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Sensor AI has a role not only in industry, but also in sectors such as medicine and consumer electronics

Corporate artificial intelligence and robotics are no longer just futuristic concepts but are becoming an integral part of everyday business operations. They enable companies to improve efficiency, productivity, and responsiveness to change. They also help with product innovation. One of the key aspects of this integration is the use of sensor AI, which allows for data collection and analysis using a variety of sensors and devices.

Let’s take a look at some examples of how sensory AI can transform various industries and innovate businesses. The following examples illustrate practices already in use today:

• Industrial automation: In industrial automation, sensor AI is used to monitor and control manufacturing processes. Sensors can monitor essential parameters such as temperature, pressure, or humidity, but also detect microscopic changes in the environment that could signal potential issues. For example, sensors detecting changes in air pressure can warn of impending equipment failure, allowing maintenance to be carried out before the problem becomes serious.

• Medicine: Sensors enable the monitoring of heart rate, blood pressure or glucose levels. This data can be analysed by artificial intelligence, for example to diagnose and monitor health conditions or to predict the future course of a disease or a patient’s response to treatment. Sensory AI detects patterns of changes in blood pressure that may predict when the next hypertensive crisis will occur and warn the doctor or patient well in advance.

• Autonomous vehicles: Sensors are crucial for collecting data about the surrounding environment. In addition to traditional sensors such as lidar, radar and cameras, modern vehicles often use other advanced sensors such as ultrasonic sensors to detect obstacles in the vicinity of the vehicle or sensors to measure road quality. This information is essential for the proper functioning of autonomous systems, which must be able to quickly and accurately respond to various situations on the road to ensure safe driving.

• Smart cities: Sensor AI in smart cities is used to monitor traffic, air quality, noise levels, and other factors affecting the environment. Modern sensors measure essential parameters and identify specific pollution or problems in public infrastructure. For example, a sensor network in a city can detect gas leaks in the distribution network and automatically alert the relevant authorities, enabling rapid action.

• Wearables: Sensors in electronics such as smart watches or fitness bracelets collect data on movement, heart rate and other physiological parameters. This information is not only used for personal monitoring and improving the health of users but can also be shared in the form of anonymised data with research institutions or public health organisations to analyse and predict epidemics or to track population health trends.

Why don’t Czech companies use AI?

Despite all these potential benefits, many Czech companies are still hesitant to implement AI into their processes. There are several reasons for that.

Firstly, there is a shortage of qualified experts in the Czech Republic, who would be able to design and implement AI systems into corporate infrastructure.

According to RSM, a local IT consulting firm, 48% of companies have the technical conditions for rapid implementation of AI, but the development is hindered by both managers and legislation. According to the analysis, specific challenges such as managers’ low willingness to bear the risks associated with pioneering phases of AI implementation, including legislative and security aspects (e.g., personal data protection), are obstacles. It may be difficult to agree across the company on how the corporate AI should work. Moreover, significant revisions of existing legislation and updates to the national AI strategy are needed, a process that is still in its early stages.

Some companies don’t have a clear idea on how to use AI to improve their processes or innovate products and services. This lack of awareness may lead to a lack of motivation for investment in AI technologies.

However, organisations should not resist this trend. In countries such as Japan and the US, AI is already widely used, including in autonomous taxis. Once Czech companies overcome their concerns and embrace AI as an essential part of their operations, they can enjoy higher efficiency, innovation, and a competitive advantage. There is hardly any company that cannot benefit from what AI has to offer, be it from small things such as data processing and analysis, to process automation, automated car control, to fully autonomous factory or shop floor operation.

The age of semantic automation

The combination of Robotic Process Automation (RPA) and Artificial Intelligence (AI) creates a powerful symbiosis that can elevate business productivity and efficiency to a new level. Semantic automation, based on generative artificial intelligence, is a driving technology with the potential to fundamentally change the way companies operate.

In a time when digital transformation is a necessity rather than just a trend, RPA is becoming a major player. With its ability to automate mundane, repetitive tasks, RPA significantly enhances employee productivity. Together with AI, they form a synergistic duo, combining automation with the creativity of the human mind.

According to IDC, automation in companies reduces operating costs by 13.5% and saves an average of 1.9 hours of work per week (source: Worldwide Automation Spending Guide 2022 by IDC) per employee. These figures highlight the transformational potential of RPA and AI in increasing productivity and reducing costs.

