AI/ML 
Software Development 
Knowledge Management with LLMs
Smart knowledge, right where you need it.
We’ve developed an AI-powered knowledge management platform based on large language models (LLMs) and Retrieval-Augmented Generation (RAG) architecture. It integrates with your operational systems, ERP/CRM, and internal communication tools. The platform supports maintenance, sales, and communication – whether on the shop floor, in the office, or in the cloud – providing fast access to operational knowledge and documentation, regardless of the user’s experience level.
Why does this solution matter?
In many organizations, operational knowledge is fragmented and difficult to use in daily work. Technical documentation exists in multiple formats and locations – from PDFs and paper manuals to network folders. The history of previous failures may be stored in isolated systems with limited access, while valuable employee knowledge often resides only in memory or private notes. In practice, this means that access to critical information is slow and inconsistent, and decision-making is often based on intuition or incomplete data.
Our AI knowledge platform centralizes key resources — documentation, logs, service tickets, and notes — and makes them instantly accessible. Thanks to natural language queries and real-time responses, employees get precise answers backed by verified sources. The result: faster problem-solving, better operational decisions, and fewer repeated mistakes. The organization becomes more efficient, predictable, and resilient.
What challenges do clients face before implementing this solution?
Searching across multiple formats and systems
technical documentation is stored in PDFs, scans, directories, etc., increasing the time needed to find relevant data
Intuition-driven maintenance and emergency response
in critical moments, teams often rely on the experience of one person, increasing repair time and risk
Loss of operational knowledge due to staff turnover
much of the expertise is not formally documented, leading to a “knowledge drain” when employees leave
Data silos and lack of integrated access
incident history, machine logs, procedures, and documentation live in separate systems, delaying decisions and actions
What are the benefits of an AI-powered knowledge management platform with LLM?
- Real-time access to knowledge – users can ask questions in natural language and receive instant, contextual answers with clear sources.
- Preservation and archiving of operational knowledge – team know-how is retained despite staff turnover; all solutions are documented for future reference.
- Scalability and reduced downtime – an integrated knowledge base and faster diagnostics help reduce machine downtime and boost operational efficiency.
- Smart data integration – the system connects technical documentation, service history, machine logs, notes, and checklists — eliminating manual searching.
- 24/7 availability and ease of use – accessible across all shifts, regardless of user experience; the interface requires no advanced IT skills.
- Data security and control – the platform runs in a client-controlled environment, processing only selected internal data; it can be deployed on-premises or in the cloud.
Metodology 4D
Discovery
Understanding the DNA of the problem before the first line of code is written
The Discovery phase allows for a deep understanding of the business challenge, user needs, and technological context. As a result, the project starts on solid foundations, and key assumptions are validated before development begins.
Key artifact
Standardized Concept Document
Our focus
Our activities
We analyze the client’s business and technological environment: from existing systems to user needs and strategic goals. We validate business assumptions, identify risks, and define the problem to be solved. The outcome is a coherent product concept that forms the foundation for the next stages of the project.
Definition
Translating knowledge and ideas into a concrete product plan
In the Definition phase, we transform insights from Discovery into a detailed solution design. This includes defining requirements, system architecture, and the user experience concept.
Key artifact
Product & Architecture Blueprint
Our focus
Our activities
We translate business goals into specific functional and technical requirements. We design UX prototypes, define the architecture, and plan the project implementation. This ensures development starts with a clear plan and minimal risk.
Delivery
Building and delivering reliable software
In the Delivery phase, we develop the final solution. We focus on code quality, clear communication with stakeholders, and a stable product release.
Key artifact
Production-ready product / deployment
Our focus
Our activities
Our teams build the solution using modern development practices and continuous integration. We regularly test the product and maintain transparent communication with stakeholders to deliver a stable, production-ready solution.
Direction
Transforming a product into a growing digital business
Direction is a phase of long-term product development. Instead of ending cooperation after implementation, we support clients in scaling solutions, introducing innovations, and building a competitive advantage.
Key artifact
Product development and innovation roadmap
Our focus
Our activities
Together with the client, we analyze product data, identify new growth opportunities, and plan future functionalities. We help scale the solution, optimize its performance, and build a long-term product strategy.
What do you gain by working with us?
- Significant reduction in repair time (MTTR) and operational downtime.
- Retention of operational knowledge and better information accessibility – even during employee turnover.
- Increased productivity of technical and operational teams – fewer errors, less time spent searching for information.
- Scalable implementation – the platform can be extended to new areas without major infrastructure overhauls.
- Better operational decisions thanks to real-time data access, system integration, and a complete data view.
Where is an AI knowledge platform essential?
Industrial manufacturing plants – e.g. pharmaceutical production lines, where downtime is costly; the AI agent supports maintenance, diagnostics, and access to machine documentation.
Sectors with complex technical infrastructure – such as logistics, energy, or heavy industry, where documentation, incident history, and knowledge access are vital for uptime and safety.
Sales and customer service teams – especially B2B companies with complex product knowledge, aiming to speed up responses, lead qualification, and CRM/ERP integration.
Multi-site or international organizations – operating in multiple locations, systems, and languages; the platform works globally or on-premise, delivering consistent knowledge across the company.
Organizations undergoing digital transformation – investing in back-office automation, knowledge-sharing across teams and systems, and transferring know-how from employees to a shared, searchable platform.
