Enterprise Hybrid RAG SDK with table-aware extraction, conversation state, and multi-cloud deployment
Project description
VRIN Hybrid RAG SDK v0.4.0
Enterprise-grade Hybrid RAG system with hybrid cloud architecture, user-defined AI specialization, multi-hop reasoning, and blazing-fast performance optimization.
๐๏ธ Hybrid Cloud Architecture
VRIN supports two deployment models:
- General Users (
vrin_API keys): Cost-effective shared infrastructure - Enterprise Users (
vrin_ent_API keys): 100% private infrastructure with data sovereignty
๐ก๏ธ Data Sovereignty Guarantee: Enterprise customer data NEVER leaves their cloud account
๐ New in v0.4.0 - Hybrid Cloud & Performance Breakthrough
- ๐๏ธ HYBRID CLOUD COMPLETE - Enterprise private infrastructure with data sovereignty
- ๐ API Key Routing -
vrin_shared vsvrin_ent_private infrastructure - โ๏ธ Azure Integration - CosmosDB with Gremlin API for enterprise customers
- ๐ข Enterprise Portal - Organization, user, and API key management
- โก Performance Revolution - Raw fact retrieval in <2s (96.3% faster than full analysis)
- ๐ Dual-Speed Processing - Fast website display + comprehensive expert analysis
- ๐ง User-Defined Specialization - Create custom AI experts for any domain
- ๐ Multi-Hop Reasoning - Cross-document synthesis with reasoning chains
- ๐ Enhanced Graph Retrieval - Fixed Neptune storage, now finding 36-50 facts vs 0
- ๐ฏ Expert-Level Performance - 8.5/10 validation against professional analysis
- ๐๏ธ Production Infrastructure - 7 Lambda functions optimized (Python 3.12)
- ๐พ Smart Storage - 40-60% reduction through intelligent deduplication
- ๐ Enterprise Security - Bearer token auth, user isolation, compliance ready
๐ Core Features
- ๐๏ธ Hybrid Cloud Architecture - Customer choice of infrastructure (shared vs private)
- ๐ก๏ธ Data Sovereignty - Enterprise data stays in customer cloud account
- โก Hybrid RAG Architecture - Graph reasoning + Vector similarity search
- ๐ง User-Defined AI Experts - Customize reasoning for any domain
- ๐ Multi-Hop Reasoning - Cross-document synthesis and pattern detection
- ๐ Advanced Fact Extraction - High-confidence structured knowledge extraction
- ๐ Expert-Level Analysis - Professional-grade insights with reasoning chains
- ๐ข Enterprise Portal - Complete organization and user management
- ๐ Enterprise-Ready - User isolation, authentication, and production scaling
๐ฆ Installation
pip install vrin==0.4.0
๐ง Quick Start
from vrin import VRINClient
# For general users (shared infrastructure)
client = VRINClient(api_key="vrin_your_api_key")
# For enterprise users (private infrastructure with data sovereignty)
from vrin import VRINEnterpriseClient
enterprise_client = VRINEnterpriseClient(api_key="vrin_ent_your_enterprise_key")
# STEP 1: Define your custom AI expert
result = client.specialize(
custom_prompt="You are a senior M&A legal partner with 25+ years experience...",
reasoning_focus=["cross_document_synthesis", "causal_chains"],
analysis_depth="expert"
)
# STEP 2: Insert knowledge with automatic fact extraction
result = client.insert(
content="Complex M&A legal document content...",
title="Strategic M&A Assessment"
)
print(f"โ
Extracted {result['facts_count']} facts")
print(f"๐พ Storage: {result['storage_details']}")
# STEP 3A: Fast fact retrieval for website display (NEW v0.4.0)
raw_response = client.get_raw_facts_only("What are strategic insights?")
print(f"โก Lightning-fast retrieval: {raw_response['search_time']}") # ~0.7-2s
print(f"๐ Facts found: {raw_response['total_facts']}")
# STEP 3B: Complete expert analysis for comprehensive reports
response = client.query("What are the strategic litigation opportunities?")
print(f"๐ Expert Analysis: {response['summary']}")
print(f"๐ Multi-hop Chains: {response['multi_hop_chains']}")
print(f"๐ Cross-doc Patterns: {response['cross_document_patterns']}")
print(f"โก Full Analysis: {response['search_time']}") # ~15-20s
๐ Performance & Validation (v0.4.0)
Production Performance
- โก Raw Fact Retrieval: 0.7-2s (96.3% faster than full analysis)
- ๐ง Expert Analysis: 15-20s for comprehensive multi-hop reasoning
- ๐ Graph Retrieval: Now finding 36-50 facts (fixed from 0 facts)
- ๐ Multi-hop Reasoning: 1-10 reasoning chains per complex query
- ๐ Cross-document Patterns: 2+ patterns detected per expert analysis
- ๐พ Storage Efficiency: 40-60% reduction through intelligent deduplication
- ๐ฏ Expert Validation: 8.5/10 performance on professional M&A analysis
- ๐๏ธ Infrastructure: 7 Lambda functions optimized (Python 3.12), sub-second API response
Benchmark Validation (September 2025)
VRIN v0.4.0 validated against industry-standard RAG benchmarks:
| Benchmark | Accuracy | Validation |
|---|---|---|
| RGB (Noise Robustness) | 97.9% โ | Core retrieval architecture validated |
| FRAMES (Multi-hop) | 28.6% | Multi-constraint reasoning challenges identified |
| BEIR SciFact | 22.2% | Scientific claim verification |
| RAGBench FinQA | 11.1% | Table interpretation enhancement in progress |
Key Finding: RGB benchmark (97.9% with 60% noise) validates VRIN's core hybrid retrieval is sound. Enhancement underway for structured data (tables).
