Fetchply vs Knoku

Pricing, capabilities and platforms side by side. Prices are as of the "Pricing checked" date in the table.

Fetchply

Setup is genuinely minimal: drop in a URL, let it crawl, embed one line of code, and the widget is live. The cited-answer model is the differentiator — instead of generic GPT responses, visitors get answers traced back to your help center or product catalog, which reduces the 'the bot told me something wrong' support escalation. That said, Fetchply is a conversational widget, not an agent that takes actions — it answers questions, it does not process returns or update records. For teams whose support volume outpaces their message plan, conversations start queuing or getting blocked until the next billing cycle. Teams needing autonomous task execution or deep CRM write-back will hit the ceiling fast.

Knoku

Knoku indexes public and internal sources — crawled websites, GitHub Markdown, Notion runbooks, Confluence spaces, Jira tickets, Zendesk help articles, and OpenAPI schemas — into a single project index, then serves answers through an embeddable widget, Slack, and API. Citations point back to the source file, so users can verify the answer without trusting a black box. The built-in analytics track deflection rates, repeated questions, and knowledge gaps, which means you see where your docs are failing without exporting data to a separate analytics tool. The ceiling appears when you need answers that require synthesizing information across sources in ways that demand reasoning rather than retrieval — and there is no self-hosted option, so every query touches Knoku's infrastructure.

Specs come from each tool's own site and docs (how we test). AIDiveForge is editorially independent.