Emporiqa
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Coding Assignment Help
Emporiqa is the AI chatbot that closes sales. A shopper asks "dog food for a senior lab with joint problems, grain-free, under 40" and your search bar returns every dog food you sell. The right product is there; the search just can't find it.
Emporiqa acts like an online salesperson for your store. It reads your product catalog and does what a floor rep does: recommends the right product, handles objections on price or fit, suggests variations when the shopper hesitates, and walks them to checkout from the chat. It also answers shipping, return, and payment questions from your own store pages.
Answers come from your products and your store pages, not the open internet. When it isn't sure, it hedges or hands off rather than guessing. Every conversation is saved and reviewable on your dashboard.
When it shouldn't answer alone, it hands off to your team with the full conversation. The shopper sees a waiting status; your agent picks up where the salesperson left off.
Product expert, customer support, and order-tracking agents run in parallel so one chat can find a jacket, quote the return policy, and check a past order without switching tools.
A dashboard showing which chats led to purchases, the full conversion funnel, top products by cart activity, and satisfaction ratings.
65+ languages, same behavior in each. Install free with $25 of signup credit (~100 conversations) on your real catalog, no card needed. You pay only when the chat talks to a shopper. If it never talks to a shopper, you never pay. EU company, GDPR, no model training on your data.
Native plugins for WooCommerce (WordPress), Magento 2, PrestaShop, Drupal Commerce, and Sylius, all available on their official marketplaces, plus Shopware 6 via Composer and GitHub.
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Emporiqa's answer
Django, LangGraph, Qdrant (vector database), PostgreSQL, Redis, Celery. Search uses intfloat/multilingual-e5-large for embeddings and ms-marco-MiniLM-L-6-v2 for cross-encoder reranking. Inference runs on a separate FastAPI service.
Emporiqa's answer
For over 15 years I built software, first as an engineer and then as a CTO, and I kept running into the same gap with online stores. Walk into a physical shop and a good salesperson knows the products and helps you choose. Online, the shopper is alone with a search box that returns 200 results or none. I built Emporiqa to put that salesperson on the website. It answers only from your own products and pages, so it won't invent a product or quote a price you don't have. It recommends the right item, handles the objections that stall a sale, and walks the shopper to checkout. It also shows which chats turned into orders, so you can watch it earn its keep.
Emporiqa's answer
Pay-as-you-go: $0/month base + $0.25 per conversation, with $25 of signup credit (~100 conversations) and a $59/month default cap you can adjust. A conversation counts only when a shopper writes to the chat, so you pay only when the chat talks to a shopper. If it never talks to a shopper, you never pay. Unlimited team members on every account. Native plugins for six e-commerce platforms: WooCommerce (WordPress), Magento, PrestaShop, Drupal Commerce, Sylius, and Shopware 6 (Composer/GitHub), plus a webhook API for anything else. And the chatbot closes sales, while most competitors deflect, escalate, or capture leads.
Emporiqa's answer
Online store owners and e-commerce agencies running Drupal Commerce, Magento 2, PrestaShop, Sylius, Shopware, or WooCommerce. Mid-size to large catalogs (2,000 to 100,000 products) where keyword search stops working and shoppers need a salesperson.
Emporiqa's answer
It's the AI chatbot that closes sales. It behaves like an online salesperson: recommends a specific product from your catalog, handles objections on price and fit, suggests variations, and walks shoppers to checkout. Not a FAQ bot that deflects. Answers come from your catalog, so it doesn't invent products.Search expands the shopper's question with a language model, matches it against vector embeddings of your catalog, then reranks with a cross-encoder, handling both natural-language questions and exact part-number lookups. Same salesperson behavior across 65+ languages without a translation layer.
My programming assignment, in general, is good, I got 81 out of 100, and I was planning to get more, but it is still I still want to work with your team, and looking forward to receiving good work from a great team. I received some notes about the PPT that it was very basic, but overall, I would really thank you for the quick response and actions from your side in a perfect timeline :)
Based on our record, Emporiqa seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I built Emporiqa, a chat assistant for e-commerce stores. After shipping integrations for Drupal Commerce, WooCommerce, and Sylius, Magento was next. The catalog complexity made it the most interesting one to build. - Source: dev.to / 5 months ago
I wrote about the hybrid search pipeline, the sync architecture, and the parallel agent system separately. This post is about how they connect. The WooCommerce plugin is live on wordpress.org. I covered the full WooCommerce integration on the Emporiqa blog, and the setup docs walk through the configuration step by step. You can test the pipeline end-to-end with a free sandbox at Emporiqa. - Source: dev.to / 5 months ago
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