The lead-capture failure mode
Generic chatbot widgets (the ones you can install from a SaaS dashboard in ten minutes) typically fail at lead capture in one of three ways. They answer questions but never push toward a contact handoff. They aggressively push toward a contact form that visitors abandon. Or they are so obviously bot-like that visitors disengage before any lead signal forms.
The model: invisible structured extraction
The chatbot we deploy works differently. The visitor experience is a conversation: they ask, the bot answers, they keep asking. Behind the scenes, every response includes a hidden structured channel that watches for qualifying detail (name, address, phone, problem description, urgency level). The moment that channel captures enough detail to constitute a lead, a structured email fires to the business — without interrupting the conversation, without requiring a form click, without asking the visitor to confirm anything.
The visitor never realizes a lead was captured. They keep chatting. The business gets a structured email with everything they need to call the visitor back.
The system prompt is the product
The model is a frontier Anthropic model. The product is the system prompt we write for your specific business. Services, pricing posture, response windows, service area, the way you triage emergency vs scheduled, the language you actually use with customers, the questions you ask in a typical intake.
A good system prompt for a plumber looks very different from one for a law firm. A pet-boarding chatbot operates differently from a B2B logistics chatbot. The model is the same; the prompt is bespoke per client.
Prompt caching keeps costs flat
One detail most chatbot vendors gloss over: AI API costs scale linearly with conversation volume by default. At high volume that becomes a problem. We use prompt caching so the system prompt is cached on the API side — we only pay for the new tokens in each turn, not the full prompt every time. Operating cost stays flat even at 5,000+ messages per month.
Spam and safety hardening
Public chatbots get hit with the same spam and abuse problems contact forms do, plus prompt-injection attempts. We harden every deployment with: CSAM and harm-content phrase filter, US/CA geo-fence via Cloudflare country headers, prompt-injection resistance (the bot ignores instructions embedded in user input), refusal patterns for off-topic requests, rate limiting.
Integration is one script tag
The chatbot is a single JavaScript file loaded on first interaction (we lazy-load to avoid impacting Core Web Vitals). It works on custom-coded sites, WordPress, Squarespace, Wix, Shopify, anywhere you can paste a script tag. We can deploy on a third-party site you do not control if that is the constraint.
What this looks like in practice
See a Reno leak-detection company — live chatbot trained on a Las Vegas plumbing business, handling 24/7 inbound interest while the owner sleeps. The chatbot captures qualifying detail (name, address, problem) and fires a structured email to the owner’s inbox within seconds. From visitor to lead notification in under three seconds, every time.
Pricing
$99-249/month depending on conversation volume. Setup and system-prompt training included. See the AI Chatbots service page for the full breakdown.
Ready to apply this?
This is the playbook we run on every YelloPost AI build. If you want a build like this for your business, book a quick demo.