RPA and generative AI – the combo for perfect automation

Generative artificial intelligence, as a subset of AI, focuses on the creation of content or data rather than just processing it. It uses machine learning techniques such as neural networks and deep learning to create new content in various forms. “Generative AI models learn from existing data and use this knowledge to produce original, creative and contextually relevant output,” explains Viktória Lukáčová Bracjunová, Head of Robotics and Automation at Soitron.

RPA excels in repetitive tasks, follows rules and procedures, doesn’t make mistakes and doesn’t need breaks. It dominates in structured processes, minimizing deviations. It is a key technology component for companies to reduce costs, reduce errors and speed up routine tasks.

Using semantic automation in a dynamic environment

In a dynamic automation environment, the combination of RPA and generative AI creates a powerful synergy that goes beyond the capabilities of either technology alone. “RPA successfully handles routine tasks, while generative AI is strong at processing complex, unstructured data and solving creative challenges. RPA ensures process consistency and minimises errors, while generative AI analyses data and provides deeper insights, improving the quality of strategic decisions,” says Viktória Lukáčová Bracjunová.

In the field of AI and natural language processing, semantics play a crucial role. It provides the foundation for creating advanced generative artificial intelligence systems that are better able to understand and interact with human language, which is crucial for the success of many AI applications.

Implementable in any company

RPA’s integration with existing systems and applications makes this technology an ideal choice for automating tasks within existing workflows. Next-generation automation can work with a variety of data types and formats, ensuring compatibility with a wide range of processes. Generative AI integration enhances customer experience through personalized interactions, understanding natural language and solving complex queries with empathy.

Where semantic automation can help

Advanced Natural Language Processing (NLP) capabilities – it can understand and respond to the customer’s natural language, which is key to automating customer care, order processing and maintaining customer relationships.
Machine Learning (ML) – allows robots to learn from data and improve their performance over time, which is crucial for tasks requiring adaptivity or decision making.
Optical Character Recognition (OCR) – enables the reading of information from unstructured digitized documents such as PDFs and images.

Meeting the challenges of the modern market

In a rapidly evolving market environment, the combination of RPA and generative AI delivers precision automation, as well as creative innovation, providing a competitive advantage when deployed. Ignoring this technological symbiosis means missing an opportunity. “Now is the right time to let RPA and generative AI technologies collaborate and achieve improved results,” concludes Viktória Lukáčová Bracjunová.

Generational leap! Deploy Cisco Catalyst Center for campus network management

The corporate network infrastructure has undergone fundamental changes in recent years. Campus network management needs to respond to the way IT is currently consumed. Cloud environment, IoT and hybrid working create extreme demands on network performance and security. Cisco Catalyst Center (CCC) is a centralized virtual platform designed to simplify and streamline network management while significantly improving security posture.

Cisco Catalyst Center offers centralized, intuitive network management that makes it easy and fast to design, provision, and apply policies across the entire network environment. The Cisco Catalyst Center graphical user interface provides complete network visibility and uses network information to optimize network performance and deliver the best user and application experience. CCC can be deployed as a hardware appliance, but most customers appreciate the virtual platform option, which is available for the AWS cloud service and now also for VMware on-premise platform.

Firsthand experience

The Soitron team, an implementation Gold Partner of Cisco, is one of the top specialists in deploying Cisco Catalyst Center in corporate environments. Soitron was one of about 60 selected companies worldwide involved in testing the very first pre-production version of the tool (then known as Cisco DNA Center). “We used the platform to manage our own network in the Czech Republic, Slovakia and Bulgaria. We tested the tool for any issues with installation, resources, certificates, and security. Our actual telemetry data were made available to Cisco and used for further development,” said Marianna Richtáriková, Network Business Unit Manager at Soitron.

The scorecard for Catalyst Center

Having first hand practical experience with the tool, Soitron experts were able to identify the areas and situations in which the Cisco Catalyst platform has the highest added value.

Network Design: If you are building a new network from scratch, CCC makes it very easy to design connections in a hierarchical way, adding and defining additional elements in a single tool. Of course, it is also possible to gradually convert the legacy network infrastructure to a modern software-defined network infrastructure.

