Multi-Agent AI Outbound System

The problem

Outbound depended entirely on manual SDR effort: prospect research, list building, personalization and follow-up. Volume was capped by hours in the day, quality dropped whenever volume rose, and follow-up sequences died after two touches.

Scaling meant hiring — with ramp time, management overhead and turnover risk on a role that was 80% repetitive work.

The solution

We designed a multi-agent system where specialized agents hand work to each other: a research agent identifies and enriches ICP-matched accounts from multiple data signals; a writing agent produces genuinely personalized outreach grounded in that research; a qualification agent classifies replies, answers questions and books meetings into rep calendars.

Humans stayed in the loop where judgment matters — approving messaging strategy, taking booked meetings, and reviewing edge-case replies surfaced by the system.

Architecture

• Signal ingestion and enrichment layer feeding a central prospect database
• Claude-powered research and personalization agents with per-prospect context
• Reply classification with confidence-based routing: auto-respond, book, or escalate
• Full CRM synchronization — every touch, reply and meeting logged and attributed

Technologies

Business outcome & ROI

System cost recovered within the first quarter of pipeline generated; ongoing cost is a fraction of one SDR salary.

Services used