Protected by industry-leading end-to-end security
Partners access comprehensive dashboards with actionable insights that save time & money
The data is then normalized to ensure superior visualizations & cutting edge predictive analytics
talpasolutions' platform securely integrates data from diverse sources of any format
The process of data normalization


Boost your productivity


Enable stakeholders to understand and react to critical information by visualising high volume & velocity of data of heavy equipment.

Facilitate executives to monitor performance, by highlighting broad trends & patterns.

Synthesize data & metrics into high-level dashboards.

Make your data available to other community applications and services.


Mitigate unplanned downtimes, increase asset utilization and profitability by predicting failures & breakage for high value machines.

Prevent operational disruptions before they occur through event & condition prediction.

Identify root causes of machine failures through data science models & machine learning.

Translate insights into action by suggesting specific tasks & activities that minimize downtime and enhance efficiency.

Start acting instead of reacting



Innovative, sustainable and secure way to manage and structure the various varieties, volumes, and velocities of data generated by diverse machines and sources.

Contextualize multiple data sources to produce more accurate insights with an elastic software architecture in terms of storage, computing capacity and concurrent workload.

Specific end-user needs, required analytics capabilities and advanced algorithms provide a convenient digital image and overview of machines, sensors and measurement devices of assets & processes on any device in any place.

Integrate & store all relevant data