Centralization: Cisco Catalyst Center enables the centralized management of the entire network, simplifying device configuration and monitoring from a single dashboard.

Automation: CCC provides advanced tools for automating network operations, allowing for fast and consistent network deployment, reducing error rates, and saving time. Any configuration changes can be applied at once across an entire group of devices, minimizing the time a network administrator needs to spend on tedious manual tasks.

Analysis and Diagnostics: The tool provides extensive monitoring and analysis capabilities for network traffic and selected application services. It helps identify problems and respond quickly to outages or security incidents. CCC telemetry provides real-time as well as historical data, making diagnostics much easier.

Security: Cisco Catalyst Center integrates security features and makes it possible to monitor the network’s security status. It helps identify threats and enhance network protection. Automated procedures allow security policy to be prepared in advance and then applied from a single point to any device managed by CCC. For end-users, security policies are applied upon user login (authentication) to the network.

Integration: CCC is designed to be compatible with other Cisco products and technologies, allowing the functionality to be scaled as necessary. It can be connected to platforms such as ThousandEyes for network, internet, and cloud monitoring. An interesting integration is the connection of Apple, Samsung or Intel devices, enabling the monitoring of communication from the device end-user perspective. As for application services, CCC can evaluate and interpret the status of application services such as Webex, MS Teams, and others. An integral part of the solution is also the support for location-based services through integration with DNA Spaces.

Choosing Cisco Catalyst Center makes it possible to create connections not previously possible and transform slow manual processes into automated workflows.

A dangerous development: the rise of zero-click exploits is also becoming a threat to ordinary users

Cyber attacks through zero-click exploits are nothing new. What is a new trend, however, is that even ordinary users are becoming targeted.

A zero-click exploit is the exploitation of a security flaw in software that allows an attacker to remotely attack a device without any user interaction. This technique can be used for purposes such as espionage, device control, malware distribution, and even extortion. Overall, this is a dangerous technique that can have a significant impact on the security and privacy of users. The bad news is that users have very limited defences against such attacks.

“The fact that the number of groups specializing in this kind of attack is growing is very worrying. Attackers have adopted techniques previously used only by high-profile actors, such as state or government organizations and secret services. Cybercriminals are using the Exploit as a Service model (i.e. selling the exploit for a single payment) to also attack the private sector and ordinary users, rather than just high-profile or politically exposed individuals, government organizations, and other targets with valuable information,” says Petr Kocmich, the Global Cyber Security Delivery Manager at Soitron. That is why he believes it is important for businesses and users to follow models of best practice and procedures recommended in cybersecurity and to make sure they properly protect their devices from potential attacks.

The impact of vulnerabilities

One of the most well-known and well-described zero-click exploits was the ENDOFDAYS spyware, which was used to compromise iPhones, specifically iCloud calendar invitations.

“ENDOFDAYS is an exemplary case where an attacker is able to take control of an entire device without any interaction with the user. This includes the exfiltration of call recordings through access to the microphone and controlling access to the GPS location of the device. The attacker also gains access to both the front and back cameras and the ability to search files stored in the device. They can also disguise the spyware to avoid detection. The spyware enters the device in a mundane way – by sending a specifically crafted invitation to the iCloud calendar with older timestamps (an invitation that has already taken place in the past),” says Kocmich.

Such an invitation is automatically added to the user’s calendar without any notification or prompting, allowing the ENDOFDAYS exploit to run with no user interaction and making the attack undetectable to the target. The vulnerability has been patched in new versions of the system, but the flaw affected all versions of iOS from 1.4 to 14.4.2 and, according to research, was exploited primarily in 2021.

Despite this awareness, these exploits still exist, and very advanced applications evading detection in the system are written for specific vulnerabilities. “This clearly shows why it is necessary to update your device regularly. A zero-click exploit can be present on a device for a long period of time without the user being aware of it. That is why it is necessary to respect the principles of cybersecurity and ensure that the software is always up to date and that additional security measures are in place,” warns Kocmich.

Others are also being targeted

For Apple, this is not the first or last zero-click exploit that has been discovered. In 2020, a vulnerability was discovered in the iMessage app that could be exploited by attackers to remotely execute a malicious code on users’ devices without any need to click a link or open an attachment. The Android operating system and individual mobile apps are also far from safe from these flaws.

