Visible on Google. Cited by AI. Converted by the chatbot.
Leadsprovider specializes in B2B/B2C teleprospecting and customer relationship management. Busony powered their digital presence with AI: optimized WordPress site, visibility in generative engines (ChatGPT, Perplexity) and an agentic chatbot to turn visitors into prospects.
The challenge
Three distinct problems, one AI approach.
Invisible in AI engines
Leadsprovider ranked well on some Google queries but was completely absent from ChatGPT and Perplexity answers — where a growing share of B2B prospects now research.
Slow and expensive content
Producing quality SEO content required hours of manual work: GSC opportunity analysis, competitive benchmarking, writing, publishing. Impossible to scale.
Unconverted visitors
The site generated traffic but few direct conversions. Visitors left without leaving contact details or booking an appointment.
What Busony deployed
Three complementary building blocks, deployed progressively.
Multilingual AI WordPress
WordPress site overhaul with AI integration: content updates in natural language, automatic translation of existing pages, continuously optimized on-page SEO. The site is maintained by AI without manual back-office intervention.
Agentic content pipeline (GEO)
The agent queries Google Search Console via MCP to identify high-potential queries (high impressions, low CTR, positions 4–15). It also queries Perplexity to measure AI response visibility, then automatically generates and publishes AEO-optimized content.
Agentic chatbot
AI agent on the site: answers commercial and technical questions, qualifies leads (sector, volume, need), books appointments directly in the calendar and routes to the right contact. Available 24/7.
WebMCP
WebMCP protocol integration to make the site actionable by Google and Gemini AI agents. Prospects can interact with Leadsprovider's services directly from AI interfaces, without visiting the site.
What we actually did
Real examples of the agentic pipeline in action on the Leadsprovider site.
Agentic AI vs manual work
| Task | Manual | Agentic |
|---|---|---|
| Identify GSC quick wins | 2–3h | 2 min |
| Analyse what AI cites | Impossible at scale | Immediate |
| Write AEO-optimized article | 3–4h | 10 min |
| Publish on WordPress | 15 min | Immediate |
| Full workflow | Half a day | Without leaving the interface |
How it's deployed
SEO & GEO audit
GSC opportunity analysis, measurement of current visibility in AI responses (Perplexity, ChatGPT, Claude).
AI WordPress
MCP access configuration for WordPress, integration of translation and automatic SEO optimization tools.
Agentic pipeline
Deployment of the GSC → AI analysis → writing → publishing flow. First content in production within 48h.
Chatbot & WebMCP
Agentic chatbot integration and WebMCP endpoints. Team training on pipeline management.
Stack & tools
Questions about this project
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