VECSAI because, this is the way
VecsAI-DB is a minimal, fast vector database for any AI related product.
- Vector database
- Hybrid search
- Personalisation
- Simulation
warm jacket for wet hikes
- Alpine Shell JacketWaterproof · insulated · hiking0.94
- Trailhead Down ParkaWarm · water-resistant0.91
- Ridge 3-in-1 JacketRemovable fleece liner0.88
Filtered: in stockexample
Made for catalogue-driven platforms
Wherever people choose from more items than they can browse, vecsai helps them find the right one, and helps you test what you change.
Product search that understands shoppers, and recommendations that lift basket size.
- Semantic product search. Match descriptions, attributes and intent, with typo tolerance and facets.
- Personal recommendations. Homepage picks, similar products, frequently bought together and cart suggestions.
- Merchandising control. Boost campaigns and new arrivals, bury out-of-stock items, across search and recommendations at once.
wireles hedphones
Showing results for wireless headphones
- Wireless Over-Ear HeadphonesNoise cancelling · 30 h battery
- Sport Wireless EarbudsViewed similar items
- Studio Headphones, BluetoothMatches your brands
Ranked for this shopperexample
One engine, four products
Use the database on its own, or let us run search and recommendations on it for you. Test any change in VecsAI-Simulation.
Built for teams that ship fast
Fast by design
VecsAI-DB is written in Go and built for low-latency queries over large catalogues.
Text, vector and hybrid
Keyword relevance and semantic similarity in a single query, from a single engine.
Personal in real time
Every interaction updates the next result, for search and recommendations alike.
New items from day one
Items are found and recommended from their content before they have any history.
Rules you control
Filter, boost, bury and pin once, and the rules apply to search and recommendations together.
Simple to configure
A schema, an API key and a few requests. Run it in our cloud or on your own servers.
Website
Mobile app
Email & push
VecsAI-SearchSearch as a serviceVecsAI-RecommenderRecommendation engineVecsAI-SimulationTests changes before release
VecsAI-DBFull-text, vector and hybrid search · real-time writes · filtering and facetsSearch and recommendations share the same catalogue, user signals and rules.
See the effect of a change before your users do.
An AI-coordinated simulation engine for OTT, e-commerce and social platforms. Test ranking, recommendation and catalogue changes on simulated users before release.
- An AI agent coordinates every simulation
- Built for OTT, e-commerce and social media
- Compare current and proposed versions side by side
- Works with vecsai or with your existing system
Example report · 50,000 simulated viewers · 30 days
GoWritten for low-latency queries
HybridText and vector search in one query
Real timeSignals applied per interaction
Cloud or yoursManaged, or on your own servers
See vecsai on your own catalogue
Tell us about your platform and we will show you search, recommendations and simulation running on your data.