SOLUTIONS - Inero Software - Software Consulting https://inero-software.com/category/solutions/ We unleash innovations using cutting-edge technologies, modern design and AI Wed, 19 Mar 2025 12:40:12 +0000 en-GB hourly 1 https://wordpress.org/?v=6.9.1 https://inero-software.com/wp-content/uploads/2018/11/inero-logo-favicon.png SOLUTIONS - Inero Software - Software Consulting https://inero-software.com/category/solutions/ 32 32 153509928 Optimization of Back-Office Processes with AI Agent Implementation: A Practical Example https://inero-software.com/optimization-of-back-office-processes-with-ai-agent-implementation-a-practical-example/ Wed, 19 Mar 2025 12:38:32 +0000 https://inero-software.com/?p=7613 In this blog we will explore how an AI-powered agent can support legal, administrative, and human resources departments. Check out our latest case study.

Artykuł Optimization of Back-Office Processes with AI Agent Implementation: A Practical Example pochodzi z serwisu Inero Software - Software Consulting.

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Are you looking for practical examples of AI agent applications in a business setting? In our previous blog, we discussed integrating an AI agent with email in a freight forwarding company. You can find the full text here >>. This time, we will explore how an AI-powered agent can support legal, administrative, and human resources departments. Check out our latest case study.

AI agents are intelligent systems based on machine learning algorithms. You can learn more about them in this text >>. They can be integrated with various tools such as email, ERP, or CRM systems. In this example, we will demonstrate an integration with the Slack communication platform.

Slack is used as a team collaboration tool that enables messaging, organizing discussions in thematic channels, file sharing, and integration with other business applications.

One of the available options is API integration with a selected LLM (Large Language Model) such as Gemini, ChatGPT, or DeepSeek. This time, our AI agent will be based on ChatGPT from OpenAI and Google Search.

You are surely familiar with situations where an offer or contract needs to be urgently prepared by filling in a template. Every day, employees have to draft, analyze, and negotiate various documents, including commercial agreements, supplier contracts, non-disclosure agreements (NDAs), and collaboration agreements.

Many managers wonder how artificial intelligence can automate and accelerate some of these tasks without compromising the high quality of work. The solution once again lies in implementing a dedicated AI agent that supports employees by searching for and filling in information based on data from the National Court Register.

In our example, we designed the AI agent to receive commands via the Slack platform and automatically fill in contractor details in a pre-existing NDA template. Thanks to its integration with Google Search, the agent retrieves specific data from the National Court Register (KRS), including the company’s address, tax identification number, business registry number, KRS number, and the authorized representative of the company.

Next, the assistant asks for verification of the retrieved information. Once confirmed, the employee receives the NDA with the partner company’s details filled in. The completed fields are highlighted in yellow to ensure visibility of the changes made.

This is just one of many examples of how an AI agent can support documentation and front- and back-office processes. Using our developed method, we can create a tool that prepares contracts for companies dealing with, for example, seasonal employment or those with high employee turnover.

AI agents are a relatively new topic but are rapidly gaining popularity. Many companies recognize benefits such as time savings on repetitive tasks, reduced operational costs, and increased business process efficiency. By automating routine tasks, employees can focus on more strategic and creative aspects of their work.

Moreover, AI agents can operate 24/7, eliminating delays caused by staff availability. Their applications span various fields—from customer service and legal document analysis to advanced decision-support systems in business.

 

Companies are increasingly adopting open language models, allowing for greater control over data and the customization of AI agents to meet specific organizational needs. As technology evolves, we can expect even deeper AI integration into daily processes, along with a growing awareness of ethical considerations and security in their use.

Build an AI agent with us!

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Artykuł Optimization of Back-Office Processes with AI Agent Implementation: A Practical Example pochodzi z serwisu Inero Software - Software Consulting.

]]> 7613 What are AI Agents and how can they help your company https://inero-software.com/what-are-ai-agents-and-how-can-they-help-your-company/ Fri, 28 Feb 2025 09:51:15 +0000 https://inero-software.com/?p=7498 In this article, we will take a closer look at AI Agents, which can provide valuable support, particularly in back-office processes.

Artykuł What are AI Agents and how can they help your company pochodzi z serwisu Inero Software - Software Consulting.

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The term artificial intelligence has been prominently featured in numerous publications as a solution to challenges related to efficiency, organization, and creativity. Many companies are following this trend, striving to incorporate AI-driven solutions into their offerings. These efforts take various forms. In this article, we will take a closer look at AI Agents, which can provide valuable support, particularly in back-office processes.

For some time now, we have been observing a significant rise in the popularity of terms related to the use of artificial intelligence. So, let’s start from the beginning.

What is "Artificial Intelligence"?