“Some exploitable vulnerabilities in the current versions of operating systems and applications are not even known yet, even though they may already have been exploited. Until these vulnerabilities are discovered, they can first be exploited for espionage and ‘higher interest’ purposes before being monetized by selling the Exploit as a Service to customers on the dark web,” adds Kocmich. It turns out that even ordinary users may be vulnerable to zero-click exploits.

The sophistication of the attackers is increasing

Zero-click attacks are usually based on vulnerabilities in software, including operating systems, applications, and services. The question is whether these are just unintended bugs, or whether they are deliberate.

“The faster new software is developed, the higher the need will be to manage and secure the code and the entire software development cycle. We automate testing, include additional security tests in the early stages of development (Shift-Left) in the CI-CD pipeline, perform static and dynamic code reviews, use artificial intelligence to find bugs in the code, and subject the final result to both automated and manual penetration testing; however, it would be foolish to assume that all types of vulnerabilities are caused by common errors in the code. The question is whether some vulnerabilities are actually deliberate backdoors, serving specific purposes,” concludes Kocmich.

Companies need to have ChatGPT policies: what should they include?

Recently, applications using Large Language Models (LLM) such as OpenAI’s ChatGPT, Microsoft’s Bing AI, and Google’s Bard have been growing in popularity. These tools are fast, easy to use, and available to anyone. It is not surprising that employees of large and small companies have started to use them. There is nothing wrong with that, but one important thing should not be omitted.

ChatGPT and similar machine learning-based applications are gaining traction in corporate environments. They are used for a variety of purposes:

content creation – they can draft a high-quality presentation and write a surprisingly good speech, blog post, email, or comment.

creative idea generation – within seconds, they can generate a list of possible questions or answers on a given topic and help you come up with a title for an article, presentation, or business plan.

checking and revising texts – they correct grammatical errors and can shorten or expand information according to the user’s wishes, change the style to a more formal or colloquial one, and generally improve the quality of a text.

information search – like Google or Wikipedia, they are used to search for information.

programming – they become a common tool for coding and code reviewing.

“LLM-based systems are already contributing to improving corporate content, helping employees with various tasks, and even participating in decision-making processes,” says Martin Lohnert, a cybersecurity specialist at Soitron; however, with the adoption of these disruptive technologies come certain risks that users and organizations are often unaware of because of the initial excitement.

The risks of using ChatGPT in a corporate environment

The immediate benefits of LLM-based tools are so great that curiosity and excitement often outweigh caution. Nonetheless, there are several risks associated with the use of ChatGPT in companies:

Protection of personal and sensitive data

When using ChatGPT in a corporate environment, personal or confidential data may be inadvertently shared. Users often enter this data into the tool without knowing that it is shared with a third party. A case has already been reported where a bug in ChatGPT allowed users to see other users’ data, such as chat history.

Intellectual property

LLM training is based on the processing of large amounts of diverse data of unknown origin, which may include copyrighted and proprietary material. Using any outputs based on this data may lead to ownership and licensing disputes between the company and the owners of the content that was used to train ChatGPT.

Malicious or vulnerable code

Computer code generated by artificial intelligence (AI) may have vulnerabilities or malicious components, which can lead to subsequent use and the propagation of such vulnerabilities in corporate systems.

Incorrect and inaccurate outputs

AI tools of the current generation sometimes provide inaccurate or completely incorrect information. There have been cases where the outputs had distorted, discriminatory, or illegal content.

Ethical and reputational risks

Using and sharing incorrect ChatGPT outputs in corporate communication can lead to ethical and reputational risks for the company.

The need for a ChatGPT policy

Given these risks, it is essential to define the rules on how employees can (and should) use ChatGPT when doing their job. “A corporate policy should serve as a compass to guide the company and its employees through the maze of AI systems ethically, responsibly, and in compliance with laws and regulations,” says Lohnert.

When defining a corporate policy, it is first necessary to determine what technologies it should cover. Should the policy apply specifically to ChatGPT or to generative AI tools in general? Does it also cover third-party tools that may incorporate AI elements or even the development of similar solutions?

What a ChatGPT policy should include

A ChatGPT policy should begin with a commitment to privacy and security when working with similar tools, and it should set boundaries by clearly defining acceptable and unacceptable uses of the technology.

