Instant Product Advisor

For

Shop owners at independent boutiques and specialty stores

Solves

Customers leave empty-handed because staff cannot provide quick answers about product details or alternatives.

Delivers

A customer-facing URL with camera recognition and Q&A capabilities, and a populated product catalog

Built in

10 days of creation time, MVP in 2 days

Investment

$5,000 for the MVP, $15,000 for the full product

Run it

Inside your business, or as part of your offer to clients

For shop owners at independent boutiques and specialty stores, turn product labels and images into instant customer answers and checkout capability.

1. Scan product labels with camera.
2. Extract attributes from images and web data.
3. Generate a customer-facing QR code.
4. Identify products in real time via camera.
5. Answer natural language questions about products.
6. Generate payment links for checkout.

What goes in, what comes out

The workflow

1. In
   Start with

   Product images, label text, web data, shop product database

2. 1

   Upload product images

3. 2

   Scan labels to extract data

4. 3

   Review extracted data

5. 4

   Generate a customer URL

6. 5

   Answer customer questions

7. 6

   Process checkout requests

8. 7

   Hand over the item

9. Out
   Finish with

   A customer-facing URL with camera recognition and Q&A capabilities, and a populated product catalog

AI does the heavy lifting, people stay in charge

Use vision models to identify products from camera feeds and language models to answer questions using the shop's own data. Validate product attributes against the database. A shop owner reviews the extracted data before it is used to ensure accuracy.

What your team sees

Key screens: Inventory scanner, customer query interface, checkout agent. Use a camera viewfinder for scanning items, a chat interface for answering questions, and a payment link generator for checkout. The first view is the inventory scanner, followed by the customer query interface and checkout agent.

Accounts and administration

Shop owner accounts, product database versions, approval states for extracted data, usage logs, and subscription management

Integrations and data access

Shopify for online store data, payment gateways for checkout

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   2 days

   One buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   5 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will shop owners at independent boutiques and specialty stores use it to solve "customers leave empty-handed because staff cannot provide quick answers about product details or alternatives"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Prove it by having a shop owner scan 50 products and track the number of customer questions answered and sales completed via the system compared to baseline.
4. Measure, then decide. Track number of products catalogued, number of customer interactions and and conversion rate of assisted sales. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. The first cut: one shop owner, one product category, the scanner module and the basic Q&A module, manual review of extracted data

After the MVP. Automated checkout processing, multi-language support, inventory management integration, and advanced analytics on customer queries

What the build depends on. Browser camera access, on-device vision models, and language APIs

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Monthly subscription priced at 190 USD for small shops and 490 USD for larger stores based on product count and interaction volume

Message to test

Turn your phone into a 24/7 salesperson for your shop

Where to find buyers

Direct outreach to boutique owners, social media marketing, and partnerships with retail software providers

Lead magnet

A free demonstration of scanning your inventory and generating a customer-facing URL

The first 30 days

1. Week 1: Build the inventory scanner and data extraction module.
2. Week 2: Develop the customer-facing web app with camera recognition.
3. Week 3: Integrate the Q&A agent with the shop's product data.
4. Week 4: Launch the pilot with one boutique.

Paid pilot

Prove it by having a shop owner scan 50 products and track the number of customer questions answered and sales completed via the system compared to baseline.

Success metrics

Number of products catalogued, number of customer interactions, and conversion rate of assisted sales

Retention and expansion

Earn recurring revenue through monthly subscriptions and increase value by adding more products and features over time

Why clients would pick it

The value comes from the proprietary dataset of product attributes extracted by the vision model, which becomes more accurate as more shops use it

Alternatives and positioning

Staff training, printed brochures, and manual checkout. This differs by providing instant, AI-driven answers and self-service checkout on the customer's device

Main delivery costs

API costs for vision and language models, server hosting for the web app, and customer support

Limit the number of products per subscription tier, restrict access to the admin panel, and ensure the AI does not hallucinate product details not in the database