The term “artificial intelligence” encompasses Large Language Models (LLMs), natural language processing (NLP) systems, machine learning algorithms, neural networks, and generative AI models.

LLMs, such as ChatGPT from OpenAI or Gemini from Google, are models trained on vast datasets that can analyze, process, and generate text in a way that mimics human reasoning. They are used in various applications, ranging from chatbots and voice assistants to advanced systems supporting business analysis and process automation in companies.

Artificial intelligence is not limited to text processing. Modern models can also analyze images, audio, video, and numerical data, making them highly versatile tools in business. AI enables not only the automation of repetitive tasks but also the detection of patterns in large datasets, trend forecasting, and support for strategic decision-making in companies.

Who are AI agents?

“AI agents” are intelligent systems based on machine learning algorithms, natural language processing (NLP) models, and Large Language Models (LLMs). Their purpose is to automate processes, support decision-making, and interact with users in a natural and context-aware manner.

This means that virtual assistants are based on well-known and widely used LLMs such as ChatGPT, Gemini, Claude, Mistral, or DeepSeek, which can generate coherent responses, analyze texts, and adapt to the context of a conversation.

However, AI agents differ from language models in that they are designed to perform specific tasks autonomously. In practice, this means they are equipped with additional modules that enable them to gather information, process data in real-time, and make decisions based on business rules.

Unlike traditional chatbots, AI agents not only answer questions but can also handle complex processes, integrate with enterprise systems, and learn from user interactions. As a result, they are used in various areas, from administrative support and document analysis to the automation of operational processes in enterprises.

Also read: Meet Your Personal AI Agent – A Case Study for a Freight Company

The operation of AI agents is based on several key components:

    • Communication interface – allows the agent to interact with users through text, speech, or other data formats.
    • Decision engine – based on AI models and business rules, it enables situation analysis and the selection of optimal actions.
    • Integration with external systems – AI agents often operate in conjunction with databases, business applications (ERP, CRM), or cloud services, allowing them to access up-to-date information.
    • Process automation – they can perform specific tasks, such as generating reports, processing requests, sending notifications, or initiating predefined processes in IT systems.

What are the types of AI agents?

AI agents may take various forms depending on their application and level of autonomy. Leveraging advanced artificial intelligence models, they can assist users in a wide range of activities, from customer support to data analysis and business process management.

We can distinguish several main types of AI agents:

    • Conversational agents – include chatbots and voicebots that interact with users through text or speech. They can answer questions, handle customer inquiries, and support sales processes.
    • Analytical agents – specialize in processing and interpreting data. They use machine learning algorithms to analyze trends, detect anomalies, and generate reports.
    • Operational agents – automate business tasks by integrating with enterprise systems. They can manage documentation, process documents, or coordinate activities within corporate processes.
    • Autonomous agents – operate independently, making decisions based on collected data and predefined business rules. They are used in areas such as logistics, resource management, and dynamic operational planning.
    • Decision-support agents – provide recommendations based on advanced data analysis, helping managers and specialists make strategic decisions.

Each of these types can operate independently or collaborate with other systems, creating a complex AI-driven environment. In the following sections, we will explore specific applications of AI agents and their impact on the operational efficiency of businesses.

Cloud or on-premise solution – how can an AI agent be implemented in a corporate environment?

Implementing an AI agent in an organization requires selecting the appropriate deployment model that best meets business, technical, and regulatory requirements. Companies can choose between a cloud-based solution (SaaS) or an on-premise deployment, depending on their needs for flexibility, security, and integration with existing systems.

The choice of the appropriate model depends on various factors, which are presented in the table below.

Comparison: SaaS vs On-Premise
Criterion SaaS (Cloud) On-Premise (Local)
Deployment model Cloud-based (AWS, Azure, Google Cloud) Operates on the company’s own infrastructure
Infrastructure Cloud service provider Local servers
Initial costs Low High
Operational costs Subscription-based Fixed maintenance and energy costs
Scalability Very high Limited (dependent on hardware)
Data security Limited (processed outside the company) High (full control over data)
Regulatory compliance May require additional agreements and certifications Easier to meet regulatory requirements
Ease of implementation Easy and fast Requires hardware purchase and setup
Updates and maintenance Automatic, provided by the vendor Self-managed updates and maintenance
Integration with enterprise systems Strong API support and pre-built integrations Full control but may require additional integration

The choice of the appropriate deployment model—cloud-based or on-premise—depends on the company’s specific requirements regarding security, costs, and integration with existing systems. Regardless of the chosen strategy, AI agents can significantly enhance operational efficiency and allow employees to focus on tasks that require creativity and strategic thinking.

