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Building a Print-on-Demand Shopify Integration Platform
This Print-on-Demand (POD) platform is designed to help businesses sell custom-designed products without managing inventory, production, or logistics.
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AI Shopping Assistants and Agentic Commerce
AI assistants that help shoppers find products, and product feeds so AI agents can sell for you.
Stack we work in
- Google Gemini
- Stripe
- Shopify
- WooCommerce
- BigCommerce
- PostgreSQL
- Redis
- LangGraph
- Projects delivered
- 680+
- Clients served
- 310+
- Client retention
- 98%
- Certified engineers
- 20+
- Building since
- 2018
Figures as of Oct 2026
Trusted by
- Aralia
- Rosa Pistrina
- Lashbo
- Micromunchi
- Payroll Ninja
- POD
- Petdx
- Yokey
- Spin Up
- Starwear
- Udlins
- Vegpal
- Wander Wings
- Wish It
- Wisl
Problems we are usually asked to fix
Shoppers now ask AI assistants what to buy, both on store websites and in tools such as ChatGPT.
Read the full overview
We build AI shopping assistants that answer product questions in plain language, recommend the right items and help customers check out, using only your real catalog, prices and stock. We also prepare your store for agentic commerce: clean product feeds, the Agentic Commerce Protocol for checkout inside ChatGPT, Shopify's agent-ready catalog and MCP tools, and similar standards, so AI agents can find and sell your products accurately.
Search that needs exact words
Shoppers type what they mean and get no results or the wrong products.
The same pre-sale questions all day
Support answers sizing, compatibility and delivery questions by hand.
Invisible to AI shopping
Products do not show up, or show wrong details, when shoppers ask AI assistants.
Messy product data
Missing attributes and inconsistent titles make every channel weaker.
A chatbot nobody trusts
An earlier bot gave wrong answers and was switched off.
Outcomes
What you get
- Shoppers find the right product faster, in their own words
- Fewer pre-sale questions for your support team
- Your products listed and buyable where AI agents shop
- Cleaner product data that helps every channel, not just AI
- Answers grounded in your catalog, with checks against errors
- Code, prompts and data owned by you, with no lock-in to us
What we deliver
Where teams use this service
Guided selling
Ask a few questions and recommend the right product, as a good shop assistant would.
Conversational search
Replace keyword search with natural-language search on the store.
Selling in ChatGPT
Product feeds and Instant Checkout through the Agentic Commerce Protocol.
Pre-sale support
Answer product and policy questions and hand off to a human when needed.
Learn moreCatalog enrichment
Fill missing attributes and fix product copy at scale.
Custom AI agents
Agents that take actions such as reorders or returns through your APIs.
Learn more
What you receive
Use case and data review
Which assistant features to build first, and what product data needs fixing.
Enriched catalog and feeds
Cleaner product data and feeds for your store, ads and AI channels.
AI shopping assistant
Search, recommendations and chat, integrated into your store and apps.
Agentic commerce setup
Feeds, checkout and order flows for AI shopping channels.
Evaluation suite
Test questions, scores and dashboards for accuracy and cost.
Handover
Source code, prompts and runbooks in your repositories and accounts.
Conversational product search
Let shoppers describe what they want.
- Natural-language search over your catalog with semantic and keyword matching
- Answers grounded in product data, reviews and policies, with links to products
- Size, fit and compatibility questions answered from your own data
- Hand-off to a human agent in Gorgias, Zendesk or Intercom
Built with
- Gorgias
- Zendesk
- Intercom
Recommendations and personalization
Show the right products to each shopper.
- Similar and complementary product recommendations
- Quiz and guided-selling flows powered by an LLM
- Personalized ranking from browsing and purchase history, with consent
- Bundles and upsells based on cart contents
Agentic commerce
Be ready when AI agents shop for customers.
- Agentic Commerce Protocol integration for Instant Checkout in ChatGPT, with Stripe
- Product feeds in the formats AI shopping surfaces require
- Shopify catalog and Storefront MCP setup for AI agents
- Order, stock and price APIs that agents can call safely
- Monitoring of how your products appear in AI answers
Built with
- Agentic Commerce Protocol
- Stripe
- Shopify
- Shopify Catalog
Product data quality
AI is only as good as the catalog it reads.
- Product attribute enrichment and clean-up with LLMs and human review
- Consistent titles, descriptions, sizes and variants across channels
- Feeds for Google Merchant Center, Meta and AI shopping surfaces
- Structured data on product pages for search engines and agents
Built with
- Google Merchant Center
Safety, evaluation and cost control
Keep answers accurate and costs predictable.