It should define uses that are permitted in the organization without restriction. “This can include various types of marketing activities, such as reviewing materials for public use and generating ideas or initial material for further development,” says Lohnert. In doing so, it is important to carefully consider the legal aspects of possible intellectual property infringement and be cautious about the known pitfalls of inaccuracy and misinformation.

The second group of rules which the policy should include involve scenarios where use is allowed with more authorization. Typically, these are cases where the output from ChatGPT needs to be assessed by an expert before it can be used (e.g. computer code).

The third category involves scenarios where its use is forbidden. This should include all other uses, especially those where users enter anything containing sensitive data (e.g. trade secrets, personal data, technical information, and custom code) into ChatGPT.

A good servant but a bad master

An LLM use policy should be “tailored” to each company after thoroughly identifying any associated potential risks, threats, and impacts. “This will allow your company to quickly harness the potential of the new AI-based tools, while formulating a strategy to integrate them into the existing corporate environment,” concludes Lohnert.

We can deploy various types of robots in your company

With Robotic Process Automation (RPA), i.e. software robots, we can streamline and speed up many business processes while reducing the error rate to a minimum. When deploying a specific type of a robot, it is essential to clearly describe the processes in which the robot is to be involved and to define the exact criteria it should follow. The following examples will show you what types of robots are available and what kind of tasks they can handle either with or without human assistance.

A robot: your trusted colleague

One of the simpler software robots is an On-Demand Robot that works only when you need it. Let’s take the example of a contact centre. If a customer calls the contact centre with a request to cancel part of a purchase order, you as the operator then type in the purchase order number; this initiates the robot, which will find the necessary information about the customer and the ordered goods across various systems. The inquiry takes a few seconds. You then verify the information with the customer and modify the purchase order as requested. A more sophisticated solution is an Attended Robot working in tandem with you as the employee. Once the robot is running, you do not wait for the result and you can fully focus on the customer and other activities. The robot works in the background and notifies you when everything is completed. These types of robots function as virtual assistants, helping you when you need them, and are especially suitable for back-office tasks at Finance, HR, IT, and many other departments.

More work for the robot means less for the employee

By combining the two previous types of robots, we get a Hybrid Robot. This is particularly useful if the work takes a little longer to complete. An operator or other employee at the contact centre provides input data to the robot, which will check the original purchase order in all the necessary systems. This part is relatively fast, and the customer can stay on the line and be immediately informed that their request is ready to be processed. As the operator needs to continue using this robot, the collected data is sent to another robot that works independently. After working hours, or at a specifically chosen time, the second robot launches the completion process of things like cancelling all collected orders. When finished, it sends a notification about the job completion.

The robot can also work Partially Unattended, and hence you do not have to wait for the outcome. For example, if a company needs to refund a customer, a Finance Department staff member enters this request into a file (such as an Excel spreadsheet). At a specific time, the robot automatically activates itself, reads the file, checks the data, and then processes all the refunds. Similarly, this type of robot can also be utilised by IT departments for the onboarding of new employees, or for another process where you can enter specific input data and do not need to immediately work with the outcome of the robot’s work; in this case, the IT specialist only enters the necessary data, and the robot orders new devices for the new employee or generates access to the company’s systems. If a new hire is replacing a leaving employee, the robot revokes access for the offboarded employee and then generates access to the same applications and orders the same devices for the newly onboarded employee.

For processes that can be fully automated, you can use a Fully Unattended Robot. These robots need no assistance or activation. Whenever the robot detects a new request, it activates itself and performs the tasks based on predefined criteria. Flawlessly. We know from our own experience that the robot works reliably without any fluctuations according to the way we and our clients jointly set it up. If a new invoice arrives in our accountant’s e-mail, the robot opens, reads, processes, and books the invoice in all the required systems and we only get the final notification. We have used full automation for our clients to do things like process power supply disconnection and reconnection requests, generate various regular reports, and execute GDPR compliance processes where the robot’s task was to delete sensitive customer data.

