Ecommerce work is gated on platform fit before anything else. A prospect with a 500,000 USD Shopify Plus project does not care how good your Magento work is; they need to know within two minutes whether you have shipped recent Plus migrations, scope similar to theirs, and a team available in their timezone. A static portfolio grid rarely makes that obvious. SleekAI reads case studies tagged by platform, scope, and industry, then answers "have you done a Shopify Plus replatform from Magento" with specific projects and outcomes.

The bot pulls from wp_posts, ACF fields, and custom taxonomies via the data-source wizard. Tag case studies by platform, revenue band, and project type (replatform, redesign, optimization), and the bot filters answers on any combination. Display conditions run a Shopify-tuned bot on the Shopify cluster and a WooCommerce-tuned bot on the Woo cluster, each pulling the same WordPress data but with a different system prompt and scope.

Pre-qualification keeps the new business team focused. The system prompt encodes the agency's minimum engagement, the platforms the team does and does not service, and the typical project shape per tier. Off-fit prospects get a polite no; qualified leads book a discovery call with the chat transcript attached. Conversation logs include model name, token usage, and page URL so the agency can audit which platform clusters actually convert and tune the prompt over time.

Mid-market and enterprise ecommerce RFPs are gated by platform fit before anything else gets evaluated. A merchandising lead with a 300,000 USD Shopify Plus replatform on the table is not running a generic best-agency search; they are filtering down to teams who have shipped recent Plus projects of comparable scope. The static portfolio grid is bad at making that obvious.

Most agency sites group case studies by client logo, not by platform tag, and the prospect has to scroll, infer, and triangulate to figure out which projects are Plus versus standard Shopify versus headless. Most give up after two or three case studies and move to the next agency on the shortlist. A bot that reads every case study and filters by platform and project type closes that loop in two messages.

Integration scope is the second gate. Plus migrations stall on ERP and subscription complexity more than on design taste, and a prospect with NetSuite and Recharge in their stack needs to know within the first conversation whether the agency has shipped those integrations recently. The bot can speak to this directly if the capabilities page is in its context.

Pre-qualification by engagement size protects the new business team's calendar, which is the most expensive thing in the funnel after senior engineering time. Filtering out projects under the agency's minimum, or above the team's current capacity, before a call books, raises close rate on calls that do happen. The transcript is the compounding payoff: reading a week of conversations tells the agency which platforms inquire most, which integration patterns recur, and which case studies actually pull weight on the cluster pages, which informs both pitch decks and case-study sequencing on the site itself.