- Guardrails against made-up prices, stock or claims
- Test sets and evaluations before each release, tracked in Langfuse
- Model choice across OpenAI, Anthropic Claude and Google Gemini by task and cost
- Caching, usage limits and spend dashboards
Built with
- Anthropic Claude
- Google Gemini
- Langfuse
Why retailers choose Equitysoft for AI shopping assistants
Commerce and AI in one team
The same team builds stores and AI products, so the assistant is wired into your catalog, cart and order data rather than bolted on.
Answers grounded in your catalog
The assistant only quotes products, prices and stock it can find in your data, and we test it against a written evaluation suite before launch.
A pilot before the big spend
We start with a pilot on one use case and a written estimate, so you see real conversations before committing to a full build.
Cost and safety designed in
Model choice, caching and usage limits are part of the design, and customer data handling is agreed up front under NDA.
Recent work from our team
FMF Glass Hardware – WooCommerce to Shopify Store Migration
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Revolutionizing Chocolate Shopping with CioccoMiami
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Starwears: Bid on Celebrity Fashion and Own a Piece of Star Style!
How we work
Discovery
We review your catalog, questions shoppers ask, channels and data quality, and agree measurable goals.
You receive Use cases and success measures
Data readiness
We clean and enrich product data and set up the feeds and indexes the assistant needs.
You receive Clean catalog and feeds
Prototype
We build an assistant on your real catalog and test it with real questions.
You receive Working prototype and test results
Build
We integrate it into your store, apps and support tools, with guardrails and analytics.
You receive Production assistant
Agentic channels
We connect your catalog and checkout to AI shopping channels such as ChatGPT.
You receive Live agentic channel
Measure and improve
We track answer quality, conversions and costs and keep improving prompts and data.
You receive Monthly report and roadmap
Tech stack
Technologies we use
AI and machine learning
Databases
BI and analytics
Frontend
Backend and APIs
Languages
Cloud and DevOps
- Vercel AI SDK
AWS
CRM, commerce and CMS
Other tools
Engagement
Ways to work with us
Pilot
A fixed-scope assistant on your real catalog, tested with real questions.
- Clear success measures
- Go or no-go result
Full project
Assistant, feeds and agentic channels delivered against an agreed scope.
- Written estimate up front
- Demos at each iteration
Dedicated team
AI and commerce engineers working inside your process.
- Scale up or down with notice
- Covers data, AI and store work
Questions, answered
It depends on catalog size and data quality, the channels (website, app, chat, ChatGPT), integrations with support and order systems, and how much evaluation and tuning you need. After a short discovery call we send a written estimate. Model and platform usage is billed to your accounts. As a guide, an AI shopping assistant pilot usually costs $10,000 to $30,000, and a production assistant with agentic checkout and feeds $30,000 to $100,000 or more (USD).
It is when an AI agent, such as ChatGPT or another assistant, finds and buys products for a shopper. For your store to be chosen, agents need accurate product data and a safe way to check out. Standards such as the Agentic Commerce Protocol, created by OpenAI and Stripe, define how that works.
Yes, if you meet the program's requirements. We prepare a product feed, connect checkout through the Agentic Commerce Protocol with Stripe or a compatible payment provider, and handle order updates. Shopify and some other platforms provide much of this through their own integrations, which we set up and extend.
We design against it. The assistant can only answer from your live catalog and policies, prices and stock are read from your systems at answer time, and we test it on hundreds of real questions before launch and after changes.
We choose by task and cost, usually from OpenAI, Anthropic Claude and Google Gemini models, and sometimes open models for search and ranking. The design lets you switch models later.
It helps a lot. Most projects start with enriching titles, attributes and descriptions, which also improves your website search, marketplaces and ads. We use LLMs with human review to speed this up.
Yes. We integrate with Shopify, WooCommerce, BigCommerce, Adobe Commerce and custom platforms through their APIs, and add the assistant as a site widget, a search experience or inside your app.
We send models only the data needed for each answer, use providers' business terms that do not train on your data, store chat logs securely with retention limits and respect cookie and personalization consent.
We track answer accuracy, search-to-cart and conversion rates for assistant users, support tickets avoided and cost per conversation, and compare against a control group where possible.
We start with a short review of your catalog, data and goals, then send a written estimate. A pilot on one use case usually takes 4 to 8 weeks; a full assistant with agentic checkout takes longer. We need access to your product data, store platform and a person who can make decisions.
You own the code, prompts, evaluation suite and data. After launch we can monitor answer quality, model costs and conversions, and update the assistant as your catalog and the AI models change.
Want shoppers and AI agents to find your products?
Book a call with our team. We will review your catalog and goals and outline the assistant, the agentic channels, the steps and the likely cost.