Embedding Model Fine-Tuning Services for Your Business
Embedding model fine tuning services teach a search model the language of your field, so a query for one internal term finds documents that use its synonyms and abbreviations. Omeiro fine-tunes dense models such as BGE or Voyage on pairs drawn from your own corpus.
How embedding model fine tuning 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.
- Your documents are loaded
Files are split, indexed and kept in your own storage.
- A question comes in
The system finds the parts of your documents that match.
- The model answers from them
Answers point back to the source so people can check.
- People review the edge cases
We agree what happens when no good answer is found.
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 embedding model fine tuning
Fine-tuning dense embedding models (BGE, Voyage) on proprietary company corpora. Boosting retrieval accuracy in niche industries with bespoke vocabulary and technical jargon.
Basic Package
Fine-tune 1 embedding model on up to 5k text pairs. 5-day delivery, 1 round + 30-day fixes.
Standard Package
Pair generation from your corpus, 20k pairs, retrieval benchmark. 9-day delivery, 1 round + 30-day fixes.
Premium Package
Hard-negative mining, re-index of your vector DB, hosting, 30 days support. 14-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 embedding model fine tuning works
Measure the baseline
We score the base model on questions your users really ask.
Prepare pairs
Matching queries and passages are collected or generated from your documents.
Train
The model is fine-tuned and checked against held-out examples.
Compare and deliver
Benchmarks show the change, and higher tiers re-index your data.
Embedding model fine tuning: preparing data that teaches the model
Training pairs are the product. Embedding model fine tuning learns from examples of a query matched with a passage that answers it, so quality beats quantity. The best pairs come from real user searches, support tickets or documented questions, not from text invented in isolation. Before ordering, collect sample queries, note terms staff use differently from the documents, and gather a list of acronyms and abbreviations. These show where a general model confuses meanings.
Measure first and keep a test set aside. Embedding model fine tuning can overfit to its own pairs, so some questions must remain unseen and be used only for scoring. Because new embeddings change every vector, your database has to be re-indexed afterwards, and that step needs planning around downtime. Tell us the size of your corpus and which vector store you use, so the re-index and any hosting are scoped realistically.
In short
- Delivery in 5 to 14 days, by package.
- Fixed price, shown before you order.
- Copyright yours after full payment.
Embedding Model Fine Tuning: common questions
How much does embedding model fine tuning cost?
Prices are fixed and shown by package on our Embedding Model Fine Tuning pricing page, so you see the full price before you order. You can also ask for a custom quote.
How much does embedding model fine tuning cost?
Prices are fixed and shown by package on our Embedding Model Fine Tuning pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does custom embeddings development take?
Delivery depends on the package: Basic 5-day delivery; Standard 9-day delivery; Premium 14-day delivery.
What is included in the Basic Package?
The Basic Package includes: Fine-tune 1 embedding model on up to 5k text pairs. Higher packages add more scope, revisions and support.
Can I get a custom domain specific embedding model 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.
Should I fine tune embeddings for search or use a better base model?
Try a stronger base model first. Fine-tuning pays off when your vocabulary is unusual.
Will I need to re-index?
Yes, after embeddings change. Premium handles the re-index.
Can the model be hosted?
Premium includes hosting.
What is a domain specific embedding model?
It is an embedding model adapted to the vocabulary of one field, such as law, medicine or engineering. It places related technical terms closer together than a general model would.
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 embedding model fine tuning?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.