Beyond the LLC: Automating Your Fashion Consulting Business
Yes, you should set up an LLC for a small fashion consulting business. It separates your personal assets from business liabilities, even with low revenue.
Once the legal structure is in place, the real challenge is managing client work without administrative help. Small consultancies spend hours on repetitive tasks like processing style questionnaires and scheduling follow-ups, which limits how many clients they can serve.
We built an AI assistant for a 6-person brand styling studio. It processes their 30-question client style quiz, generates a summary using the Claude API, and drafts the initial client welcome email. The build took 2 weeks and cut their client onboarding time from 90 minutes down to just 15.
What Problem Does This Solve?
Most fashion consultants start with a mix of standard tools: a Google Form or Typeform for client intake, Calendly for scheduling, and Gmail for all communication. This works for the first few clients, but it breaks down quickly. Client answers from the form have to be manually copied into a separate document, wasting the first hour of every new engagement on data entry.
A client's detailed preferences get buried in long email threads. Finding what they said three weeks ago about a specific color palette means searching through your inbox. Schedulers like Calendly can book an initial call, but they cannot manage a multi-step sequence like a fitting followed by a final review a week later. This forces you into manual email back-and-forth, which feels unprofessional.
Fundamentally, these tools move data around but cannot interpret it. A Typeform submission is just a wall of text. It cannot read twenty answers, synthesize the client's core style into three bullet points, and flag that their stated budget doesn't match their brand preferences. This interpretive work, the most time-consuming part of onboarding, remains entirely manual.
How Does It Work?
We start by connecting directly to the Typeform API. When a new client submits your questionnaire, a webhook triggers a FastAPI endpoint we host. We use a Pydantic model to validate the incoming data, ensuring every field from the form is correctly mapped and typed before any processing begins.
The validated data is then sent to the Claude API. We engineer a specific prompt that instructs the model to act as your expert styling assistant. It reads all the client's answers, extracts key themes like 'prefers natural fabrics' or 'needs outfits for business travel', identifies potential style conflicts, and generates a structured 250-word summary. The entire process, from webhook trigger to final summary, completes in under 8 seconds.
The AI-generated summary and a list of key tags are written to a new client record in a Supabase database. This creates a clean, searchable system of record for every client. The system then uses the summary to draft a personalized welcome email, referencing specific client answers. It sends this draft via the Gmail API for you to review and approve, complete with a pre-filled subject line.
The entire application is deployed as a serverless function on AWS Lambda, which keeps hosting costs under $15 per month for up to 500 client submissions. We use structlog for structured JSON logging to AWS CloudWatch and set up an alert that notifies you via Slack if the Claude API fails or if processing time for any single client exceeds 30 seconds.
What Are the Key Benefits?
Onboard a Client in 15 Minutes, Not 90
Automate the manual review of style questionnaires. The AI assistant reads, summarizes, and drafts the welcome email before you even open your inbox.
Pay for Usage, Not Per User
A one-time build cost and flat monthly maintenance. Your operating costs stay low even if you add another stylist, with no per-seat software fees.
You Own Your Client Intake Logic
You receive the full Python source code in your private GitHub repository. The custom prompts and logic that define your unique consulting process belong to you.
Get Notified Before Your Clients Do
The system monitors its own health. If a third-party service like Typeform has an outage, you get a Slack notification instantly to manage the client experience.
Integrates With Your Existing Tools
The system connects directly to Typeform, Google Calendar, and Gmail via their APIs. Your workflow does not change; the manual steps just disappear.
What Does the Process Look Like?
Workflow Discovery (Week 1)
You provide access to your questionnaire, email templates, and scheduling process. We map every manual click and copy-paste action of your client intake.
AI Assistant Build (Week 2)
We write the Python code, engineer the Claude API prompts, and build the Supabase database. You receive a link to a staging version to test with sample data.
Integration and Launch (Week 3)
We connect the system to your live Typeform and Gmail accounts. The first real client submission gets processed automatically while we monitor.
Monitoring and Handoff (Weeks 4-8)
We monitor all automated processes for four weeks to ensure reliability. You receive a runbook and a Loom video walkthrough of the code and infrastructure.
Frequently Asked Questions
- How much does a system like this cost?
- The cost depends on the number of integration points and the complexity of the logic. A system that only processes a form and sends an email is simpler than one that also needs to check inventory with suppliers. After a 30-minute discovery call, we provide a fixed-price quote. All builds are scoped engagements, not hourly.
- What happens if the Claude API gives a weird or wrong summary?
- This is rare but possible. The system logs every API request and response. If you see a bad summary, you can send us the log ID. We use that data to refine the prompt and add more specific instructions to prevent it from happening again. Maintenance includes up to two prompt revisions per month.
- How is this better than using Zapier to connect Typeform and Gmail?
- Zapier can connect two apps, but it cannot interpret the content. It can move raw text from a form into an email template. It cannot read the answers, understand the client's style preferences, generate a unique summary, and then use that summary to write a truly personalized email. Our system adds a layer of intelligence, not just data plumbing.
- I'm not technical. How do I manage this?
- You do not have to manage it. The system is designed to run without intervention. The only thing you see is the end result: a summarized client brief and a sent email. We handle all deployment and monitoring. The optional monthly maintenance plan covers any issues, updates, or API changes from third-party services.
- Can this system also help me source clothing items for clients?
- Yes, that would be a second, more complex module. We could build an AI agent that takes the client's style summary and scours specific online retailers for matching items based on size, budget, and style keywords. This is a common follow-on project after the initial client intake automation is running smoothly.
- What if I change my client questionnaire next year?
- Small changes, like rephrasing a question, will not break anything. If you add or remove questions, the system will need a small update. This is typically a few hours of work and is covered under our monthly maintenance plan. We just need to update the Pydantic model and potentially the Claude API prompt to reflect the new structure.
Related Solutions
Ready to Automate Your Small Business Operations?
Book a call to discuss how we can implement ai automation for your small business business.
Book a Call