Enterprise Multi-Tenant Platform Build-Out

UpworkSENot specifiedintermediateScore: 74
AI BotAI ChatbotAI DevelopmentAI Text-to-SpeechAI Text-to-ImageAI Speech-to-TextAI App DevelopmentAI Agent DevelopmentAI Mobile App DevelopmentAI Image GenerationAI ImplementationAI PlatformAI Model IntegrationAI SecurityAI Trading
Milestone 1 — Architecture Setup & Backend Foundation Azure Sweden Central infrastructure setup Azure PostgreSQL with pgvector enabled Redis + Blob Storage setup Dockerized backend deployment New multi-tenant database schema (professionally designed) Strict row-level security implementation tenant_id enforcement at API layer Clean modular Python backend architecture JWT / secure cookie authentication Shared auth between landingpage and app Async job queue setup (Celery or RQ) Logging + monitoring (Application Insights) Outcome: Production-ready backend foundation with verified tenant isolation. ✅ Milestone 2 — Production-Grade RAG & Memory System Document parsing (self-hosted Unstructured or Marker) Optimized chunking strategy Embedding storage per tenant namespace Retrieval of 5–12 ranked chunks Re-ranking layer implementation Multi-query expansion for large documents Strict answer grounding in retrieved context Short-term memory (dynamic 12k–20k token window) Auto-summarization at threshold Hybrid long-term memory with semantic scoring Selective memory retrieval (not full injection) Brave Search API integration (zero retention) Agent-based web search decision logic Outcome: Enterprise-grade RAG system with stable memory architecture. ✅ Milestone 3 — Chat UI & Admin Control Tower Claude-style minimal chat interface Wide chat layout + subtle typography Smooth streaming responses Fully responsive design Usage meter + tenant badge Secure admin control tower (separate route) Tenant management interface Document management dashboard Memory visibility controls Audit logs access Seamless login flow (landingpage → app.) Outcome: Fully functional multi-tenant AI assistant with clean UI and admin control. ✅ Milestone 4 — Voice, Scalability & Production Hardening Azure VM setup for Whisper + diarization Cost-optimized CPU instance Audio storage in Azure Blob Transcription integrated into assistant flow Horizontal autoscaling configuration Load testing & performance optimization Redis caching optimization Async job scaling validation GDPR alignment validation Sweden-only infrastructure confirmation Azure OpenAI regional endpoint configuration Environment-based endpoint switching Security review + audit validation Outcome: Enterprise-ready, scalable, Sweden-compliant AI platform prepared for 500+ tenants.
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