Projects using PostgreSQL in RanchiProjects using PostgreSQL in Ranchi
Cover image for Introducing live RAG ,VIXIT Cortex:
Introducing live RAG ,VIXIT Cortex: Enterprise AI That Turns Your Data Into Instant Answers Category: AI & Machine Learning / Web Development Tools Used: Node.js, PostgreSQL, Vector Embeddings, REST API, Natural Language Processing, Zero-Trust Security and many more stuff Project Description: The Problem: Data-heavy teams — hospitals, law firms, banks, insurers — spend weeks extracting insights from their data. SQL queries, data teams, manual reports. Slow, expensive, error-prone. The Solution: VIXIT Cortex is an enterprise AI agent that lets teams ask questions in plain English and get instant answers. No SQL. No data teams. No waiting. What I Built: Natural language query engine that understands domain-specific terminology Vector embedding system that processes 18 years of data in under 3 minutes Real-time analytics with sub-second query response (1.2s latency) Zero-trust security architecture (HIPAA, SOC 2 Type II, GDPR compliant) Tenant-isolated PostgreSQL databases with SHA256 token hashing Human-in-the-loop oversight for critical decisions Export capabilities (PDF, Excel, CSV) with source citations Key Features: Ask questions like "How many patients have eye power above 8?" and get instant answers Multi-step reasoning that breaks complex queries into logical steps Persistent memory that remembers context across conversations 99.99% uptime SLA with 24/7 priority support Integration with existing systems (Postgres, MySQL, Snowflake, BigQuery, Epic, Cerner)
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Cover image for AI Document Intelligence & Invoice
AI Document Intelligence & Invoice Processing Platform Description Built an AI-powered document intelligence platform designed to automate invoice processing, document classification, data extraction, and approval workflows. The system uses AI, OCR, and workflow automation to process business documents automatically, eliminating manual data entry and reducing processing delays across finance and operations teams. By integrating with existing databases and business systems, the platform transforms unstructured documents into actionable business data. Key Features • AI-powered document analysis • Invoice data extraction • OCR-based document processing • Automated approval workflows • Purchase order matching • Vendor management integration • Document classification • Data validation system • Real-time processing dashboard • Automated reporting and audit trails Business Impact ✓ Reduced manual data entry ✓ Faster invoice processing ✓ Reduced processing errors ✓ Improved financial visibility ✓ Faster approval cycles ✓ Reduced operational costs ✓ Increased productivity across teams Technology Stack • Java • Spring Boot • PostgreSQL • OpenAI API • OCR Processing • REST APIs • Workflow Automation • Analytics Dashboard Results • Automated document processing workflows • Reduced invoice processing time by approximately 75% • Improved data accuracy • Reduced manual administrative effort • Accelerated approval and payment cycles This solution demonstrates how AI-powered document intelligence can automate finance and operational processes while improving accuracy, compliance, and efficiency.
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Cover image for AI Customer Support Assistant
Built an
AI Customer Support Assistant Built an AI-powered customer support platform designed to automate customer interactions, reduce support workload, and provide instant assistance using company documentation and knowledge base content. The system leverages OpenAI, enterprise knowledge bases, and backend automation to deliver accurate, context-aware responses while seamlessly escalating complex issues to human agents when needed. Key Features: • OpenAI-powered conversational assistant • Knowledge base search and retrieval • FAQ automation system • Context-aware customer responses • Human escalation workflow • Multi-channel support integration • Customer interaction analytics • Real-time response monitoring • REST API architecture • Enterprise-grade backend services Business Impact: ✓ Reduced repetitive support workload ✓ Faster customer response times ✓ 24/7 automated customer assistance ✓ Improved customer satisfaction ✓ Consistent support experiences ✓ Lower operational costs ✓ Increased support team efficiency Technology Stack: • Java • Spring Boot • PostgreSQL • OpenAI API • REST APIs • Docker • Maven • Knowledge Base Integration Results: • Automated approximately 80% of common support requests • Reduced average response time from hours to seconds • Reduced manual support workload by approximately 60% • Improved scalability without increasing support staff This solution demonstrates how AI-powered customer support systems can improve customer experience while significantly reducing operational overhead.
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