Semantic Search Implementation for Your Business
Vector database implementation services convert your product or customer catalogue into embeddings so search understands meaning, not just keywords. Omeiro loads catalogues into Pinecone or Weaviate and builds semantic search, similar-product recommendations and customer clusters.
What semantic search implementation looks at
The main areas we work through. The exact scope depends on your package and is agreed before we start.
Sources
- Which systems feed it
- How often
- Who owns access
Pipelines
- Loads and schedules
- Retries and alerts
- Logs
Models
- Clean tables
- Clear names
- Tests on key fields
Docs
- What each table means
- How to add sources
- Runbook
What we cover The exact scope depends on your package and your data, and is agreed before work starts.
What you get with semantic search implementation
Vectorizing customer and product catalogs. Pinecone and Weaviate embeddings enabling semantic product search, cross-sell recommendations, and personalized clustering.
Basic Package
Embed 1 catalog (up to 10,000 items) into Pinecone or Weaviate, search demo. 3-day delivery, 2 revisions.
Standard Package
100,000 items, semantic search API, similar-product recommendations; docs. 6-day delivery, 2 revisions.
Premium Package
Auto re-indexing pipeline, customer clustering, relevance tuning; 30 days support. 10-day delivery, 2 revisions.
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.
Your data stays in your own accounts and tools wherever possible, and access is removed when the work is done.
How our semantic search implementation works
Prepare the catalogue
Titles, descriptions and attributes are cleaned.
Embed and index
Items are converted to vectors and stored.
Expose search
A demo or API returns the nearest matches.
Tune relevance
Results are checked and adjusted on higher tiers.
Vector database implementation: preparing your catalog
Vector database implementation starts with deciding what you are embedding and why. Product titles and descriptions suit semantic search, while support articles suit question answering. Share a catalog export with IDs, text fields and any attributes used for filtering, such as category or price. Tell us how often the data changes, since a catalog that updates hourly needs a different indexing plan than one updated monthly.
A common mistake is embedding messy text, such as titles stuffed with keywords, and then blaming the database for poor results. Vector database implementation here cleans the text, picks an embedding model suited to your language and domain, and tests search with real queries. Metadata filters let shoppers narrow by size or price. Results are evaluated, not just demoed, and relevance tuning is included on the top tier.
In short
- Delivery in 3 to 10 days, by package.
- Fixed price, shown before you order.
- Developers needing pinecone consulting for a first index.
- Copyright yours after full payment.
Semantic Search Implementation: common questions
How much does semantic search implementation cost?
Prices are fixed and shown by package on our Semantic Search Implementation pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does Pinecone consulting take?
Delivery depends on the package: Basic 3-day delivery; Standard 6-day delivery; Premium 10-day delivery.
What is included in the Basic Package?
The Basic Package includes: Embed 1 catalog (up to 10,000 items) into Pinecone or Weaviate, search demo. Higher packages add more scope, revisions and support.
Can I get a custom weaviate development 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.
Pinecone or Weaviate?
Pinecone is fully managed, while Weaviate offers open-source flexibility. Basic supports either.
What is semantic search?
Search that matches meaning, so related items appear even without the same words.
Does the index stay current?
Premium includes an automatic re-indexing pipeline.
Will it replace my existing search?
It can sit alongside it. We discuss integration when you order.
What is an embedding?
An embedding is a list of numbers that represents the meaning of a piece of text or an image. Items with similar meaning end up close together, which is what makes semantic search possible.
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 semantic search implementation?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.