Knowledge assistants
Search manuals, internal instructions and product information using natural language.
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AI that solves real tasks
Turn company knowledge into a useful AI solution.
We develop assistants, knowledge search and automations with large language models (LLMs). The solution is connected to your documents, data and workflows—with clear access rules and human review where it matters.
Applications
Where AI can create measurable value.
We start with the task, available information and expected benefit—not with a particular model.
Document processing
Extract, classify, compare or summarise information from recurring documents.
Text assistance
Create drafts and structured replies while keeping people in control.
Workflow automation
Combine AI with rules, databases and existing processes instead of operating it in isolation.
Software integration
Add useful AI functions to custom tools, web applications and inventory systems.
Small pilots
Test feasibility, quality and operating costs with a manageable first use case.
From source to answer
A controlled system instead of an isolated chatbot.
- 01Select sources
Define which documents, databases or interfaces may be used.
- 02Retrieve context
RAG provides relevant information for the current request.
- 03Generate result
The LLM formulates a result based on instructions and supplied context.
- 04Check and use
Sources, rules and human approval make results more dependable.
Data and responsibility
Cloud, local or hybrid—matched to the project.
Data sensitivity, quality requirements, response time and cost determine the architecture. External AI services are not connected to confidential customer data without prior agreement and a suitable legal basis.
- Transparent data flowsSources, providers and storage are documented.
- Defined accessUsers receive only permitted information.
- Quality checksTests and review paths fit the use case.
- Maintainable operationPrompts, sources, interfaces and models can be updated.
FAQ
Frequently asked about AI and LLMs.
What is an AI assistant?
An AI assistant combines a language model with instructions, approved knowledge and, where useful, software functions for a specific task.
What does RAG mean?
Retrieval-Augmented Generation retrieves relevant information from defined sources and supplies it to the language model as context for the answer.
Can existing software and data be connected?
Yes. Depending on the system, documents, databases and APIs can be connected with suitable access controls.
Does the solution have to run in the cloud?
No. Cloud, local and hybrid architectures are possible. The right choice depends on data, quality, cost and performance requirements.
Can incorrect AI answers be prevented completely?
No language model is error-free. Relevant sources, narrow tasks, tests, rules and human review can substantially reduce risk.
Can we start with a small project?
Yes. A clearly bounded pilot is often the best way to evaluate value, quality and ongoing costs before expanding.
Your use case