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Case StudyEQUOS · Voice AI · Solo Founder

€1.5M in enterprise pipeline. One founder.

No sales team. No paid ads. No manual prospecting. Full autopilot.

~35%
Connection rate
>30%
Reply rate
1–3/day
Calls booked
0%
Manual effort
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Most founders try to solve pipeline with effort.
More outreach, more follow-ups, more time.

Effort doesn't scale.

The alternative is to build a system: automated processes that generate, qualify, and convert leads without requiring your time at every step.

Antoine's system has two engines. The Inbound Engine captures demand that already exists — people who engage with his content and are pre-warmed before any conversation starts. The Outbound Engine creates demand proactively through signal-based lists. Both are fully automated. Both rely on Kakiyo to handle every conversation.

The system

Two independent engines. Same CRM pipeline. Kakiyo at the center.

Inbound Engine

Captures demand that already exists. Content drives engagement, engagers become conversations, conversations become meetings.

LinkedInLeadSharkClayKakiyoMeeting
Outbound Engine

Creates demand proactively. Signal-based lists target the right prospects. Kakiyo runs every conversation from scratch.

ClayKakiyoMeeting
Both engines → Same CRM pipeline → Discovery call, fully prepped

The full stack

LinkedIn
Demand creation
LeadShark
Engagement capture
Clay
Enrichment + ICP scoring
Kakiyo
Every conversation, inbound and outbound
n8n
Automation layer + pre-call summaries
Attio
CRM + pipeline tracking
Cal.com
Call booking

You don't need every tool on day one. The minimum viable version is Clay + Kakiyo + a CRM.

How it works

Step by step, from content to booked meeting.

Inbound Engine

01
LinkedIn
Demand creation. Strategic lead magnet posts that surface in front of decision-makers and drive engagement. No ads.
02
LeadShark
Engagement capture. Someone likes or comments. LeadShark fires instantly: auto-replies, extracts the profile, pushes it into the system.
03
Clay
Enrichment + ICP scoring. Profile enriched with company data, scored against ICP, and routed. ICP match goes to high-intent track.
04
Kakiyo
AI conversation. Full autopilot: connection, follow-up, qualification, call booking. Every message personalized from Clay data.
05
Attio
Pipeline updated. Lead added with enriched data, conversation status, and engagement history. Real-time pipeline.

Outbound Engine

01
Clay
List building + segmentation. Lists filtered by industry, role, seniority, tech stack, and trigger events. Signal-based targeting only.
02
Kakiyo
Automated outreach. Prospects pushed from Clay. Connection, personalized opening, follow-ups, call booking. Kakiyo does the talking.
03
Attio
CRM sync. Status updates, reply signals, and pipeline stage changes happen automatically as conversations progress.

Pre-call intelligence

When a call is booked from either engine, a second automation triggers. Kakiyo exports the full conversation, n8n generates a structured AI summary, and the note is pushed to Attio.

Full conversation history
Clear intent signals
Personalized talking points
Zero prep time

The results

Industry average vs. EQUOS running on Kakiyo.

Connection rate
Industry
15–20%
EQUOS
~35%
Reply rate
Industry
5–10%
EQUOS
>30%
Calls booked
Industry
1–2 / week
EQUOS
1–3 / day
Manual effort
Industry
High
EQUOS
0%

These numbers are not from a 10-person SDR team.
They are from one founder running on full autopilot.

Cloud-based, no Chrome extension
AI pre-qualifies before invites
Qualified meetings on autopilot

Kakiyo