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Contra - A professional network for the jobs and skills of the futureAI-Powered Client Intake System for Beauty Pros | Feedback Wanted

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Mia Ivanović

• 1d

Just submitted my project to the Notion Custom Agent Buildathon 🚀

I built an AI-powered client intake system for beauty professionals using Notion.

It helps organize client data and identify VIP clients with simple AI recommendations.

Would love feedback from the community 👇

Notion nocode AI Automation

Krystal Antoine

• Mar 23

Automated client intake pipeline built for Krystal OS. Prospect submits a Tally form → n8n receives the webhook → Claude API analyzes the submission and generates a pre-call briefing → confirmation email sent automatically via Gmail → client record created in Notion. Full pipeline operational.

AI Automation Business Workflow Automation Business Operations Claude N8N Notion

Bob Vasic

pro

• Mar 24

Clean setup. This is exactly how intake should work -- capture → enrich → organize.

The Claude briefing is the real power here; with simple qualification added, this becomes a pre-qualified pipeline, not just automation.

Close the loop with outcomes and it gets smarter over time.

Goran Plantic

• Mar 23

This is an amazing challenge, looking forward to build with notion agentic workflows 😊

Jelena Stricak

pro

• Mar 20

Stop planning, start building products. 🚀

Unlock the full power of Notion at the Contra-powered BUILDATHON.

👇 Secure your spot here: https://on.contra.com/q6DNjf

Gabe Upton

• Mar 23

Built an AI coaching system called The Mirror — a context-aware assistant that learns about each user and delivers personalized insights across 5 life dimensions.

Features 5 chat modes (Chat, Guided, Deep, Research, Insight), each with specialized prompts and behavior. Guided Intake builds a user profile through conversation, tracking understanding across key life areas. All responses grounded in a RAG knowledge base via pgvector semantic search.

The research pipeline generates 6 evidence-based documents daily via Claude and ingests peer-reviewed papers from PubMed weekly — automatically chunked, embedded, and stored for retrieval.

Tech: Next.js 15, Claude API, Supabase (pgvector + RLS), OpenAI embeddings, n8n. Shipped as a core feature of Catalyst OS with Supabase Auth and Stripe-gated Pro access.