Problem
Lead generation teams lose momentum when telephony, qualification, and follow-up depend on scripts, disconnected tools, and inconsistent operator decisions.
Project case study
StormIQ
AI-powered lead generation platform designed to automate prospect engagement workflows and move structured outcomes into sales operations.
Project facts
Theme
Applied AI & Automation Systems
Current state
Active Build
My role
Sole architect and full-stack engineer
Core constraint
Async job orchestration: separating telephony events from decision logic via queue-backed services
Outcome
Architecture validated with working voice gateway, queue orchestration, and CRM integration layer; advancing toward pilot deployment
Approach
A concise problem → system → evidence structure so the engineering story is easier to inspect.
System design
Built as a layered voice workflow platform. Telephony and transcript intake feed queue-backed orchestration services, decision layers evaluate conversations, CRM-facing APIs move structured lead outcomes forward, and dashboards keep the system reviewable instead of opaque.
Voice gateway handles inbound and outbound call flow events.
Queue-based orchestration separates telephony from decision logic.
Agent and CRM layers turn transcripts into actionable lead records.
Stack
TwilioRabbitMQFastAPIPythonRedisDashboard Web
Evidence
The architecture is documented as a real voice workflow system with clear boundaries between intake, orchestration, decisioning, and delivery.
Architecture diagramWorkflow diagramLead routing artifacts
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