Inside Zembl's Multi-Agent Sales System: How 4 AI Agents Handle 100+ Daily Leads

A technical walkthrough of Zembl's production AI sales system - showing exactly how 4 specialized agents collaborate to process 100+ inbound leads daily with minimal human intervention. This is the complete system architecture behind Zembl's 30% conversion increase. AGENT ARCHITECTURE: 1️⃣ TONI (Lead SDR Agent) → Triggered when lead enters Salesforce → Categorizes lead (SMB/residential, bill status) → Performs 3 research steps: Google search, LinkedIn enrich, website scrape → Validates prospect info (finds ABN) → Composes personalized email based on categorization → Sends via own Outlook inbox → 14-day follow-up triggers for non-responses 2️⃣ COMPARISON CAMI (Bill Analysis Agent) → Runs high-level bill comparison if uploaded → Extracts key data points → Provides quick insights for sales team 3️⃣ SMS SAMI (SMS Outreach Agent) → Handles email bounces (typos, wrong domains) → Sends SMS follow-ups when email fails 4️⃣ SALESFORCE SALLI (CRM Specialist) → Handles all Salesforce operations → Uploads bills, enriches fields → Changes queues, updates data → Toni's "direct report" (added month 3 due to Toni's overwhelm) DESIGN PHILOSOPHY: "AI agents are like humans - they can get overwhelmed. Toni got overwhelmed managing everything, so we gave him Sally as his first direct report at 3 months." Specialist agents with clear responsibilities perform better than one generalist agent trying to do everything. OPERATIONAL PROCESSES: 360 PERFORMANCE REVIEWS: → Team whiteboard sessions at 3 months → What's working with Toni's prompt? → Development areas for next 3 months → SMS Sami born from these review sessions PROBATION PERIOD: - 4-6 weeks reviewing all Toni's emails before full automation - Customer-facing communication required iteration - Escalation protocols: If customer emails twice, human reviews - Business manager now manages AI agent like team member CURRENT STATE: → Toni's team runs at ~95% auto-approval → Only tool failures escalate to humans → Daily check-ins to review edge cases → Continuous iteration based on team feedback --- 🏢 ABOUT ZEMBL Australian business energy comparison platform zembl.com.au 🤖 Built with Relevance AI | relevanceai.com Resources: → Traditional case study (3 min overview): https://youtu.be/HaWOuBGo0BY → Request demo: relevanceai.com/book-a-demo #AIArchitecture #SalesEngineering #MultiAgentSystems #GTMTech #SalesAutomation #TechnicalDeepDive #AIWorkforce