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RAG & LLM Integration for Enterprise in Belgium

Unlock your organization's knowledge with AI. We build retrieval-augmented generation systems that connect large language models to your proprietary data.

We design and implement enterprise RAG systems that enable organizations to leverage large language models with their proprietary data while maintaining security and compliance. Our solutions include document processing pipelines, vector databases, and production-grade APIs that integrate seamlessly with existing systems.

Wat we leveren

RAG Architecture & Design

Document Processing Pipeline

Production API & Monitoring

Hoe we werken

1

Use Case Definition & Data Assessment

2

RAG System Implementation

3

Testing & Production Deployment

Technologieën die we gebruiken

OpenAIAnthropic ClaudeLangChainPineconeWeaviatePythonFastAPI
Production RAG systems deployedGDPR-compliant architectureMulti-modal data processing

Veelgestelde vragen

What is RAG and why do we need it?

Retrieval-Augmented Generation (RAG) connects large language models to your proprietary data, enabling AI applications that understand your specific domain knowledge. Without RAG, LLMs only know their training data and cannot access your documents, databases, or internal knowledge.

How do you ensure data security with LLM integration?

We implement multiple security layers: data encryption in transit and at rest, access controls, audit logging, and private deployment options. For sensitive data, we use on-premises or VPC-hosted solutions. All integrations comply with GDPR and Belgian data protection requirements.

What are the costs of running a RAG system?

Costs include LLM API usage, vector database hosting, and compute resources for document processing. A typical enterprise RAG system costs €2,000-10,000 per month depending on usage volume. We optimize costs through caching, batch processing, and efficient model selection.

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