The development of AI technology is undoubtedly one of the strongest technological trends in recent years. Therefore, it is worth considering now how AI agents can support your company’s growth and become a key element of its digital transformation.

We will create an AI Agent for your company.

Contact us to learn how we can help you implement a new AI-based solution.
Contact us

Artykuł What are AI Agents and how can they help your company pochodzi z serwisu Inero Software - Software Consulting.

]]> 7498 Meet Your Personal AI Agent: A Case Study for a Freight Forwarding Company https://inero-software.com/meet-your-personal-ai-agent-a-case-study-for-a-freight-forwarding-company/ Fri, 21 Feb 2025 11:27:19 +0000 https://inero-software.com/?p=7341 AI-driven tools are becoming increasingly prevalent across various industries, streamlining processes from simple graphic design and translations to advanced document, email, and database analysis. In this article, we will present a practical business application of an AI assistant in action. AI Agents have a wide range of applications, and their…

Artykuł Meet Your Personal AI Agent: A Case Study for a Freight Forwarding Company pochodzi z serwisu Inero Software - Software Consulting.

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AI-driven tools are becoming increasingly prevalent across various industries, streamlining processes from simple graphic design and translations to advanced document, email, and database analysis. In this article, we will present a practical business application of an AI assistant in action.

AI Agents have a wide range of applications, and their full potential is still being discovered. The main advantages of AI-powered assistants include:

1. Automating Routine Processes

AI agents can handle repetitive tasks such as customer inquiries, document analysis, and data management. By automating these processes, businesses can reduce operational costs and improve efficiency.

 

2. Personalized Customer Interactions

By analyzing data, AI agents can provide personalized recommendations and tailored offers, enhancing customer engagement and improving overall user experience.

 

3. Speed and Availability

AI operates 24/7, delivering instant responses and real-time support. This is particularly valuable in industries that require quick reaction times, such as e-commerce, finance, and logistics.

 

4. Advanced Data Analysis

AI-powered agents can process vast amounts of data in a short time, identifying patterns and correlations that support better business decision-making.

 

5. Optimizing Decision-Making Processes

With predictive modeling, AI assists in demand forecasting, risk management, and supply chain optimization, helping organizations make more informed decisions.

 

6. Seamless Integration with Existing Systems

Modern AI solutions can be easily integrated into existing ERP, CRM, and analytics platforms, enhancing their capabilities and improving overall system efficiency.

A Practical Example of AI Agent Use in the Transport Industry

AI agents can be applied across various industries, including banking, sales, and human resource management. In this text, we will focus on a freight forwarding company that handles anywhere from a few to dozens of shipments daily.

 

 

Freight forwarders deal with constant communication and the verification of numerous documents. Each of these tasks takes time—a resource that is often in short supply—making errors more likely when the workload is high.

 

 

How can time management be improved? By automating repetitive and predictable tasks. This is where an AI Agent comes in. Here’s an example of an AI assistant we developed, powered by Google’s Large Language Model, Gemini.

 

One possible application is the following scenario:

 

 

A freight forwarder receives an email that should include an insurance policy along with proof of payment. The AI Agent automatically, without needing to be prompted, checks whether the email contains the required attachments. If they are included, it proceeds to verify the following details:

In the Insurance Policy:

      • Policy number
      • Insurance period and whether it is currently valid
      • Insured party details, including tax identification number and address
      • Bank account number for premium payment

In the Payment Confirmation:

      • Payment reference
      • Amount
      • Bank account number
      • Payment date
      • Whether the transfer corresponds to the submitted policy (e.g., based on the reference, account number)

The AI Agent then transfers the extracted data into a designated Excel file, which is continuously updated. The data file can be formatted accordingly, for example, by highlighting entries in red where the insurance policy is invalid or the payment has not been verified. 

In this simple way, instead of searching through their inbox for the right emails, the freight forwarder can check the Excel file to see if the documents have been received from a specific sender and whether they are correct. This saves a significant amount of time and ensures data accuracy.

 

There are many ways to further develop our AI Assistant. It can be integrated with other tools, such as Slack or other communication platforms, to send notifications about missing documents or generate automated email responses. An AI-powered agent can be tailored to the specific needs of a company, a department, or even an individual role.

Do you want to explore the possibilities of AI Agents?​

Schedule a meeting. We’d be happy to discuss the possibilities.
SCHEDULE A MEETING

Artykuł Meet Your Personal AI Agent: A Case Study for a Freight Forwarding Company pochodzi z serwisu Inero Software - Software Consulting.

