File AI is a full-stack, production-ready Software-as-a-Service (SaaS) platform designed for secure, scalable multi-tenant document management with AI-powered semantic search. Built using modern technologies including React, Node.js, PostgreSQL, and Docker, the platform enables organizations to securely store, manage, and retrieve documents with intelligent search capabilities powered by Retrieval-Augmented Generation (RAG). The system ensures strict tenant-level data isolation, role-based access control, and enterprise-grade security while maintaining high performance and scalability.
","showcaseImages":[],"featureImage":{"guid":"https://api.evolvan.com/wp-content/uploads/2026/03/Screenshot-from-2026-07-31-15-31-02.png"},"featureImage2xDisplays":{"sourceUrl":"https://api.evolvan.com/wp-content/uploads/2026/03/Screenshot-from-2026-07-31-15-31-02.png"},"websiteURL":"http://40.177.246.111:5173/","date":"2026-03-11T10:47:17","challenge":"Developing a secure multi-tenant SaaS platform introduced significant architectural and security challenges. The system required strict tenant-level data isolation while operating on shared infrastructure, ensuring no cross-tenant data exposure. Implementing AI-powered semantic search using a RAG pipeline added complexity in terms of vector storage, embeddings, and query performance optimization. Secure file uploads, role-based access control with granular permissions, and real-time notifications further increased system complexity. Additionally, the platform needed to maintain high performance under concurrent usage while adhering to enterprise-grade security and compliance standards.","solution":"A robust multi-tenant architecture was implemented using row-level data isolation through tenantId enforcement across all database models, combined with middleware-based tenant context injection. PostgreSQL with pgvector enabled efficient vector similarity search for AI-powered semantic queries. The RAG pipeline was modularly designed to support text extraction, chunking, embedding generation, and hybrid search. JWT-based authentication with refresh tokens ensured secure session handling, while a comprehensive RBAC system provided granular permission management. File uploads were secured using S3 integration with tenant-isolated paths and pre-signed URLs. Docker-based containerization ensured consistent deployment, scalability, and environment isolation across development and production.","results":"File AI successfully delivered a production-ready SaaS platform with secure multi-tenant data isolation and enterprise-grade performance. API response times averaged under 200ms, while semantic search queries executed within 500ms. The system supports 1000+ concurrent users and scalable horizontal expansion. AI-powered document retrieval significantly reduced document search time compared to traditional keyword-based systems. The platform achieved secure file handling, real-time activity tracking, and comprehensive audit logging, positioning it as a competitive solution in the AI-driven document management SaaS market.","caseStudiesData":null,"projectType":["saas","restsoap","reactjs"],"shortDescription":"A production-ready multi-tenant SaaS platform with AI-powered semantic document search, secure data isolation, and enter","slug":"fileai-multi-tenant-ai-document-management-saas","technologiesData":{"nodes":[{"id":"cG9zdDoxMDEz","title":"Saas"},{"id":"cG9zdDo5OTE=","title":"Postgresql"},{"id":"cG9zdDo1OTA=","title":"CSS3"},{"id":"cG9zdDo0NTM=","title":"NodeJs"},{"id":"cG9zdDo0NTE=","title":"React Js"}]},"additionalInfoLeftImage":null,"additionalInfoRightText":"Client: Internal SaaS Product
Industry: AI Document Management
Platform Type: Multi-Tenant SaaS
Architecture: Full-Stack (Frontend + Backend)
Deployment: Docker Containerized
Database: PostgreSQL with pgvector
Status: Production-Ready MVP
File Ai is built with a scalable, microservices-ready architecture that supports secure tenant isolation, AI-driven document retrieval, and enterprise-grade compliance standards. The modular design allows continuous feature expansion, AI model upgrades, and infrastructure scaling without compromising stability or security. The platform is designed to support regulated industries requiring strict data protection, audit logging, and controlled user access.
","testimonials":null,"metaTagDetail":"File Ai is a multi-tenant AI-powered document management SaaS platform built with React, Node.js, PostgreSQL, and Docker, featuring semantic search, role-based access control, and enterprise-grade security.","metaTagKeyword":"AI document management SaaS, multi-tenant SaaS platform, semantic search document system, RAG document search, React Node.js SaaS application, secure document management software"}}},"staticQueryHashes":["1070998670","1495217618","3069938414","3400521700","3910808925","884346343"],"slicesMap":{}}