@paper has made the transition from design iterations to a live iOS app incredibly seamless. Being able to show clients exactly what their app will look and feel like in a working build makes the entire process easier to communicate.
From there, I can focus on what I enjoy most: designing, refining, and making decisions while @claudeai handles the repetitive development work.
At this point, I’m essentially delegating, reviewing, and watching it all come together in real time.
Atelier Pétale — Boutique Botanical Hair & Color Studio
Location: 428 Blossom Row, Suite 3B, Design District
Problem solved: Atelier Pétale needed to turn customer inquiries into confirmed appointments while reducing the manual work of answering questions, managing availability, matching clients to the right service and stylist, and aligning colour expectations.
Who is the salon?
Atelier Pétale is a boutique hair and color studio led by Elena, a master colorist and the owner, known for signature 3-hour botanical balayages. She also manages two other specialists with different services and schedules: Marcus and Chloé.
Their quirks
Elena can be unavailable for messages while working with lightener.
Her signature balayage appointments can occupy three hours and are booked weeks in advance.
Clients often begin with vague questions about booking and need help determining the right service.
Clients sometimes request the wrong stylist or times that conflict with approved leave.
Colour clients can have expectations that do not match what is realistically achievable.
The solution
We rebuilt the customer journey around “Can I book?” → “You’re booked.”
AI Support: answers client questions and can book appointments directly through chat.
Find My Match: clients upload their own hair photo, combine it with existing shades or reference colours, and preview a realistic result before booking—helping align expectations.
Smart booking: availability accounts for stylist schedules, leave, existing bookings, and service duration.
Automated follow-through: confirmations, rescheduling, cancellations, reminders, and waitlist recovery.
Elena had to handle inquiries, determine what service a client actually needed, manage stylist availability, deal with cancellations and scheduling conflicts, and repeatedly clarify what colour result a client should realistically expect.
After
Atelier Pétale turns that process into a self-service booking journey: AI Support answers questions and books directly from chat; Find My Match lets clients upload their own hair and preview reference or existing colours realistically; and the booking system matches services to the correct stylist and available time.
"Find My Match" caught my attention more than the booking flow itself. For a salon, helping someone figure out what they actually need before asking them to choose a service could remove a lot of friction. Nice product decision. Is the matching based purely on preferences or...
𝐑𝐀𝐆 𝐀𝐈 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 | 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐒𝐞𝐚𝐫𝐜𝐡, 𝐀𝐈 𝐀𝐧𝐬𝐰𝐞𝐫𝐬 & 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞
I designed and built a RAG-powered AI knowledge platform that lets businesses search documents, websites, databases, and internal knowledge using natural language.
The system processes content, creates embeddings, stores them in a vector database, retrieves the most relevant information, and uses AI to generate accurate, source-grounded answers.
My services include: RAG development, document ingestion, semantic search, vector database setup, OpenAI/LLM integration, internal knowledge assistants, API integrations, and analytics.
The solution helps teams find information faster, reduce repetitive research, improve answer consistency, and build scalable AI-powered knowledge systems.