Leadfire is an AI chat assistant for websites and online stores that turns visitor conversations into qualified enquiries. It is built to respond instantly, capture contact details, and collect structured lead information rather than leaving businesses with vague messages or missed chats.
The product qualifies enquiries by gathering names, phone numbers, email addresses, job details, service preferences, timeframe, and other key signals. It also guides the conversation with natural, human-sounding replies, customisable questions, and responses shaped around a business’s service, job types, tone, and the kinds of enquiries it wants. Leadfire includes analytics that show which pages, sources, campaigns, and devices generate quality leads and where prospects drop off. The site also says it provides unlimited AI conversations, unlimited lead capture and qualification flows, and instant replies around the clock.
Leadfire is delivered as a plugin that can be dropped into a WordPress site, and the site also describes it as working on any website. Incoming enquiries are managed in a clean admin workflow, and structured lead details are delivered straight to a team’s WhatsApp account for follow-up. The page presents live examples for service businesses such as waste clearance, roofing, and driveway work, and says the assistant is tailored to each customer’s brand, tone, and enquiry flow.
Pricing is shown as free for 7 days, then £29.99 per month. The site also refers to a free, instant audit tool for reviewing a website’s enquiry flow. The product page uses the term AI chat assistant and describes Leadfire as more than a chat bubble.
Leadfire is an AI project. It automates lead qualification and customer engagement on WordPress sites using AI-powered chat. It is built as a B2B product for small businesses and service providers using WordPress. There is a free tier. Leadfire is available on the web.
Leadfire builds and maintains Leadfire, and it first shipped in 2026. Among its 6 catalogued features are AI live chat, lead qualification, and whatsApp integration.
Summary written by a language model from the project’s public pages.
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