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Multi Agentic Customer Query Handling and Resolution Orchestrator with Guardrails

by RamSUpdated Aug 2026
RequiresGmailGmailGoogle GeminiAirtableAirtableEmail (IMAP)Email (IMAP)OpenAI
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GuGuardrailsAgOrchestrator AgentOrchestrator Ag…TWCall Ticket Analyser AgentCall Ticket Ana…TWCall Knowledge Worker AgentCall Knowledge …TWCall Resolution AgentCall Resolution…MBSimple MemoryGmail TriggerEmail Reply ToolSTSlack ToolGuard LLMReasoning Model for OrchestratorReasoning Model…Log Threats in AirtableLog Threats in …EREmail Trigger (IMAP)Email Trigger (…AgKnowledge worker and InvestigatorKnowledge worke…DDDefault Data LoaderDefault Data Lo…Embeddings OpenAIEmbeddings Open…VSKnowledge Base RetrievalKnowledge Base …VSKnowledge Base StorageKnowledge Base …RAG LLMCoClean JsonTicket Analyser LLMTicket Analyser…CoClean JSONAgEmail / Ticket Analyser AgentEmail / Ticket …Resolution Agent LLMResolution Agen…AgResolution AgentMBSimple Memory for RAG agentSimple Memory f…MBSimple Memory for Resolution AgentSimple Memory f…MBSimple Memory for Email Analyser AgentSimple Memory f…FoUpload File / Copy Text hereUpload File / C…SePlaceholder 2(Read Note and Setup)Placeholder 2(R…SePlaceholder 1(Read Note and Setup)Placeholder 1(R…SePlaceholder 3(Read Note and Setup)Placeholder 3(R…1234567891011
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Starts on a Gmail event

On incoming email, a guarded multi-agent system resolves customer queries with Gemini and a Supabase vector store, replying via Gmail and logging to Airtable.

Tags

eventadvancedGmailGoogle GeminiSupport ChatbotAI Chatbotdiscoveredpending-review
Connects
gmailGmailGoogle GeminiairtableAirtableemailimapEmail (IMAP)OpenAI
CategoryRAG & Knowledge Bases
Triggerevent
Complexityadvanced
Nodes32
AddedJun 27, 2026