SuperChargeDBSupercharged search for text, documents and images
An object-storage-native, multimodal vector + document search engine. Semantic and hybrid search with instant retrieval — the fast, scalable foundation for RAG, recommendations and enterprise search.
- Instant retrieval
- Vector + hybrid search
- Text, docs & images
- Powers RAG
Why SuperChargeDB
Find the right result — by meaning, not just keywords
ms
Instant retrieval
Nearest-neighbor search that returns the most relevant results in milliseconds.
Multimodal
Text · docs · images
One engine to search across text, documents and images together.
Hybrid
Vector + keyword
Blend semantic vectors with keyword filters for precise, explainable results.
Native
Object-storage backed
Built directly on object storage, so it scales cheaply without heavy infrastructure.
Capabilities
One search engine for all your data
Vector search
Fast approximate nearest-neighbor search over embeddings for semantic relevance that keyword search can’t match.
Document search
Ingest, chunk and index documents, then retrieve the exact passages that answer a query.
Multimodal
Index and search images alongside text — find visually or semantically similar content in one query.
Hybrid ranking
Combine dense vectors with keyword and metadata filters, then rerank for precise, explainable results.
RAG-ready
A drop-in retrieval layer to ground LLMs and AI assistants in your own trusted content.
Object-storage native
Runs directly on object storage for elastic scale and low cost — no bulky database cluster to babysit.
Use cases
Retrieval that powers real products
E-commerce search
Power semantic product discovery and visually-similar recommendations that convert — beyond brittle keyword matching.
Legal & document retrieval
Search across contracts, filings and knowledge bases and jump straight to the most relevant clause or passage.
RAG for AI apps
Ground your chatbots and copilots in trusted content with a fast, reliable retrieval layer that reduces hallucinations.
How it works
From raw data to grounded answers
Step 1
Ingest your data
Point SuperChargeDB at text, documents and images — it chunks, embeds and indexes them into object storage.
Step 2
Embed & index
Content becomes vectors plus keyword and metadata indexes, ready for fast semantic and hybrid retrieval.
Step 3
Query anything
Search by meaning, keyword, image or a blend — with filters and reranking for precise, explainable results.
Step 4
Ground your AI
Feed the retrieved context to your LLMs and assistants for accurate, source-backed answers.
Architecture built for scale and speed
SuperChargeDB runs directly on object storage and the same edge-native foundation ZadeNor uses for production AI — so retrieval stays fast and costs stay low, at any scale.
- Object-storage-native — elastic scale at low cost
- Approximate nearest-neighbor vector search in milliseconds
- Hybrid retrieval — dense vectors + keyword + metadata filters
- Multimodal indexing across text, documents and images
- Edge-native delivery for low-latency retrieval anywhere
Built by ZadeNor AI · the retrieval layer behind smarter apps
FAQ
Questions builders ask first
What is SuperChargeDB?+
SuperChargeDB is ZadeNor AI’s object-storage-native, multimodal vector and document search engine. It performs semantic and hybrid search over text, documents and images with instant retrieval — a fast foundation for RAG, recommendations and enterprise search.
What is hybrid search?+
Hybrid search blends dense vector (semantic) similarity with traditional keyword and metadata filtering, then reranks the results. You get the recall of semantic search and the precision of keyword search in a single query.
Can I use it for RAG?+
Yes. SuperChargeDB is a drop-in retrieval layer for retrieval-augmented generation — it grounds your LLMs and AI assistants in your own trusted content to reduce hallucinations and cite sources.
Does it really search images too?+
Yes. SuperChargeDB is multimodal — it indexes and searches images alongside text and documents, so you can find visually or semantically similar content in one query.
How is it built?+
SuperChargeDB is object-storage-native and runs on the same edge-native foundation ZadeNor uses for production AI — so it scales cheaply and returns results with low latency wherever your users are.
Supercharge your search and RAG today
Give your apps instant, multimodal, meaning-first search — and ground your AI in content you trust.