The Challenge
AI agents can only work when they understand your reality.
You want the Agentic Company — AI agents that automate processes, answer questions, prepare decisions. But agents are only as good as their access to your knowledge. And today, this knowledge is trapped in silos: websites, file servers, CRM, technical documentation, employees' heads. Without a structured knowledge base, agents are blind — or they hallucinate. The knowledge base is the foundation for everything that comes next.
Data Silos
Your knowledge is scattered across websites, PDFs, emails, CRM, and employees' heads. Nobody has the complete picture — and nobody knows what's current.
Format Chaos
Websites, PDFs, Word, PowerPoint, Excel, emails — all in different formats, languages, and quality levels. No unified structure, no searchability.
No Single Source of Truth
Contradictory information in different documents. Outdated datasheets alongside current ones. No version control, no traceability.
THE SOLUTION
AI Knowledge Base
We build a structured, queryable knowledge base — your single source of truth for all AI applications. In three phases: Capture, Structure, Validate. The result: Every piece of information is findable, every source is traceable, every contradiction is resolved.
Capture
We catalog your data sources and build a repeatable ingestion pipeline: crawl websites, extract PDFs, process documents. All formats, all languages.
Structure
We develop a domain model for your company: How do products, customers, applications, materials relate? This becomes the knowledge graph — machine-readable and queryable.
Validate
Quality assurance with provenance tracking: Where does each piece of information come from? Which version is current? Where are contradictions? Automatic detection and resolution.
What You Get
Concrete Results
Data Source Catalog
Complete overview of all data sources — what exists, where it lives, who maintains it, what priority it has. No more hidden knowledge.
Ingestion Pipeline
Repeatable pipeline that processes websites, PDFs, Office documents. When sources change, the same pipeline runs again. No manual work.
Knowledge Graph
Structured knowledge base with entities and relationships. When someone asks 'Which product is suitable for phosphoric acid at 180C?', the system finds the answer.
Provenance Tracking
For every piece of information: Where did it come from? When was it captured? Which version? Conflict resolution for contradictions.
Ready to unlock your company knowledge?
Let's talk.
Let's talk.
Frequently Asked Questions
What is a knowledge graph?
A knowledge graph is a structured representation of knowledge: entities (products, customers, materials, processes) and their relationships. Unlike a database, it maps connections — when a sales rep asks 'Which reactor is suitable for phosphoric acid at 180C?', the system understands the connection between product, material compatibility, and temperature limits.
Which data sources can be integrated?
All common formats: websites (we crawl them), PDFs, Word, PowerPoint, Excel, emails, SharePoint, wikis, CRM exports, technical documentation. The architecture is extensible — ERP and PIM integrations are possible but typically a separate project.
How is this different from a data warehouse?
A data warehouse stores structured data for reporting and analytics — numbers, metrics, transactions. A knowledge graph stores knowledge with context and relationships — ideal for AI applications that understand natural language and answer questions.
How long does it take to build?
A first usable state is achievable in 8-12 weeks. This depends on the number of data sources and complexity of your domain. The knowledge base grows iteratively — new sources and use cases can be added at any time.
Do we need the AI Opportunity Assessment first?
Recommended but not mandatory. If you already know which AI use cases you want to implement and which data is relevant, we can start directly. The Potential Analysis helps set priorities and define scope clearly.
What happens when sources change?
The ingestion pipeline is repeatable. When you publish new datasheets or update documents, the same pipeline runs again and updates the knowledge base. Provenance tracking ensures old vs. new versions remain traceable.
Why We Are the Best Partner for You
In-Depth Understanding of the German Mittelstand
We specialize in working with German Mittelstand companies and understand their unique challenges and needs. Our tailored approach ensures that our GenAI solutions are perfectly aligned with the operational realities and strategic goals of Mittelstand businesses.
+20 Years of Expertise in Building Robust Software
With over 20 years of experience in data management and technology solutions, we have a proven track record of developing and integrating complex software systems. Our technical expertise ensures that your GenAI solutions are seamlessly integrated, secure, and scalable.
Advanced Knowledge in AI Technologies
Our team possesses expertise in GenAI, including large language models and AI-driven processes. We stay at the forefront of AI advancements to provide you with innovative solutions that drive efficiency, enhance customer experiences, and deliver measurable business value.