02 · B2B Tech & Outbound Growth Pipeline~10 HRS MANUAL WORK SAVED / WEEK
MULTI-AGENT AI BUSINESS AUTOMATION
Autonomous Account Discovery, ICP Scoring & Contextual Outreach Engine
LangChainLangGraphLLM Orchestrationn8nApollo.ioHubSpot CRMPython
01 / THE CORE BOTTLENECK
Rep Fatigue & Superficial Personalization
Growth and sales reps were drowning in repetitive manual prospecting: reviewing hundreds of target domains, researching recent funding/hiring news, evaluating ICP scorecards, and crafting bespoke messages one by one.
02 / THE ARCHITECTURAL FIX
Multi-Agent DAG with Schema-Constrained Handoffs
Designed and deployed a LangChain/LangGraph and n8n autonomous multi-agent pipeline integrated with Apollo.io and HubSpot CRM that continuously evaluates target accounts and queues high-probability deals.
KEY ARCHITECTURAL ELEMENTS:
—LangChain & LangGraph multi-agent supervisor pattern for task delegation
—Custom Python scraping and schema validation for clean unstructured data parsing
—n8n webhook orchestrator managing schedule triggers and rate-limited API calls
—Apollo.io enrichment endpoint integration with domain validation checks
—HubSpot CRM custom property sync and deal-stage automation
03 / VERIFIED BUSINESS OUTCOMES
Defensible Operational Returns
10–15 target accounts autonomously qualified per week without manual SDR searching
~10 hours of manual sales work saved every week per growth team member
Eliminated generic template outreach; all emails generated with verified contextual hooks
Deterministic score threshold prevents bad-fit accounts from clogging CRM pipeline