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monterdekeanu/README.md

🚀 What’s built here

MicroSaaS / SaaS foundations with AI integration, designed for real usage:

  • AI features: chat assistants, structured extraction, summarization, classification, routing
  • RAG / knowledge base: embeddings + retrieval + citations + eval loops
  • Document workflows: OCR → field extraction → validation → normalized JSON
  • Vision workflows: image understanding → automation → review queues
  • Secure SaaS patterns: authentication, roles/claims, orgs/workspaces, multi-tenant access control
  • Production delivery: logging, rate limiting, retries, background jobs, monitoring-friendly design

🧠 AI Stack

Model Providers

  • OpenAI: tool/function calling, structured outputs, embeddings, streaming
  • Claude (Anthropic): long-context reasoning, summarization, extraction safety

Azure AI

  • Azure Document Intelligence: invoice/contract/forms extraction → structured outputs
  • Azure Vision: image understanding + workflow automation

⚡ Core Tech





🧱 SaaS Building Blocks

  • Auth & Access: Identity, roles/claims, JWT, session flows, passwordless-ready patterns
  • Data & Domain: EF Core modeling, migrations, indexing, query optimization
  • Workspaces / Tenancy: orgs, members, permissions, shared vs isolated data strategies
  • Payments-ready: plans, seats, metering hooks, usage logging
  • Async jobs: queues, schedulers, webhooks, backfills
  • Auditability: change history, event logs, exportable records

🤖 AI Integration Patterns

  • Tool calling: AI triggers actions through controlled functions (safe + auditable)
  • Structured extraction: documents → typed JSON schemas → validation + repair
  • Human-in-the-loop: review queues for uncertain outputs
  • Cost control: caching, rate limits, model routing (fast vs deep), batching
  • Reliability: retries, fallbacks, timeouts, circuit breakers
  • Evaluation: test sets, regression checks, quality scoring, prompt/version tracking

📫 Connect

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