See: docs/BENCHMARK_TESTING_RESULTS.md for comprehensive analysis
๐๏ธ Hybrid Cloud Architecture
VRIN uses enterprise-grade Hybrid RAG with hybrid cloud architecture:
๐ API Key Routing
vrin_keys โ VRIN shared infrastructure (cost-effective)vrin_ent_keys โ Customer private infrastructure (data sovereignty)
๐ Database Support
- Neptune (AWS) - For general users and AWS enterprise deployments
- CosmosDB (Azure) - For Azure enterprise deployments with Gremlin API
- Automatic routing based on API key type and enterprise configuration
๐ข Enterprise Portal
- Organization and user management
- API key provisioning and management
- Infrastructure configuration (Azure/AWS)
- Usage monitoring and analytics
๐๏ธ System Flow
- API Key Authentication - Routes to appropriate infrastructure
- User Specialization - Custom AI experts defined by users
- Enhanced Fact Extraction - Multi-cloud database storage
- Multi-hop Reasoning - Cross-document synthesis with reasoning chains
- Hybrid Retrieval - Graph traversal + vector similarity (36-50 facts)
- Expert Synthesis - Domain-specific analysis using custom prompts
- Production Infrastructure - 11 Lambda functions with hybrid routing
- Enterprise Security - Bearer token auth, user isolation, compliance
๐ Authentication & Setup
General Users (Shared Infrastructure)
- Sign up at VRIN Console
- Get your
vrin_API key from account dashboard - Use the API key to initialize your client
client = VRINClient(api_key="vrin_your_api_key_here")
Enterprise Users (Private Infrastructure)
- Contact VRIN Enterprise Sales for onboarding
- Deploy VRIN infrastructure in your Azure/AWS account
- Get your
vrin_ent_API key from enterprise portal - Configure your infrastructure via enterprise portal
enterprise_client = VRINEnterpriseClient(api_key="vrin_ent_your_enterprise_key")
๐ข Production Ready Features
๐ Hybrid Cloud
- Data Sovereignty: Enterprise data never leaves customer infrastructure
- Multi-Cloud Support: AWS Neptune and Azure CosmosDB
- Intelligent Routing: Automatic infrastructure routing by API key type
- Enterprise Portal: Complete organization and user management
๐ง AI Capabilities
- Custom AI Experts: Define domain-specific reasoning for any field
- Multi-hop Analysis: Cross-document synthesis with evidence chains
- Working Graph Facts: Fixed Neptune/CosmosDB storage now retrieving real relationships
- Expert Validation: 8.5/10 performance against professional analysis
๐๏ธ Infrastructure
- Production APIs: Bearer token auth, 99.5% uptime, enterprise ready
- Smart Deduplication: 40-60% storage optimization with transparency
- Hybrid Database: Seamless Neptune/CosmosDB routing
- Enterprise Security: VPC isolation, private endpoints, compliance ready
๐ฏ Use Cases
- Legal Analysis: M&A risk assessment, contract review, litigation strategy
- Financial Research: Investment analysis, market research, due diligence
- Technical Documentation: API analysis, architecture review, compliance
- Strategic Planning: Competitive analysis, market intelligence, decision support
๐ What Makes VRIN Different
vs. Basic RAG Systems
- โ Multi-hop reasoning across knowledge graphs
- โ User-defined specialization instead of rigid templates
- โ Cross-document synthesis with pattern detection
- โ Expert-level performance validated against professionals
vs. Enterprise AI Platforms
- โ Complete customization - users define their own AI experts
- โ Hybrid cloud architecture - customer choice of infrastructure
- โ 100% data sovereignty - enterprise data never leaves customer infrastructure
- โ Multi-cloud support - AWS and Azure with seamless routing
- โ Enterprise portal - complete organization and user management
- โ Production-ready infrastructure with full authentication
- โ Temporal knowledge graphs with provenance and graceful fallback handling
- โ Resilient connectivity - Neptune/CosmosDB fallback ensures service continuity
- โ Open SDK with transparent operations and full API access
๐ License
MIT License - see LICENSE file for details.
Built with โค๏ธ by the VRIN Team
Last updated: September 15, 2025 - Production v0.4.0 with Hybrid Cloud Architecture
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