It is the opposite. The whole point of SleekAI is that it does not require a procurement cycle, a vendor onboarding, or an MSA. You install a plugin, plug in an API key, and you have a chatbot grounded in your own content the same day. The five person company spends less time configuring than they would have spent reading a SaaS pricing page.

SleekAI is a one-time WordPress plugin license. The variable cost is the LLM provider you choose, billed through your own API key. We have customers running their entire support and sales chatbot for under twenty dollars a month on token cost because the prompts are tight and the volume is real but modest.

Common setup. Most startups have docs on Notion or a static site generator and the blog on WordPress. You can either move the docs into WordPress as a CPT, or point SleekAI at a JSON or API source so the bot reads the docs system without touching its hosting. The display conditions let one bot answer both.

Yes, but you should run them as separate bots. The sales bot lives on the pricing and landing pages with a shorter, more outcome focused system prompt. The support bot lives on the help center with a longer, more careful prompt. Multibot ships with SleekAI, so this is a configuration choice, not a separate purchase.

OpenAI, Anthropic, Google, and any OpenRouter route, which covers most other current models. Per-bot model choice means the cheap fast model handles the high volume pricing bot and the more careful model handles the technical support bot. Switching providers is a single field change, no migration.

Both are good products if you are at the scale where their pricing makes sense. At seed and Series A, the per-seat math rarely does. SleekAI gives you grounded conversations on your own content for the cost of an API key, with the conversation log in your own database. The trade is you do the configuration yourself, which is a couple of hours.

Conversations live in a normal WordPress table. Configurations live in JSON files in your theme. There is no proprietary index, no vendor owned embedding store, and no exit fee. You can dump the table to CSV, archive the configs in your repo, and the bot disappears cleanly when you decide to migrate.

The widget loads lazily after the first paint, so Core Web Vitals do not move. The LLM call only happens when a visitor actually types a message, and the response is streamed back, so the perceived latency is similar to ChatGPT. There is no background polling and no analytics beacon hammering your server.