Building an internal AI platform for a comms agency — multi-model setup with GDPR compliance (Azure OpenAI + Claude API). Anyone done this?

I'm planning an internal AI tool for a small communications agency (~15 people). The concept is a web app where each employee gets a personal login with their own conversation history and preferences. It'll include a RAG layer with client-specific knowledge bases — so when someone works on a press release for Client X, the AI already knows the client's tone of voice, brand guidelines, and past work. There'll also be specialized tools for recurring tasks (LinkedIn posts, press releases, social copy).

The multi-model setup: For GDPR compliance (we're EU-based), I want to route different tasks to different models:

• Azure OpenAI (GPT-4.1 / GPT-4.1 mini) — for tasks involving client data, because of their EU datacenter guarantees
• Anthropic Claude API (Sonnet) — for strategic and creative work; Anthropic has a solid DPA and I prefer Claude for longer-form reasoning
• Model routing via edge functions — so we can swap models without touching the frontend

The idea is to assemble context in the edge function: user profile + client RAG + tool-specific system prompt → routed to whichever model fits the task.

What I'm trying to figure out:

1. Has anyone built a similar multi-provider setup? Any gotchas with mixing Azure OpenAI and Anthropic in the same routing layer?
2. Is there a clean pattern for model routing in edge functions, or does everyone just write a big if/else?
3. For the RAG layer: pgvector vs. a dedicated vector store (Pinecone etc.) — at our scale (~15 users, ~50–100 client documents), is pgvector sufficient?
4. Any GDPR considerations with Anthropic's API specifically? Azure's enterprise agreement is well-documented, but Anthropic's DPA is less discussed.

Stack: Lovable, Supabase (auth, PostgreSQL + pgvector, storage, edge functions). No dedicated DevOps — needs to be maintainable without deep technical resources.

Happy to share more as it develops. Appreciate any input from people who've shipped something similar.