Even though many business processes can be partially or completely automated, there are activities where the human factor is necessary and irreplaceable. Processes that cannot be completely automated include those where the robot does not have clearly set-up criteria for it to work reliably, where a decision or approval of a physical person is required, and where several departments need to be involved in the process: for example, a handwritten document can be digitised, but the robot cannot guarantee the collection of all the necessary data from it unless it is a structured document. A loan approval may require an assessment of the applicant’s current income and liabilities, but another important factor is the applicant’s behaviour during their interactions with banking staff. In such cases, we deploy Long-Running Robots combining the work of a human with various types of robots. When the robot completes part of its work and the next step requires human involvement, the robot creates a task for the human, clearly specifying the expected outcome, and waits for the task to be completed. It then resumes the automatic task processing.
The robot can therefore help with the processing and preparation of all necessary information, do the necessary checks, and display all the relevant information to the human employee. The task for the employee is to make a single-click decision about the next steps. The robot then completes the job.

Flawlessly and with a quick return on investment

Robots work exactly the way they were set up. If we enter the right criteria together, the robot makes the right decisions. It accesses systems based on how we have set it up. It never gets tired or stops working due to being bored of repetitive processes. It is not a problem even if the system is overloaded or if it crashes. The robot reopens the system and resumes working where it left off because it continuously logs all completed operations. If you decide to invest into partial or full automation, the return on your investment depends on the size of the automated process. It may vary from three months for simpler solutions to one or one and a half years for automating more complex processes. The robots will also save you labour costs and eliminate errors. If you need advice on how to start or extend process automation and digitisation, we will be happy to help you, analyse options, and prepare a strategy for your company. Getting all the necessary licences will not be a problem for you either. We can rent them (RPA as a service) or get them for you. The benefit of renting is that you get all the updates as well as the IT support and service. At Soitron we take care of the robot completely. If you decide to purchase a full licence, we can train your specialists and provide them with all the necessary information.

Three questions to answer before RPA deployment

If you have ever been interested in Robotic Process Automation (RPA), you are most likely familiar with its benefits, which include increasing productivity and efficiency as well as reducing cost.

A software robot never sleeps, which saves a lot of time and speeds up processes; it also relieves people of time-consuming and routine tasks. This results in improved services for customers and the general public as well as higher employee satisfaction.

But even RPA technology cannot do everything. For it to be successfully deployed, some necessary prerequisites must be met. Here are the three basic things to keep in mind before implementing RPA.

1. Nothing is done without input data

RPA needs digital data; it cannot handle paper documents. If you want the software to automate things, such as the processing of written customer complaints or invoices arriving by traditional mail, these documents need to be digitised first.

Ideally, input data should be “structured”, i.e., organised in a predefined way. The data available in companies and organisations (such as emails, audio recordings, videos, and images as well as digitised handwritten forms) is often unstructured, which may seem to be a major obstacle to the effective implementation of RPA.

However, having data in a form inappropriate for robotic processing is not an insurmountable problem. Today, paper documents can be quite reliably “read” using Optical Character Recognition technology. Similarly, there are solutions for transcribing audio recordings from contact centres and turning them into text files.

2. A software robot has no brain

Robotic software can process anything it was programmed to do, but it is not intelligent enough or able to learn on its own. So you cannot expect it to answer questions that have no clear answer to them. Such questions require careful consideration by humans and cannot be outsourced to robots.

For example, when approving loans or any other type of application where an applicant may meet some yet not all criteria, an automatic rejection could possibly mean the loss of business or an unhappy customer. This is why the automated application approval process should be complemented in some cases with the expert opinion of an experienced person which may be partly based on feelings.

However, the need for human judgement and decision making at some stages of the process does not automatically mean that the activity is not suitable for automation. It only means that the automated process conducted by a robot may sometimes require the involvement of a human. This can be done, for example, by a window popping up on the screen of the person in charge whenever the robot is unable or unauthorised to do something on its own.

The lack of RPA intelligence can also be dealt with by incorporating artificial intelligence and machine learning elements. In such a combination, the software robot is able to adapt and learn to make decisions based on the broader context as well as past experience.

3. Necessary integration

For RPA to be effective, it may sometimes be necessary to process large amounts of data in a variety of formats from multiple sources. For example, accounting departments tend to receive invoices from multiple vendors in a variety of formats, with individual data being located in different parts of the document. For the software to be able to read the data, it is necessary to either unify the format or adapt the robot to be able to read the data from any required form and shape.

As with the previous points, the diversity of formats and data sources is not an insurmountable obstacle. It is merely a complication to consider when determining the total labour intensity and making a costs-benefit analysis when deciding which processes are cost effective for automation and where the return on the investment may no longer be adequate.

