Spark Vault
Executive Summary
Spark Vault is a private, on-premises enterprise search solution purpose-built for sensitive medical and healthcare documents. Running entirely on NVIDIA DGX Spark, it enables organizations to search, analyze, and extract insights from complex medical records without relying on external cloud services. By combining containerized large language models, semantic embeddings, vector and graph databases, and local inference, Spark Vault delivers fast, secure, and compliance-ready search at enterprise scale.
Challenges
Solution Overview
Spark Vault addresses these challenges with a fully on-premises, containerized AI search architecture optimized for performance, privacy, and scalability: Runs entirely on NVIDIA DGX Spark with zero cloud dependency Uses local LLM inference, embeddings, and vision-language parsing Combines semantic vector search, fuzzy keyword search, and graph-based querying Maintains full data sovereignty while delivering sub-second search performance This architecture ensures sensitive medical data never leaves the organization’s infrastructure.
How it Works
Functional Workflow
1. Intelligent Document Ingestion
Medical documents are ingested locally and parsed using a vision-language model with semantic chunking.
2.Semantic Chunking & Extraction
Documents are broken into meaningful chunks using domain-aware parsing for accurate retrieval.
3.Embedding Generation
Each chunk is converted into vector embeddings for semantic similarity search.
4.Knowledge Graph Construction
Clinical entities and relationships are modeled into a graph structure for contextual querying.
5.Hybrid Search Execution
- User queries leverage:
- Semantic vector similarity
- Fuzzy keyword matching
- Graph-based relationship queries
6.Instant Insight Delivery
Results are enhanced with LLM-powered contextual insights, all generated locally.
Business Impact
- Private Search by Design Sensitive medical data remains fully on-premises at all times.
- Sub-Second Query Latency Fast and reliable search across large document repositories.
- Improved Clinical & Operational Efficiency Faster access to relevant information supports better decision-making.
- Reduced Compliance Risk Eliminates cloud exposure and simplifies regulatory audits.
- Scalable for Enterprise Growth Handles increasing data volumes without performance degradation.
Key Benefits
Key Outcomes with Spark Vault
Private Search
Sensitive medical data stays fully on-premises at all times
Low Latency
Sub-second query responses across large document collections
Hybrid Intelligence
Semantic, keyword, and graph search combined in a single query flow
Deep Understanding
Vision-language parsing enables accurate insight from complex medical documents
Enterprise Ready
Containerized, scalable architecture built for secure production deployment
Technical Foundation
Hardware
NVIDIA DGX Spark
LLM Inference
LLaMA 3.3 70B via vLLM
Embeddings
Nomic embed model
Database
PostgreSQL with pgvector and Apache AGE
Document Intelligence
Vision-language parsing + semantic chunking (Chonkie)
Deployment
NVIDIA NGC containers, Docker-based runtime
Search Paradigm
Hybrid semantic, keyword, and graph search
Conclusion
Spark Vault demonstrates a sophisticated enterprise search system that harnesses containerized AI models, advanced vector and graph databases, and high-performance NVIDIA DGX Spark hardware to deliver secure, private, and highly responsive search capabilities. Its hybrid semantic and graph querying uniquely position it as a best-in-class, on-premises solution for medical and sensitive data environments.