]]> 7341 Best Practices in Keycloak: Secure Your System in 5 Steps https://inero-software.com/best-keycloak-practices/ Mon, 13 May 2024 13:55:51 +0000 https://inero-software.com/?p=5732 Keycloak is a tool for managing identity and access that ensures the security of applications and web services. To maximally secure your environment using it, it’s important to implement best practices. Here are 5 key steps that will help you in this process. Enable HTTPS and Use Strong Certificates The…

Artykuł Best Practices in Keycloak: Secure Your System in 5 Steps pochodzi z serwisu Inero Software - Software Consulting.

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Keycloak is a tool for managing identity and access that ensures the security of applications and web services. To maximally secure your environment using it, it’s important to implement best practices. Here are 5 key steps that will help you in this process.

Enable HTTPS and Use Strong Certificates

The first and most crucial step is to ensure all communication with the Keycloak server is done through the secure HTTPS protocol. Using SSL/TLS certificates from trusted providers protects against data interception and manipulation.

In this step:

    • Configure the Keycloak Server: Set the server to use only HTTPS, rejecting all unencrypted HTTP requests.
    • Update Certificates: Regularly renew and update SSL/TLS certificates to avoid the risk of exploiting outdated keys.

Implement Multi-Factor Authentication (MFA)

This feature adds a layer of security by simultaneously using multiple methods to verify a user’s identity. 2FA (Two-Factor Authentication) is a popular form of MFA that often requires users to enter a password and confirm their identity with a second factor, such as a code from an authentication app.

In this step:

    • Activate Multi-Factor Authentication in Keycloak: Enable MFA for all users, especially those with administrative access and access to sensitive data.
    • Choose Authentication Methods: Keycloak supports various MFA methods; commonly used ones include authentication apps (e.g., Microsoft Authenticator).

Read also:

Implement strong password policies and session management

Password and session management are key to protecting user identities and preventing unauthorized access. They are the first line of defense against attacks such as brute force or phishing. Keycloak provides a wide range of configurable password policy settings from the administrative console.

In this step:

    • Configure the password policy: Set precise rules for password selection to require specific lengths, complexity (e.g., the presence of special characters, uppercase and lowercase letters), and define the password’s lifespan and history.
    • Limit session lifespan: Set short but practical session and token lifespan to minimize the window for potential attacks. Automatically logging out users after a specified period of inactivity is important for preventing accidentally leaving sessions open on shared or public devices.

Read also:

Secure API endpoints and use Role-Based Access Control (RBAC)

Role-Based Access Control (RBAC) allows for defining roles, assigning them to users, and managing permissions, enabling control over API operations depending on the role.

In this step:

    • Securing API endpoints: To secure API endpoints, it is crucial to apply appropriate authorization and authentication mechanisms:
    • Authentication: Implement authentication protocols such as OAuth 2.0 and OpenID Connect, so users and applications must prove their identity before gaining access to the API. Access tokens: Use access tokens, which contain information about user permissions, to verify access rights to various API resources. HTTPS: Ensure that all requests to the API are sent over HTTPS, protecting data from interception and modification. Role-Based Access Control (RBAC): Role-Based Access Control allows for managing user permissions based on their roles in the organization:
    • Defining roles: Establish roles that reflect different access levels in the application, e.g., administrator, user, guest, etc. Assigning roles: Assign roles to users that specify which resources and operations they can access. Managing permissions: Configure access policies in Keycloak to control which operations can be performed by users with a given role at specific API endpoints.

Read also: 

Regularly update and monitor the environment

Updating and continuously monitoring the Keycloak environment is essential to maintain high protection against new threats and security vulnerabilities. Keycloak updates appear every few months, and information about them can be found on the official project website or in the Keycloak documentation.

In this step:

    • Updates: Regularly update Keycloak to the latest stable versions.
    • Monitoring and logging: Use monitoring tools to track any unusual behavior and respond quickly to potential security incidents. Set up logging systems to collect key information about system operation. For example, using Kubernetes, you can efficiently manage and scale monitoring and logging tools such as Prometheus and ELK Stack. Kubernetes facilitates the deployment and management of containers with these tools, automating their deployment, scaling, and repair, which is crucial for maintaining continuity of operation and security in distributed systems.
    • Choose a proven partner: If implementing Keycloak best practices seems like a labor-intensive process that will heavily burden your team at this stage, seek help from specialists in this field.

Read also:

Inero Software has extensive experience in implementing advanced cybersecurity solutions. We create comprehensive systems for managing users and their roles, tailored to complex IT infrastructures and meeting high corporate standards. Our team, consisting of cybersecurity experts, implements advanced authorization schemes in accordance with renowned security standards. Thanks to our knowledge and experience, we provide effective protection against threats and compliance with corporate security policies.

Artykuł Best Practices in Keycloak: Secure Your System in 5 Steps pochodzi z serwisu Inero Software - Software Consulting.

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