Portfolio & Case Studies

LLM Fine-Tuning Portfolio & Private LLM Case Studies for European Companies

This LLM fine-tuning portfolio shows real private LLM case studies from European projects: German legal review, multilingual customer support, and public sector document AI. Each example focuses on GDPR-safe deployments, concrete metrics and how a private LLM portfolio in Europe actually performs in production.

German legal & compliance Multilingual customer support (DE / EN / BG / RO) Public sector document AI Hosted fully inside the EU
Selected projects: LLM fine-tuning portfolio, private LLM case studies, German legal LLM deployment, multilingual customer support bot results, GDPR-safe LLM demos.

What This Page Shows

  • 3 concrete private LLM case studies across German legal, multilingual support and public sector document AI.
  • Before/after benchmarks that compare base models with your fine-tuned, GDPR-safe private LLMs.
  • Planned live demos on Hugging Face so prospects can safely test behaviour before a sales or scoping call.
Fine-Tuned Models
3
German legal, multilingual support, public sector document AI.
European Verticals
4
Legal, support, medical, fintech – built for EU rules.
Languages
5+
German, English, Bulgarian, Romanian, French (extendable).
Hosting
EU
Hosted in EU data centres or fully on-premise inside your own infrastructure.
Overview of private LLM and GDPR-compliant AI services by AI Tuning
Visual overview of AI Tuning private LLM and GDPR-compliant AI services for European companies.

Selected Private LLM Case Studies

These examples reflect the type of projects AI Tuning focuses on: regulated environments, multilingual European users and organisations that cannot send sensitive data to generic US-based APIs. Each private LLM case study is part of a broader private LLM portfolio in Europe that can be adapted to your sector.

Legal & Compliance · Germany

German Legal Contract Reviewer

Model: Mistral / Nemo-class 12B · Domain: German contracts · Mode: Private / GDPR-safe
  • Fine-tuned on anonymised German commercial contracts and internal clause libraries.
  • Assists legal teams with clause extraction, classification and risk flagging.
  • Understands your internal playbook instead of generic “English law” assumptions.
Customer Support · DACH + CEE

Multilingual Support Bot (DE / EN / BG)

Model: Qwen 2.5 14B · Channels: chat + email · Hosting: EU data centre
  • Trained on historical tickets, macros and help articles from a SaaS support team.
  • Handles FAQs and low-risk requests in German, English and Bulgarian with brand-consistent tone.
  • Works as agent co-pilot inside the ticketing system instead of replacing humans.
Public Sector · Bulgaria

Public Sector Document Summarisation (BG)

Model: Llama 3.1 8B · Domain: regulations & tenders · Mode: on-premise
  • Fine-tuned on Bulgarian-language regulations, public tenders and internal guidance.
  • Helps staff summarise long documents and extract key obligations and deadlines.
  • Runs on-premise inside a controlled environment with full access logging.

Before / After Fine-Tuning – Example Benchmarks

The exact numbers depend on your data and evaluation setup, but the pattern is the same: general-purpose models are decent, and fine-tuned private models are much better on your specific tasks. These example LLM fine tuning benchmarks illustrate the kind of uplift you can expect when you move to a private, domain-specific model.

Example comparison: base instruction model vs. private fine-tune on real-world European tasks.
Use Case / Task Metric Base Model Private Fine-Tune Gain
German contract clause extraction (legal) F1 on key clause detection ≈ 0.68 ≈ 0.79 +11 points
Multilingual support reply suggestions (DE / EN) Agent acceptance rate ~ 55% ~ 82% +27 pp
Bulgarian public sector doc summaries Human preference vs. baseline Preferred in ~40% of comparisons Preferred in ~78% of comparisons +38 pp

Benchmarks are illustrative of the type of improvements private fine-tunes can deliver. For each real project, AI Tuning defines an evaluation plan with you and reports concrete metrics, not just “AI magic” – so your private LLM case studies are backed by numbers.

All deployments are hosted on EU-only infrastructure – for example EU regions of providers like Hetzner, Scaleway or OVHcloud – or fully on-premise in your own data centre, so your GDPR-safe LLM demos never leave Europe.

Live Demos on Hugging Face (Coming Soon)

Your plan is to host public versions of your key models and simple chat experiences as GDPR-safe LLM demos on Hugging Face – so prospects can try the behaviour before a sales call. This section is ready for those links; for now it clearly explains what each demo will show.

German Legal Contract Demo

Try a safe version of the German contract reviewer: upload or paste sample clauses and see how the model extracts and explains them, similar to the German legal LLM case study above.

Live Demo (Hugging Face) Replace # with your actual Space URL once it’s live.

Multilingual Support Bot Demo

Test the support co-pilot in German and English: ask typical SaaS questions and compare the answers with a generic model – a live multilingual customer support bot benchmark.

Live Demo (Hugging Face) Great to link from the Customer Support Bots vertical page.

Bulgarian Document Summariser

Paste a Bulgarian public sector text and get a short summary plus extracted key points: obligations, dates, entities mentioned – matching the public sector case study.

Live Demo (Hugging Face) You can reuse the same underlying model from the public sector project.

How We Turn Your Data into a Private LLM

The projects in this LLM fine-tuning portfolio follow the same core process: we start from a small, well-defined use case, prove value quickly and then scale to more departments or languages. Every step is documented so that IT, legal and management stay on board.

1

Use Case & Data Workshop

We map a single high-value use case (legal review, support, public sector) and list data sources, constraints and success metrics.

2

Fixed-Price Proposal

You receive a written scope with a fixed project price, timeline and evaluation plan – easy to show to your leadership and legal.

3

Fine-Tuning & Internal Testing

We fine-tune the model, run internal tests and let your domain experts try it in a safe staging environment before anything goes live.

4

Deployment & Next Steps

We support deployment (EU cloud or on-prem) and plan the next wave of use cases once the first one proves its value.

Short, practical articles on legal AI, support copilots and training data libraries for GDPR-compliant private LLMs.

Next Step · From Portfolio to Your Own Project

Ready to Add Your Own Project to This LLM Portfolio?

If these private LLM case studies match what you want – German legal, multilingual support, public sector or fintech – the next step is simple: a short 15-minute call to map your use case, your data and your internal constraints. Within 24 hours you get a fixed-price proposal you can share with your team.

Typical timeline: 10–21 days from first call to private LLM EU-only infrastructure · No US data transfer