Did you know? You can now use the
{!hybrid} parser — a custom Opensolr Solr query parser that gives you better hybrid search: correct keyword + vector fusion, real search modes, and natural-language, cross-lingual queries out of the box. Learn more →Live Search Demo
Hybrid Search in Action
Keyword matching + semantic understanding, working together. Click any query below to run it live — no sign-up needed.
How It Works
Keyword Layer
Finds docs with matching terms — fast, precise, field-weighted
Semantic Layer
Finds docs by meaning — works even with zero lexical overlap
Score Fusion
Solr's {!bool} adds scores — tunable via union, must, should modes
Zero Config
Automatic on all vector-enabled indexes — no query changes needed
Four Indexes, Four Domains
Each index below is a real, live Opensolr instance. Every query was chosen to demonstrate semantic understanding — words in the query often do not appear in the top-ranked documents.
Opensolr Docs
Technical knowledge base
Fluke
Test & measurement equipment
Dedeman
Home & DIY retail (RO)
Starbucks at Home
Specialty coffee products
Opensolr Knowledge Base
150k+ documentation pages · English · Tech/SaaS domain
Query
"pricing plans and costs"
Surfaces the pricing page and plan comparison docs — semantic layer understands "costs" maps to "pricing" context.
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Query
"crawl and index my website automatically"
Reaches Web Crawler feature docs — semantic understands "crawl automatically" as an intent for automated ingestion pipelines.
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Query
"my search results are not relevant enough"
Finds relevance tuning and field weight documentation — the semantic layer catches the intent behind a user complaint phrasing.
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Fluke Test & Measurement
150k+ product & support pages · English (locale=en_us) · Industrial domain
Semantic challenge: These queries are written in natural conversational language — they contain no part numbers, product names, or catalog terms. Pure semantic understanding required.
Query
"how do I check current without touching wires"
Finds clamp meters and non-contact current probes — the product category name never appears in the query, yet vector search retrieves exactly the right tools.
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Query
"see heat through walls"
Returns thermal imaging cameras — the query contains zero product terminology. "See heat through walls" is pure human intent, correctly mapped to infrared thermography.
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Query
"electrical safety inspection building"
Surfaces insulation resistance testers, installation testers, and safety guides — semantic layer understands the professional context of a building electrical inspector.
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Dedeman Home & DIY
350k+ products · Romanian & English queries · Home improvement & retail domain
Cross-language semantic: These queries mix Romanian descriptive intent with English category names. multilingual E5's multilingual embeddings handle both fluently.
Query (Romanian)
"loc unde sa stai confortabil"
"a place to sit comfortably in the living room"
Returns sofas, armchairs, and sectional couches — the words "canapea" or "fotoliu" (sofa/armchair) never appear in the query.
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Query (English)
"canvas artwork for bedroom wall"
Surfaces wall paintings and decorative prints listed in Romanian — cross-language semantic matching at work, bridging English intent to Romanian product catalog.
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Query (Romanian)
"recipiente pentru plante"
"recipients for plants"
Returns flower pots, planters, and garden containers — "recipiente" (containers) is a generic word that never appears in product titles, yet semantic search correctly maps it to ghivece and jardiniere.
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Starbucks at Home
400+ specialty coffee & beverage products · English · CPG domain
Dense catalog, small index: With only ~400 products, this demo shows how semantic search extracts relevant results even when keyword overlap is minimal or zero.
Query
"cozy winter hot chocolate"
Returns hot cocoa mixes and warming winter drinks — vector embeddings understand "cozy winter" as a seasonal mood context that maps perfectly to comfort beverage products.
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Query
"morning pick me up caffeine boost"
Surfaces dark roast espresso pods and high-caffeine blends — semantic model understands "pick me up" as an energy/alertness intent, not a product descriptor.
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Query
"sustainable farming environmental impact"
Finds ethically sourced and Rainforest Alliance certified coffees — no single query word appears in the product titles, yet vector search pinpoints environmentally responsible products.
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Ready to add hybrid search to your index?
One flip. Instant semantic search.
Enable vector embeddings on any Opensolr index and hybrid search activates automatically. No query changes, no schema redesign — your existing data starts working smarter.
Custom Plans Available
This is a premium feature available on custom plans tailored to your needs and budget. For small websites, we can even provide these features for free after validating your use case. Contact us at support@opensolr.com to discuss your requirements.