When considering limitations and possible obstacles to the implementation of RPA, it is worth remembering that a software robot will not fix an essentially faulty or inefficient process. This is the reason why we at Soitron analyse the affected processes and, if necessary, propose how they can be improved using business process management tools before the automation.

To sum it up, when considering RPA, it is essential to find a partner who knows the prerequisites for the successful implementation of automation very well and who provides a wide range of services (including integration and process management) that may be critical for the effective use of RPA.

Soitron wants to help hospitals and authorities manage the coronavirus crisis free of charge

Soitron responds to the coronavirus crisis and offers assistance to healthcare facilities and public authorities. Through our partnership with RPA software company UiPath which donates free licenses for software robots to hospitals and public sector institutions until September 2020, Soitron will oversee free implementation and subsequent IT support. The offer is valid for the Czech and Slovak Republics. Software robots, which are able to process very large amounts of data quickly and accurately, can become digital assistants to medical staff and public workers.

The RPA automation software can be used in any repetitive and rules-based process. As a result, it can learn and execute a “robot” or computer software based on algorithms. So-called unattended robots will find widespread use. They can process invoices at the authorities, enter new patients in the healthcare system and predict health consequences for the existing ones.

“Working on the UiPath RPA platform, we are able to put RPA into practice very quickly in hospitals as well as in public administration institutions. Nowadays, repetitive, time-consuming activities without much added value can be delegated to software robots, who can perform complex tasks without interruption and error without the help of artificial intelligence (AI) and machine learning (ML).”

VIKTÓRIA LUKÁČOVÁ BRACJUNOVÁ
Head of Automation and Robotics

Faster application processing and more efficient testing

Due to the pandemics of the new coronavirus, the Social Insurance Company (SP) is currently experiencing a major onslaught in Slovakia as part of applications for family member care (OCR) and for sickness benefits. If the insurance company deployed RPA technology, the process would be automated and significantly accelerated.

Problems are also expected elsewhere – labor offices are preparing for a large increase in citizens’ applications for inclusion in their records and for the processing of unemployment benefits. At the moment, everything is handled by officials only by e-mail or mail. Automation can also speed up the processing of applications by companies and sole traders for financial support due to a decrease in revenues under state measures. The implemented algorithm would only submit applications that meet the specified criteria after evaluating the staff of the authority. This eliminates the error rate of the human invoice.

In healthcare, RPA can help, among other things, automate patient records, search for medical history, and test for coronavirus infection. An automated process can make a significant contribution to reducing the time it takes a patient to wait for exams to be received.

“The big advantage is that RPA is a technology that we can relatively easily implement remotely and therefore help where it is most needed,” concludes Victoria Bracjun, adding that Soitron provides assistance in more areas. For example, it can protect hospitals from cyberattacks.

Soitron’s offer of RPA assistance is still valid until 30 September 2020, with a potential option of extending it for the duration of the pandemic.

The Slovak parliament says no to expensive business trips. Thanks to our videoconferencing system

Modern communication solutions are already used by many organizations. This year also National Council of the Slovak Republic (NCSR) has joined and with the new video conference system they expanded the possibilities of effective communication.

Soitron supplied NCSR with a modern video conference system which is now located in a representative meeting room. The video conference room, which was originally an ordinary meeting room, is now equipped with monitors and a third presenter track, which can recognize and watch the current speaker.

The solution itself is based on the Cisco Telepresence SX80 technology with a speaker track, controlled by the Touch 10 touch panel. Call management is provided by Call Manager and Expressway. For the first time, we’ve also tried CMS (Cisco Meeting Server) recording, which also covers video conferencing resources for multipoint connections. Cisco DX80 devices are also included in our solution. It is a smaller, portable conference system that can be flexibly used by the office at different locations as needed. As the NCSR office describes, the system thus consists of two systems:

“The first one is a conference room for 20 chatters equipped with monitors and three fully automated cameras with the ability to find and watch the speaker. It can also watch the presenter.“

NCSR sought a solution that would facilitate communication with local and foreign institutions. Thanks to the video employees can now connect for example with the European Commission at any time and without having to travel abroad. Apart from the time devoted to business trips, the costs associated with negotiating abroad will also be significantly reduced.