Multiple chatbot personas on one site, each scoped, each in its own voice
SleekAI’s multibot architecture lets you run a sales bot on pricing, a docs bot on documentation, and a support bot on the help center, each with its own system prompt, model, presets, and display conditions, all using your OpenAI, Anthropic, Google, or OpenRouter key.
One chatbot to rule them all is the wrong shape
Most chatbot plugins force you into a single configuration: one system prompt, one greeting, one set of presets, one model. That works fine for a tiny brochure site. It falls apart the moment your site has more than one job. A sales bot on the pricing page should be warm and pushy.
A docs bot in the developer reference should be terse and accurate. A support bot in the help center should be patient and lean on knowledge base articles. Squeezing all three into one prompt produces a vague middle-tone bot that does none of them well.
SleekAI is built around multibot from day one.
The result is that each persona reads the data relevant to its scope. The sales bot pulls product postmeta and pricing fields. The docs bot pulls code examples from custom post types.
Features
Multibot architecture
SleekAI ships with native multibot. Display conditions pick the right one for the current request.
Per-section scoping
Scope by post type, taxonomy term, user role, or logged-in state. The sales persona never shows on docs and the support persona never shows on the marketing homepage, no JS hacks.
Answers from your data
Map post titles, content, post meta, taxonomies or a WP_Query into the instruction, and the bot answers from what your site actually publishes.
Where personas earn their keep
Sales and pricing pages
A sales persona pitches plans, quotes competitor comparisons, and offers prorated upgrade math. Tuned for conversion, runs on a smarter model, scoped to the marketing tree.
Developer documentation
A docs persona answers code questions, links to API references, and quotes endpoint signatures.
Repeat questions
Answer the questions visitors ask every day from the pages and posts where you already answer them.
How personas fit together on one site
Map sections to personas
List your major site sections: marketing, pricing, docs, support, members. Pick a tone and a scope per section. That gives you the persona list. Most sites land between three and six personas.
Map your data
Choose the posts, fields, taxonomies or users the bot should know and reference them in the instruction.
Pick a model
Store your OpenAI, Anthropic, Google or OpenRouter key once in the shared AI settings, or add a compatible endpoint, and choose the chatbot’s model.
Set display conditions
Decide which pages, post types, roles or logged-in states show the chatbot.
Why personas matter
A website is rarely one job. A pricing page is selling. A docs page is informing. A help center is recovering trust. Each job has a different right tone, a different right model, and a different right set of preset questions.
Forcing all of them through one chatbot config means picking a middle that satisfies none of them. The pricing page bot ends up too cautious, the docs bot ends up too chatty, the support bot ends up too generic. Multibot solves that without exploding maintenance.
You still have one plugin, one API key infrastructure, one conversation log table, one update path. What changes is that each persona is its own record with its own prompt and model. The visitor experiences the bot that matches the section they are on, and the team experiences a much cleaner editorial surface.
Docs questions are typically short and well-bounded, so the docs persona can run on a cheaper model and still feel accurate. Sales questions need more nuance, so the sales persona can run on a smarter model.
Frequently asked questions
How many chatbot personas can I run on one site?
There is no hard limit. Each persona is a separate chatbot record with its own configuration. Sites with five or six personas are common: marketing, sales, docs, support, members.
How does SleekAI decide which persona to show?
Each chatbot record has display conditions evaluated against the current request: Post type, taxonomy term, user role and logged-in state.
Do personas share conversation history?
No. Each persona has its own conversation thread per visitor. Moving from the sales page to the docs page starts a new thread with the docs persona. This keeps the system prompt separation clean and avoids cross-contamination of voice.
Can each persona use a different LLM provider?
Yes. The model choice is per chatbot record. A high-traffic docs bot can run on a cheaper Haiku or Gemini Flash model while the sales bot runs on Sonnet or GPT-4 class. You can also mix providers if you want OpenAI for one persona and Anthropic for another.
How do I keep personas visually consistent?
What changes per persona is the chatbot name, avatar, greeting, and presets. Visitors see the same widget chrome but different content, which feels like one product with multiple specialists.
Which AI providers does it support?
OpenAI, Anthropic, Google and OpenRouter, plus custom OpenAI-compatible endpoints. You bring your own API key and the provider bills you directly.
Where does the chatbot get its answers?
From the WordPress data you map into its instruction: post titles and content, post meta, ACF and Meta Box fields, taxonomies, terms, users and user meta, or a WP_Query. Values resolve on every request.
Can it act on a visitor’s behalf?
No. A chatbot answers questions. It does not submit forms, create bookings, open tickets or send email; put the links for those steps in its instruction so it can point visitors to them.
Related pages
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