Zilco

Most product catalogs get bolted onto keyword search that was never designed for conversational queries. Zilco puts a chat interface in front of your catalog data: you sync inventory through the API, the Node.js SDK, or the PrestaShop and WooCommerce plugins, and the embedded widget answers visitor questions by pulling from that synchronized data rather than from general model knowledge. The core workflow is catalog-in, grounded-answers-out, with lead capture baked into the chat flow so visitor intent isn’t lost after the session.

The ‘Site Knowledge’ feature is the differentiator worth noting. Beyond product data, you can load policies, FAQs, and service details so the assistant handles the full pre-purchase conversation — pricing rules, availability, booking links, return policies — without routing those questions to a separate FAQ page or leaving the model to guess. The analytics layer flags questions the assistant couldn’t answer, giving catalog and content teams a prioritized list of gaps to close.

Zilco fits cleanly where the problem is catalog discovery and pre-sale qualification: ecommerce stores with large or variant-heavy inventories, vehicle dealers where spec queries are common, real estate listings with availability filtering, and service directories where customers need to find the right offer before booking. Where it doesn’t fit: if you need the assistant to place orders, update CRM records, trigger fulfillment, or execute any post-discovery action, Zilco has no agent loop for that — the vendor describes retrieval and chat, not task execution.

On the integration side, the vendor documents a Catalog Sync API, a Node.js SDK, a PrestaShop module, and a WooCommerce plugin — four documented paths that cover the most common catalog and CMS stacks without requiring a custom build for standard deployments. Access is request-gated, with no self-hosted option described, so data residency or air-gapped deployment requirements are a hard blocker.