---
title: "LLM Fine-Tuning Services | Custom Models on Your Data | Agility"
url: https://agilitytech.ai/llm-fine-tuning-services
description: "LLM fine-tuning when it actually helps: consistent formats, domain language and smaller, cheaper models, measured against a proper evaluation set."
publisher: Agility (agilitytech.ai)
---

Service · Fine-tuning

# LLM fine-tuning services

Fine-tuning is the right tool less often than people expect. It helps when you need a model to follow a format every time, use your domain language, or match a big model's quality with a smaller, cheaper one.

- Senior engineers on every project
- Evaluation before launch, not after
- You own the code and the models

48-hour turnaround · free · no obligation

### Talk to us about LLM fine-tuning

Tell us what you want to build. A senior engineer sends back a scope and a fixed price within two business days, no obligation.

In short

## The quick answer

It does not help a model know facts that change, which is what retrieval is for. We start by checking which problem you actually have.

What we build

## What we build with LLM fine-tuning

### Format and style consistency

Models that return the exact structure, tone or classification scheme you need without long, fragile prompts.

### Smaller models that hold their own

Fine-tuned open models such as Llama or Mistral that handle a narrow task well enough to replace an expensive general model.

### Domain language

Models that understand your industry's abbreviations and jargon, trained on examples you already have.

### Private training

LoRA and full fine-tunes run on your infrastructure when training data is sensitive.

Fit

## Is LLM fine-tuning the right choice?

### When it is a good fit

- A large prompt is getting long, slow and still inconsistent.
- You have hundreds or thousands of good input and output examples.
- You want to run a smaller model on your own hardware.

### When we would suggest something else

- The model needs facts that change weekly. Use RAG.
- You have no labelled examples yet. Start by collecting them.

Process

## How a project usually runs

- 01 ### Baseline first We measure what prompting and retrieval achieve on your task before training anything.
- 02 ### Prepare data Clean, de-duplicate and split the examples, keeping a held-out set the model never sees.
- 03 ### Train and compare Usually LoRA on an open model, compared against the baseline on accuracy, speed and cost.
- 04 ### Deploy and monitor Serving set up on your cloud or hardware, with drift checks so you know when to retrain.

Pitfalls

## What usually goes wrong

We have seen these enough times to plan around them from the start.

- Fine-tuning to add knowledge, which mostly does not work.
- Evaluating on the training data and calling it a success.
- Forgetting that a fine-tuned model has to be maintained and retrained.

Next step

Want to see similar work? Browse our [case studies](https://agilitytech.ai/case-studies) or [tell us what you are working on](https://agilitytech.ai/contact).

FAQ

## LLM fine-tuning: common questions

[Ask us something else](https://agilitytech.ai/contact)

**How much data do we need to fine-tune?+**

For narrow format or classification tasks, a few hundred to a few thousand good examples is often enough to see a difference. Quality matters more than volume.

**Can you fine-tune GPT or Claude?+**

OpenAI offers fine-tuning on some of its models, and we use it when it fits. More often we fine-tune open models, which you can then host and own.

**Is fine-tuning better than RAG?+**

They solve different problems. RAG supplies facts. Fine-tuning shapes behaviour. Many good systems use RAG with an untuned model.

**Who owns the fine-tuned model?+**

You do. Weights, training data and scripts are handed over.

Keep reading

## Related pricing and decision guides

[RAG development services](https://agilitytech.ai/rag-development-services)[Hire MLOps engineers](https://agilitytech.ai/hire-mlops-engineers)[Hire AI developers](https://agilitytech.ai/hire-ai-developers)[AI agent development](https://agilitytech.ai/ai-agent-development)[LLM development services](https://agilitytech.ai/llm-development-services)

## Get your exact number with a free 48-hour audit

Indicative ranges only get you so far. Tell us the specifics and get a scope and a fixed price in two business days.

Get my fixed estimate