LLM Synthetic Data Generation Services for Your Business
Synthetic data generation for LLM training produces instruction and answer pairs when you do not have enough real examples. Omeiro generates the pairs, removes duplicates, scores their variety, filters toxic content and uses a judge model to grade quality.
How LLM synthetic data generation works, step by step
A made-up example of one run, from start to finish. Each step is logged so you can see what happened.
- A brief comes in
From a form, sheet or chat.
- A first draft is made
Using your tone guide and examples.
- Checks run
Length, words to avoid and required details.
- A person approves
Nothing goes out without your OK.
Sample Made-up names, data and steps to show how a run is logged. Your steps, tools and rules follow your business.
What you get with LLM synthetic data generation
High-quality synthetic instruction dataset generation. De-duplication, semantic diversity scoring, toxicity filtering, and automated LLM-as-a-judge quality validation.
Basic Package
1,000 synthetic instruction pairs, dedupe; quality filter. 4-day delivery, 1 round + 30-day fixes.
Standard Package
5,000 pairs, diversity scoring, toxicity filter, LLM-judge scores. 8-day delivery, 1 round + 30-day fixes.
Premium Package
20,000 pairs, multi-task mix, human spot-check report, 30 days support. 12-day delivery, 1 round + 60-day fixes.
Clear brief first
We confirm what you need before work starts, so the scope is clear on both sides.
Revisions listed
Each package shows its revision rounds. A round is one list of changes sent together.
Yours once paid
Copyright of the final work passes to you once the order is paid in full.
Third-party tools, API usage and hosting are billed to your own accounts, so the setup stays with your business.
How our LLM synthetic data generation works
Define the tasks
We write what the model should learn.
Generate
Pairs are produced from seed examples.
Clean
Duplicates, weak and toxic pairs are removed.
Check
Judge scores and, on Premium, human spot checks confirm quality.
Synthetic data generation for LLM training: avoiding common traps
Synthetic data copies whatever the generator believes, including its errors. Synthetic data generation for LLM training therefore needs seed examples that reflect your real tasks, written or approved by people who know the domain, and clear rules on style and difficulty. Before ordering, supply a small set of gold examples and list typical edge cases. Without seeds, generators drift towards generic, repetitive pairs that teach a model very little.
Variety and leakage deserve attention. Near-duplicate pairs inflate counts without adding learning, which is why deduplication and diversity scoring exist, and test questions must never appear in the training set. Synthetic data generation for LLM training also raises licensing questions, since the generating model's terms may limit using outputs to train other models. Check those terms, keep a record of how each batch was produced, and hold out real examples for the final evaluation.
In short
- Delivery in 4 to 12 days, by package.
- Fixed price, shown before you order.
- Teams about to fine-tune with only a few hundred examples.
- Copyright yours after full payment.
LLM Synthetic Data Generation: common questions
How much does LLM synthetic data generation cost?
Prices are fixed and shown by package on our LLM Synthetic Data Generation pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does LLM training dataset creation take?
Delivery depends on the package: Basic 4-day delivery; Standard 8-day delivery; Premium 12-day delivery.
What is included in the Basic Package?
The Basic Package includes: 1,000 synthetic instruction pairs, dedupe; quality filter. Higher packages add more scope, revisions and support.
Can I get a custom instruction dataset curation package?
Yes. If none of the packages fits, use the custom package form on our pricing page to describe what you need, and our team sends you a fixed price.
Is synthetic data as good as real data?
It helps with coverage, but quality varies, which is why filters and spot checks matter.
Can I use it to train any model?
Check the generating model's terms of use.
How do you measure variety?
Standard adds diversity scoring.
Do humans review it?
Premium includes a human spot-check report.
How many training examples do I need for fine-tuning?
It depends on the task, and a few thousand clean, varied examples are often enough for narrow behaviour changes. Quality and diversity matter more than raw count.
Who owns the final work?
Copyright of the final work passes to you once the order is paid in full. Paid fonts, stock files or licences, if used, are licensed in your name.
Ready to start your LLM synthetic data generation?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.