Services Entwicklung Enterprise AI

Do you place a high priority on incorporating the latest trends into your online store? Are you looking for an AI specialist in large language models (LLMs)? You’ve come to the right place. Kenner Soft is your best partner for graph technology and the efficient use of AI. We help you automate business processes within your company and improve decision-making.

To solve problems and ensure process automation, we use AI algorithms and tailor them to your business needs. Our team develops innovative AI applications for your company to boost its efficiency and reduce the workload on your staff. Let’s discover the benefits of AI for your business!

How is AI changing modern businesses?

Corporate AI is completely transforming everyday working life. Repetitive tasks are being automated, allowing staff to focus more on core business activities. AI contributes to process optimization and reduces the workload for employees by creating and analyzing texts and generating program code. Generative systems mimic human creativity and can create data independently. Thanks to AI, the company is working more efficiently.

These days, the use of AI agents is both practical and widespread. According to the Cloudare study, 96% of companies use intelligent agents. They perform the following tasks:

automate administrative processes (intelligent document processing, invoice processing, contract management);
decision-making and strategy development based on identified market trends and customer behavior;
real-time protection against cyberattacks, identification of suspicious activity (detection of unusual transactions and blocking of fraud);
Optimizing production processes and the supply chain.

With the help of AI, large amounts of data are collected, analyzed, and interpreted. This improves efficiency, automates routine tasks, speeds up content creation, and creates personalized learning experiences. AI-powered assistants help plan meetings and quickly retrieve various information. This frees employees from manual, time-consuming work. Companies reduce their own resources, increase overall productivity and profitability, and can drive growth.

What is RAG (Retrieval-Augmented Generation)?

This term refers to a software system that combines information retrieval with large language models. It allows documents to be retrieved and texts to be generated by LLMs. The generated texts are accurate because the queries submitted to the system access information from various data sources and databases. This gives chatbots access to internal company data and enables them to provide factual information.

RAG systems combine document search and response generation using LLMs. Modern LLMs can also solve different tasks. Large language models are used with RAG without fine-tuning for chatting with your own data. Retrieval augmented generation can be combined with all LLMs (programmatically or via API). Various databases and searches are used for RAG to display search results as text sections. To use knowledge graphs and SQL databases, an LLM generates the database query in the required query language (SQL, SPARQL, Cypher). With the help of open source libraries (LlamaIndex and LangChain), the databases can be connected to LLM and the vector database with embedding model and document importer. The latter implement the standard interfaces for large language models and related technologies and can be integrated with many providers.

Advantages

The quality of the generated responses is high. They are up-to-date and contextually accurate.
Introducing new data into the LLM is cost-effective.
User confidence improves because the information is presented with real source references.
RAG improves control of AI applications for developers. They can monitor and modify the LLM's information source to adapt it to changing requirements.
The model parameters are not adjusted, so the model can be moved across many use cases.

Disadvantages

RAG requires high computational effort and presents difficulties in validating responses.
Text generation takes longer due to the multi-stage processing of information.
RAG systems are only effective if the data is current and relevant.
When updating a knowledge base, developers should initiate the conversion of new data into vectors and update the vector database.
When comparing RAG vs. fine-tuning, the former is lightweight. The LLM is used in its original form. Since it can process natural language, costs and time are saved. It can be easily kept up to date with the latest knowledge.

Integration of AI models for automating business tasks

Corporate AI is growing worldwide and opening up new opportunities. AI tools can be used to simplify many routine tasks, speed up processes, and reduce costs. They enable large amounts of data to be analyzed quickly and solutions to be found. AI applications work on the basis of machine learning. They analyze customer behavior and influence business development with new ideas. They can be used to increase employee productivity by allowing them to focus better on important tasks. For example, AI co-pilots offer support with email management and planning. AI-powered learning platforms enable personalized training and development.

Artificial intelligence is revolutionizing the business world across all industries and sectors. Thanks to their enormous potential, these tools are transforming everyday working life. Chatbots can automatically answer numerous customer questions, recognize text, and assist with project management. This enables companies to reduce processing times and increase customer satisfaction. AI solutions assist in decision-making by analyzing data. In the logistics industry, AI systems analyze traffic data, weather conditions, and delivery times, calculate routes, and ultimately lead to cost savings.

The most important areas of application are: email and document management, scheduling, data analysis, customer service, human resources, finance and project management, IT support, marketing, sales, content creation, and security monitoring.

Intelligent systems are used to perform a wide range of repetitive tasks. They give companies a real competitive advantage.

What tasks can be automated using AI?

Artificial intelligence can be used to simplify and speed up a variety of tasks. This primarily applies to repetitive, data-driven, and time-consuming activities such as data analysis, content creation, and bookkeeping. Here are some examples of how our Web development Agency uses AI.

Product Description

AI enables process automation. Product descriptions can be generated automatically. Staff do not need to do everything manually. This reduces time-to-market. Thanks to NLP, these texts are not only grammatically correct but also tailored to the target audience.

SEO for Categories and Products

AI tools assist with keyword research, grouping keywords into semantic categories, content creation, and optimization. You can automatically generate SEO-optimized meta titles and descriptions.

Product Recommendations

Data can be collected and used for machine learning models. Customer behavior is analyzed, and similar products are recommended to them. These personalized recommendations help increase sales.

Customer Service

The use of AI agents in your business makes customer service even more appealing. They handle inquiries even outside of business hours. The bot makes specific recommendations based on purchase history and guides the customer to their goal. To ensure consistent communication in your online store, contact our Agency for Chatbot development.

