AI CRM
Automation
Client: SaedShafane.com — founder-run AI consultancy, Melbourne
Published June 2026
The Challenge
Manual follow-ups and low conversion
Manual email follow-up was the primary bottleneck. Prospects received generic messages days after initial contact. Response times were measured in hours. CRM records were updated inconsistently, making pipeline reporting unreliable. Conversion rate was 30% below benchmark for the sector.
The Approach
AI agent swarm for end-to-end CRM automation
Saed built a five-agent swarm (prospect → qualify → outreach → schedule → CRM sync) that automated every non-judgment step in the sales process. The human sales function was reduced to relationship management and closing — the two activities where human judgment creates irreplaceable value.
The Agent Swarm
Five specialised agents, coordinated by a LangChain orchestrator, handle the full pre-closing pipeline without human involvement. Each agent has a defined input/output contract and a fallback handler.
Prospect Agent
Sources new leads from LinkedIn and intent-signal databases, filtered against ICP criteria before entering the pipeline.
Qualify Agent
Enriches each lead with company size, tech stack, and recent news signals, then scores against a predefined rubric.
Outreach Agent
Generates personalised email sequences referencing the prospect's specific context — company news, recent posts, role change.
Schedule Agent
Books discovery calls via Google Calendar API without human involvement, handling reschedules and confirmations automatically.
CRM Sync Agent
Updates HubSpot records in real time — contact status, interaction log, next-step flag — eliminating all manual data entry.
AI CRM Automation
The full CRM automation service — the practice behind this case study.
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