AI & AUTOMATION / BEAUTY & COMMERCE
Virtual Try-on Assistant.
An AI backend and vector search layer connecting a virtual beauty try-on experience with conversational product recommendations.
Beauty & commerce
USA
AI Backend & Product Search
Founder’s freelance project
01 / THE CHALLENGE
The problem worth solving.
Connect an existing SDK-based try-on experience to product-aware conversational intelligence.
What the system needed to do
- Connect the visual SDK experience to backend APIs
- Retrieve relevant products using catalog embeddings
- Keep conversations within the beauty product domain
The real-world constraints
- The existing SDK had no backend execution capability
- Product catalog integration and vector search
- Conversation guardrails and interactive response times
02 / THE SOLUTION
How it came together.
A dedicated backend connects SDK interactions to product data, a vector search layer, and a conversational assistant. Filter classification and recommendation logic are separate, allowing the visual experience and product discovery to evolve independently.
Bridge the existing try-on SDK to the backend API.
Explore the architecture. This is an explanatory diagram, not a live production system.
03 / THE OUTCOME
What the work delivered.
- A product-aware backend for virtual try-on
- Embedding-based product search and recommendations
- Conversation boundaries for relevant product guidance
KEEP EXPLORING
Another problem. Another solution.
Visa & immigration services / Eastern Europe
Visa Application Automation
- Problem
- Agents retyped passport and document data into multiple application forms. A single typo could delay or derail an application.
- What we built
- Passport and document extraction that prepares visa forms automatically, leaving staff to review instead of retype.
- Result
- 20 to 30 minutes saved per application
Illustration at $20 per person-hour. Application volume is not assumed. Before project and running costs.
Owner-reported project results.
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WhatsApp & Instagram Booking Automation
- Problem
- Staff manually handled bookings, pricing questions, and payment screenshots across WhatsApp and Instagram. Replies slowed outside working hours.
- What we built
- A connected booking and FAQ system with customer records, distance-based pricing, and payment-proof extraction.
- Result
- Around 12 hours saved per week in operations
Illustration at $20 per person-hour, assuming the reported weekly workload continues for 52 weeks. Before project and running costs.
Owner-reported project results.
YOUR NEXT CHAPTER
Something great
starts with a conversation.
Bring one repetitive process. We’ll discuss the time it takes, what could be automated, and the next step that fits your business.
30 minutes. One workflow. No obligation.