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.

Handler's answer:

Handler uses AI analysis, TikTok content research, video metadata extraction, creative pattern detection, and a web-based dashboard to help app marketers find and understand winning TikToks.

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 combines vector embeddings with BM25 keyword matching and cross-encoder reranking, handling both natural-language queries and exact SKU lookups. Same salesperson behavior across 65+ languages without a translation layer.

Handler's answer:

Handler is built specifically for app marketers who want to find what is already working on TikTok. Instead of guessing content ideas, Handler helps teams discover outlier TikToks, understand winning patterns, and decide what to test next.

Emporiqa's answer

Online store owners and e-commerce agencies running Drupal Commerce, Magento 2, PrestaShop, Sylius, or WooCommerce. Mid-size to large catalogs (2,000 to 100,000 products) where keyword search stops working and shoppers need a salesperson.

Handler's answer:

Handler is made for app founders, growth marketers, mobile app teams, indie app builders, and agencies that use TikTok to grow consumer apps.

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.

Handler's answer:

Handler was created because app teams spend too much time manually scrolling TikTok trying to understand what content works. We built it to make TikTok research faster, clearer, and more repeatable for app marketers.

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 customer, you never pay. Unlimited team members on every account. Native plugins for five e-commerce platforms: WooCommerce (WordPress), Magento, PrestaShop, Drupal Commerce, and Sylius, plus a webhook API for anything else. And the chatbot closes sales, while most competitors deflect, escalate, or capture leads.

Handler's answer:

Handler is focused on TikTok research for app growth, not generic social media management. It helps marketers move faster from “what should we post?” to clear creative direction based on real winning TikToks.

Handler's answer:

Handler is currently early, so we are not publishing customer names yet. The product is built for app founders, consumer app teams, growth marketers, and agencies working on TikTok-based app growth.