Agentkit turns your website, docs, and knowledge base into an AI chatbot your customers can talk to. Point it at a URL or upload files — it crawls, indexes, and learns your content in minutes. Then drop a single line of code on any site to embed a chat widget that answers questions in your brand's voice, 24/7.
Features
- Train on anything — websites, PDFs, docs, sitemaps, or raw text
- One-line embed — drop a JS widget on any site, framework-agnostic
- Multi-model — choose from GPT, Claude, Gemini, and open models via OpenRouter
- Custom branding — match colors, avatar, tone, and welcome messages to your brand
- Conversation history — review every chat, spot gaps, retrain on misses
- Lead capture — collect emails and qualify visitors inside the chat
- Team workspaces — invite collaborators with role-based access
- Analytics — see top questions, satisfaction, deflection rate
- Multilingual — auto-detect and respond in the visitor's language
Use Cases
- Customer support — deflect tier-1 tickets with instant answers from your help center
- Sales & lead qual — engage site visitors, answer pricing questions, capture leads while they're hot
- Internal knowledge base — give employees a searchable assistant over Notion, Confluence, or wikis
- Docs & developer relations — let users chat with your API docs instead of grepping them
- Onboarding — guide new users through your product without writing tooltips
- E-commerce — product recommendations, sizing, shipping FAQs on autopilot
- Education — turn course material into a 24/7 study assistant for students
Comments
This looks genuinely useful for teams that already have a lot of helpful content, but still make users dig through docs, FAQs, or support pages to find answers. I like that it’s not limited to just one source type. Being able to train it on websites, PDFs, docs, sitemaps, or raw text makes it feel flexible enough for support, sales, internal knowledge bases, and developer docs. The one-line embed is also a big plus. A lot of chatbot tools sound good until setup becomes a project on its own, so making it easy to add to any site is important. The conversation history and analytics features are probably what make this more useful long-term. Being able to see what people ask, where the bot misses, and then improve the knowledge base from that feedback is exactly what teams need. Overall, this feels like a practical product for companies that want better support and lead capture without adding more manual work for the team.
Building, training, and embedding AI chatbots without needing to manage the underlying infrastructure is a real time-saver for developers. The "embed for any website" angle makes this accessible to non-technical users too. Would be great to know more about the training data privacy model — specifically whether each customer's training data is isolated or if there's any shared learning across accounts. That's usually a key concern for enterprise buyers.
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Comments
This looks genuinely useful for teams that already have a lot of helpful content, but still make users dig through docs, FAQs, or support pages to find answers. I like that it’s not limited to just one source type. Being able to train it on websites, PDFs, docs, sitemaps, or raw text makes it feel flexible enough for support, sales, internal knowledge bases, and developer docs. The one-line embed is also a big plus. A lot of chatbot tools sound good until setup becomes a project on its own, so making it easy to add to any site is important. The conversation history and analytics features are probably what make this more useful long-term. Being able to see what people ask, where the bot misses, and then improve the knowledge base from that feedback is exactly what teams need. Overall, this feels like a practical product for companies that want better support and lead capture without adding more manual work for the team.
Building, training, and embedding AI chatbots without needing to manage the underlying infrastructure is a real time-saver for developers. The "embed for any website" angle makes this accessible to non-technical users too. Would be great to know more about the training data privacy model — specifically whether each customer's training data is isolated or if there's any shared learning across accounts. That's usually a key concern for enterprise buyers.
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