AI Assistant for Compliance & Knowledge Management
Client: ATX Company
The Challenge
In large organizations, compliance knowledge is often scattered across hundreds of documents. A leading ATX company with over 50 compliance guidelines, internal manuals, and process documents faced this challenge.
The Problem:
- Employees had no overview of relevant guidelines when facing specific questions about processes or products
- Internal compliance experts lacked capacity to answer every inquiry with necessary sensitivity
- Searching through documents was time-consuming and often led to uncertain results
- Knowledge became outdated or was applied inconsistently
The result: Slow decisions, employee uncertainty, expert overload.
Our Solution
Building a "chatbot over documents" is easy. Developing an assistant that truly understands and gives reliable answers is a different challenge. This is where Domain-Driven Design comes into play.
The Approach in Detail:
- Integration of 50+ guidelines and documents: Complete capture of organizational knowledge
- Knowledge Graph integration: Connection with company metadata for contextual intelligence
- Intelligent retrieval methodology: Not just keyword search, but semantic understanding of relationships
- Source citations with context: Every answer comes with precise reference from original documents
- Complex inquiries: System can process multi-stage, interconnected queries
What distinguishes this solution from generic RAG systems: The integration of company metadata (Knowledge Graph) enables context-aware retrieval. The AI doesn't just know what's in the documents, but also how different information relates.
The Results
80% time and cost savings on compliance inquiries
Break-even after just 2 months through reduced inquiries to experts
Relief for compliance teams to focus on strategic topics
Consistent compliance application across all departments
Traceability for audits through complete source citations
Knowledge Management Reimagined
Not search, but understanding: The solution doesn't just search for keywords but understands the intention behind questions and can explain complex relationships.
Context is king: Through Knowledge Graph integration, the system knows which information is relevant in which context – depending on department, product, or process.
Trust through transparency: Employees don't just get answers but also the reasoning and the exact location in the documents. This creates trust.
What We Learned
- Retrieval is half the battle: Answer quality depends significantly on whether the right information is found. Simple vector search isn't enough.
- Metadata is gold: Integrating company context (structure, processes, products) makes the difference between "works" and "works excellently".
- Experts remain important: The AI doesn't replace compliance experts – it gives them freedom to work where their expertise truly counts.
- Evaluation from the start: We measured how well the system answers from day 1. This was essential for rapid improvement.
This solution is a prime example of Evaluation-Driven and Domain-Driven Development. Not "quickly build a chatbot," but systematically develop a solution that solves real business problems.