Review Processing

Natural Language Processing (NLP) transforms subjective customer opinions into objective statistics. Our webshop development specialists integrate NLP software with your CRM system and adapt it to the terminology of your industry.

Content Personalization

To strengthen customer loyalty and increase conversion rates, content must be personalized. This ensures that customers receive information that is specifically relevant to them. To achieve this, AI categorizes them into groups with similar characteristics. They receive discounts or personalized messages.

Sales Forecast

As a leading AI company, we help you develop and integrate machine learning models and customize time-series models to transform historical data into future predictions. This enables you to forecast revenue or product volume and utilize transportation capacity efficiently.

Inventory Management

Kenner Soft processes your data, develops and integrates suitable AI models, adjusts forecasts to market conditions, and defines rules for automatic ordering. This allows you to predict what will happen under specific conditions.

Marketing Campaigns

Our team specializes in using AI algorithms to manage advertising campaigns, optimizing bids and creative assets. We clearly define your goals and set up conversion tracking to ensure your campaigns are successful.

Fraud Detection

To detect suspicious transactions and fraud early on, we implement and monitor specialized AI systems. This helps you avoid financial losses and keeps your business protected. At Kenner Soft, you’ll find highly skilled software developers who can train your team and provide expert support.

Search the Website

When AI is introduced into a company, semantic search algorithms are implemented and the logic is adapted to industry-specific terminology. We optimize the data structure to ensure precise results.

Product Configurator

At Kenner Soft, we make effective use of artificial intelligence when building configurators to create customized quotes. Our experts develop configuration software that is specifically tailored and adapted to your business.

Graph databases and knowledge graphs

A graph database is a system that systematically collects data/entities (nodes) and the relationships between them (edges). The network of entities (information) is called a knowledge graph. They are bound by several standards and principles that are necessary for data integration and interoperability. They use semantic web technologies (RDF, OWL, SPARQL) for understandable data representation and querying for humans and machines. Knowledge graphs are not limited to a single source or domain. They capture and link data from multiple locations.

Graph databases store networked data and help navigate within these structures. Neo4j is one of the leading NoSQL databases, offering core functions such as native vector search and a variety of integration options with common technologies and tools. It uses a flexible query language—Cypher—and has a robust architecture that is important for meeting specific requirements.

Neo4j can be used for various purposes. These include:

Recommendation systems. The graph database can be used to identify relationships between products and user interactions and provide personalized recommendations.
Network analysis. Network data analysis and visualization are performed in the IT security industry, telecommunications networks, and social networks.
Fraud detection. The graph database helps to detect fraudulent activities.

Neo4j improves usability with new features. Thanks to the new Data Importer feature, data is imported and CSV files are modeled as graphs. No cyber knowledge is required. The no-code solution is easy to use and ensures a smooth project start.

While Neo4j enables modeling and analysis of relationships between entities and objects, large files (images, photos, videos) are stored on a server – MinIO. Both solutions can be used in applications to represent structured and unstructured data and their relationships.

Implementation of leading AI models: Grok, OpenAI

Artificial intelligence has a major impact on business development. Using this technology makes businesses smarter and more future-proof. It opens up new opportunities for companies and allows them to build competitive advantages. There are currently many AI models that mark a leap forward in the capabilities of machine language systems. At Kenner Soft, we support you in choosing and implementing the right models to automate your business processes.

OpenAI O3, the latest model, is designed with a focus on logical thinking. It is a reflective model, unlike previous GPT models. O3 solves problems and difficult tasks in mathematics, programming, and science better, mixes visual and textual inputs, and uses Python, search, and image inspection to improve answers. Projects with complex reasoning tasks benefit from innovative analytical capabilities.

Grog is an advanced AI chatbot from xAI based on a generative LLM that provides solutions for complex tasks (mathematics, reasoning, large-scale text processing). It can do more than just text processing; it offers functional thinking, plans, analyzes, provides structured and formatted answers, and integrates new information in real time using its own computing capabilities.

At Kenner Soft, we develop AI-driven applications and successfully implement them into your e-commerce platform. This process involves the following steps:

Planning and goal definition: Consideration of all risks

Feasibility analysis: Resource assessment and review of data availability and quality

Data source definition: Data cleansing and extraction

Development of AI models for specific use cases

Integration

Performance monitoring: Analysis and troubleshooting

Training your employees and assessing scalability

Customer support throughout the entire process

Why is Kenner Soft your partner for AI strategy and implementation?

When searching for a qualified service provider, you may encounter several obstacles: some may lack the necessary expertise, while others may offer poor terms and conditions. At Kenner Soft, we guarantee the highest quality and transparent pricing.

Our agency offers you a complete service package. We provide expert advice and work with you to develop a suitable AI strategy for tackling your industry tasks. Our team has excellent technical knowledge and experience with AI, RAG, and Neo4j. In addition to developing AI tools, we tailor different AI models precisely to your company's requirements and develop interfaces for their integration as needed. Kenner Soft deals with RAG development based on user data for quality improvement and its implementation, as well as the connection of AI models for business process automation (data validation, creation of product and profile descriptions, reporting, chatbots for customer service).

As an experienced e-commerce specialist, our agency integrates AI into your shop (Shopware, OXID, JTL). You can rely on our experts without any concerns. They are experienced and constantly training to offer you a high-class service.

If you need enterprise AI solutions, contact Kenner Soft!

How many companies use AI?

41% of German companies currently use AI in their business processes.

Where can AI be used?

AI can be used in various areas (commerce, industry, medicine, media, security, climate protection).

How can modern AI models such as Grok or OpenAI be integrated into existing business processes?

They can be integrated for data analysis, customer support, and other tasks using no-code/low-code tools and plugins or via API.

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