Resume Manager adds a resume custom post type, the resume_category and resume_skill taxonomies, and postmeta like _candidate_email, _candidate_title, and _candidate_location to WP Job Manager. Candidates ask how to add new skills, why their resume is not showing in search, and what employers see when they preview it. Employers ask which candidates match a specific skill set and where to download a resume PDF.

SleekAI maps those fields into the chatbot prompt at request time, so candidate questions get answers based on the actual fields and taxonomies configured for the site. Employers logged in with the right capability can run a recruiter bot that searches resumes by skill or location, filters by job categories, and surfaces the most recently updated candidates. Display conditions keep the two experiences cleanly separated.

Generic bots fail here because the resume data model is wide: a single resume can have dozens of postmeta entries, multiple taxonomies, and attached files. Without an explicit mapping, the bot reverts to vague advice. SleekAI's wizard makes that mapping a few clicks and the data resolves on every request, so a candidate's profile update shows up in the next answer.

Resume Manager sites have two distinct audiences with sharply different needs. Candidates want fast, concrete help editing a resume and surfacing it in the right searches. Recruiters want to find people who match a specific skill set in seconds, not by clicking through pagination.

A generic chatbot serves neither audience well, because it does not know which terms exist in your resume_skill taxonomy and it cannot search the candidate index at all. The data is already in WordPress in a clean shape. SleekAI maps that into the chatbot prompt at request time, so candidate help suggests the exact terms recruiters search for, and recruiter help returns real matches sorted by recency.

Multibot mode keeps the candidate editor bot and the recruiter dashboard bot fully separate. Conversation logs reveal which resume questions repeat, which is usually a sign that the editor or approval workflow itself needs to be clearer. Bring-your-own-key gives the operator control over model choice and cost without giving up the data layer.