Seed Stage

You have traction.You don't have a system.

We have built GTM from zero for companies that raised $12M+ Series A rounds.

Before Phi / After Phi

From founder-led scramble to a system that runs.

Before	After
Founder is the SDR, AE, and closer	Founder on demos only
CRM is a spreadsheet	CRM with attribution and pipeline stages
ICP is "companies that might buy"	ICP mapped, segmented, validated through execution
Every deal is a one-off	Playbook running. Sequences repeating.
No idea what's converting	Daily conversion data across every stage

Zero to pipeline in 6 weeks

Four phases.Signal before we build, then a pod producing from day one.

Week 1-2

Signal

Your market. Your data. We find what's broken before building anything.

Week 3-4

Blueprint

ICP mapped. Playbook designed. CRM configured. You sign off first.

Week 5-6

Pod Live

SDR calling. AE demoing. Daily huddles. Conversions tracked from day one.

Week 7+

Compound

QA catches patterns. Playbook iterates weekly. Pipeline becomes predictable.

The pod

One team. Every role revenue needs.

SDRs

Pre-trained on your ICP. Multi-channel from day one.

AEs

Closers who run demos, handle objections, convert pipeline.

GTM Engineer

Data enrichment. CRM flows. Targeting. Attribution.

GTM Consultant

Industry experience in your vertical. Owns the number.

QA Layer

Every call reviewed. Every email checked. Every day.

The culture difference

What most teams do, and what we do.

Most teams	Phi
Activity counts. Dials per day.	Conversion rates. Deals that moved forward.
Weekly check-ins. Monthly reports.	Daily huddles. Real-time dashboards.
Reps coaching themselves.	QA on every call. Coaching same day.
Static playbook from month one.	Playbook iterating weekly on live data.
Hope the ICP is right.	ICP validated through outbound execution.
Find out what broke at end of quarter.	Find out what broke by Tuesday morning.

Your command center

This is your dashboard from week one.

One pod. One dashboard. Updated daily. Not a monthly business review.

Where does pipeline narrow?

Strong connection rate but the meeting rate drops. The problem is the conversation. We catch it on day two.

Calls Made: 1,302
Conversations: 51
Meetings Set: 7
Demos Run: 3
Closed Won: 3

Are we hitting the number?

Revenue is on pace; demo show-up is not. QA flagged the confirmation sequence the same day.

North-star metrics
Metric	Team	Actual	Target	Pace
Accounts Closed	AE Team	3	of 5	220%
Revenue Closed	AE Team	$47K	of $50K	95%
Demos Set	SDR Team	8	of 10	73%
Demos Show Up	SDR Team	3	of 8	34%

Which rep needs coaching?

Both on pace, but SDR 1's show-up is low. QA flagged discovery depth. Coaching deployed today.

Rep performance
Rep	Connects	Emails	Calls	Connect Rate	Demos	Showed	Pace	Status
SDR 1	20	21	744	2.7%	3	1	110%
SDR 2	31	50	558	5.6%	4	2	147%

What is QA catching?

Qualification accuracy below target. QA identified reps advancing unqualified deals. Fixed same day.

QA scorecard
Metric	Target	Actual
Connection Rate	8%+	9.2%
Meeting Rate	3%+	2.1%
Show Rate	80%+	85%
Qualification Accuracy	90%+	72%
Email Reply Rate	4%+	5.8%
QA Call Score Avg	7/10+	6.8

A day in the life of a Phi pod

This is what happens.Every day. From week one.

7:30 AM

Daily Huddle

Yesterday's conversions reviewed. Today's targets set before the first call.

8:00-12:00

SDR Outbound

Targeted calls and multi-channel outreach against the validated ICP.

12:00 PM

Warm Transfers

Qualified conversations handed to the AE. Pipeline pre-qualified.

1:00-5:00

AE Demos

Demos, objection handling, follow-ups. Pipeline updated live.

5:00 PM

QA Review

Calls audited. Patterns flagged. Messaging fixed for tomorrow.

End of Day

Dashboard Updated

Conversion by stage. Sequence performance. Everything visible.

Proof

Datatruck: $0 to $2.5M ARR.

97%CAC drop$12MSeries A raised$2.5MARR from zero

“They built our entire sales motion from nothing. We went from founder-led chaos to a system that raised our Series A.”

Shohruh Rahmanov, CEO, Datatruck

Read the full story →

Inside the seed motion

How Phi builds revenue from zero, in detail.

AI-Aided Sales

How AI finds signal at seed: enrichment, sequencing and ICP validation from day one, without a big team.

Day-to-Day Ops

What a seed pod does every day, on the operating cadence, with conversions tracked from the first call.

Playbooks

How we design the first repeatable playbook from scratch so growth does not depend on the founder.

QA & Metrics

QA on every call and email, and the metrics that turn a coaching gap into a same-day fix.

Sales Culture

The culture that converts at seed: conversions over dials, daily huddles over weekly check-ins.

Cost of Inaction

What staying founder-led actually costs, and where the price compounds against your runway.

The system that gets you from zero to a Series A.

Your market. Your traction. What is broken. Talk to someone who has built a seed GTM before.

Talk to us

Related:Series Proof Operating Model