---
title: "LLM Fine Tuning and RAG"
description: "LLM Fine-Tuning and RAG for Regulated Organisations Combine fine-tuned domain models with secure document-based retrieval in one controlled, production-ready system. Contact us Production-ready integrated AI systems Tilde’s LLM fine-tuning and RAG system combines domain-trained models with secure document retrieval for enterprise and regulated organisations – built for domain reasoning, factual accuracy and sovereign EU deployment.  […]"
url: "https://staging.tilde.ai/et/ai-data-services/llm-fine-tuning-and-rag/"
date_modified: "2026-06-18T15:01:18+02:00"
---

# LLM Fine-Tuning and RAG for Regulated Organisations

Combine fine-tuned domain models with secure document-based retrieval in one controlled, production-ready system.

[Contact us](/contact-us/)

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## Production-ready integrated AI systems

Tilde’s LLM fine-tuning and RAG system combines domain-trained models with secure document retrieval for enterprise and regulated organisations – built for domain reasoning, factual accuracy and sovereign EU deployment. 

### Integrated retrieval and reasoning

Train models to work directly with your document retrieval system, using retrieved information according to domain-specific logic.

### Fine-tuned domain intelligence

Fine-tune language models to apply domain terminology, reasoning patterns, and professional standards consistently.

### Focused decision logic

Ensure the system follows structured reasoning logic, using only your organisation’s approved internal sources - minimising misinformation risk and enabling full traceabilty.

### Multimodal fluency

Enable a unified system that can listen (ASR), retrieve knowledge (RAG), and respond (TTS) with precision.

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## Designed for real-world, regulated AI use

### On-premises and sovereign deployment

Deploy the full AI stack on secure EU cloud infrastructure or physical environments, ensuring data residency and compliance.

### Increased accuracy

Achieve higher precision and reliability than standalone RAG or fine-tuning approaches.

### Total data sovereignty

Maintain full control over proprietary data, models, and AI assets across the entire system.

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## Explore our specialised AI Data Service solutions

Explore Tilde’s broader [AI data services](/ai-data-services), including LLM fine-tuning, RAG and secure data preparation for regulated organisations. 

### Managed knowledge-based AI (RAG)

Build AI systems grounded in your verified documents, delivering fact-based answers with citations and no misinformation or unsupported content.

[Learn more](/ai-data-services/managed-knowledge-based-ai-rag/)

### LLM fine-tuning

Train AI models to master your domain terminology, tone, and cultural nuance for professional and regulated environments.

[Learn more](/ai-data-services/llm-fine-tuning/)

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## No Data? We create and prepare it

[Show me how](#elementor-action%3Aaction%3Doff_canvas%3Aopen%26settings%3DeyJpZCI6ImU4MmU3NWEiLCJkaXNwbGF5TW9kZSI6Im9wZW4ifQ%3D%3D)

Data sourcing & collection 				
				
				
				
									For clients with no usable data								
				
				
				
									We acquire and aggregate the raw materials needed to build AI-ready datasets:Sourcing: Ethical extraction of domain-specific data from public and licensed sources following AI Act guidelines and GDPR regulationsDataset Augmentation: Expansion of small datasets into large-scale training corporaSynthetic Data Generation: Creation of high-fidelity artificial data that mimics real-world patterns – ideal for rare edge cases or privacy-sensitive projects (GDPR compliant)								
				
					
				
		
					
				
				
					AI data cleaning & preparation (Human-in-the-Loop)				
				
				
				
									We prepare data so AI models can understand and effectively use it								
				
				
				
									This stage is the foundation of a high-performing model. We handle data preparation while ensuring every data point is verified for accuracy.								
				
				
				
									Data StructuringUnstructured-to-Structured Conversion: Converting scattered PDFs, legacy logs, and emails into machine-ready formatsRemoving Duplicates & Normalisation: Identifying and removing redundant information while standardising units, dates, and terminology								
				
				
				
									Human-Verified Data CleaningAnonymisation: Automated detection of sensitive Personal Identifiable Information (GDPR/HIPAA compliant), followed by a human audit to ensure 100% privacyNoise Reduction & Filtering: Removal of irrelevant or poor data that can lead to model drift or poor performance								
				
				
				
									Data EnrichmentDomain-Specific Metadata Tagging: Adding layers of context (sentiment, intent, entity recognition) using subject-matter expertsMultimodal Synchronisation: Aligning text with images, audio, or video for complex, multi-functional AI modelsEntity Linking & Knowledge Mapping: Ensuring your AI understands relationships between people, places, and brands, eliminating ambiguity in complex datasetsGranular Intent & Emotional Nuance: Capturing the “why” behind the words, through multi-layered intent and subtle sentiment labellingData ValidationData Validation: Auditing datasets for accuracy, consistency, and diversity								
				
					
				
		
					
				
				
					AI data services for professional environments				
				
				
				
									Talk to our team about secure, domain-specific AI solutions built for your organisation								
				
				
				
									
					
						
									Discuss your use case

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## Why organisations choose Tilde

- Strategy first - clear specifications before implementation
- End-to-end delivery - no internal AI team required
- European language expertise - beyond English-centric models
- Data sovereignty - 100% EU-based and on-premises options
- Regulated-sector experience - government, legal, medical, finance

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## Frequently asked questions

What is LLM fine-tuning and RAG? 
							
			
			
		

						
				
				
				
									LLM fine-tuning adapts a language model to your organisation’s terminology, tone and domain knowledge. RAG connects the model to verified documents and retrieves relevant information when answering. Together, they help create domain-specific AI systems that are factually grounded, securely deployed and under full data control. It is part of Tilde’s broader AI data services, including standalone LLM fine-tuning and managed knowledge-based AI (RAG). 								
				
				
					
						
				
					 What is the difference between LLM fine-tuning and RAG? 
							
			
			
		

						
				
				
				
									Fine-tuning trains the model itself on your domain data, terminology and workflows, making it consistently accurate without retrieving information each time. RAG connects a general model to your verified documents and retrieves relevant content at the point of answering. Tilde combines both approaches to deliver domain expertise and factual accuracy in one production-ready system. 								
				
				
					
						
				
					 When should an organisation use LLM fine-tuning and RAG together? 
							
			
			
		

						
				
				
				
									An organisation should combine this integrated approach when it needs both domain expertise and factual accuracy. This is especially suited to legal, government, healthcare, and financial organisations that need controlled, traceable AI outputs.								
				
				
					
						
				
					 Is Tilde’s LLM fine-tuning and RAG solution deployed in the EU? 
							
			
			
		

						
				
				
				
									Yes. Tilde’s integrated AI system is designed for EU-based, private-cloud or on-premises deployment, helping organisations maintain data sovereignty and meet European data residency requirements. 

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### AI data services for professional environments

Talk to our team about secure, domain-specific AI solutions built for your organisation

[Contact us](/contact-us)