Track A • GTM & LinkedIn growth
Outreach that books real calls
Targeted, personalised campaigns tuned to a sharp ICP — measured in acceptance, replies, and booked meetings.
Verified client outcomes & engineering
Proof, not promises.
Two sides of the same engine, both measured. GTM systems turn cold networks into booked pipeline; AI automation workflows remove the manual work behind them. Every result below is real and every client is anonymous.
Results • snapshotAnonymised
LinkedIn network growth0 → 4,000+ (2 mos)
Connection acceptance rateUp to 40%
Qualified calls booked15–20 / mo
Enterprise pipeline opps10–15 opps
Manual lead qualification100% automated
4,000+
LinkedIn followers built from zero in two months
40%
Peak cold-outreach acceptance rate
15–20
Qualified sales calls booked each month
10–15
Enterprise opportunities in two months
How to read this page
Two tracks. One system underneath.
Growth work books the meetings; automation work makes the motion run without manual effort. Most engagements use both.
Track B • AI automation workflows
Systems that remove the busywork
Lead qualification, engagement, validation, and decision workflows built to run automatically while humans retain control.
Track A • GTM & LinkedIn growth
From cold network to booked pipeline.
Five outreach engagements across insurance, deep-tech, martech, and financial services. Different markets, the same playbook: sharpen the ICP, personalise, and follow up with structure.
InsuranceCase 01
A new insurance brand, built from zero to a 4,000+ audience.
Challenge
A newly launched insurance brand needed credibility and a LinkedIn audience from scratch in a crowded, trust-sensitive market.
Strategy
- ›Content-led LinkedIn growth
- ›Educational, data-led posts
- ›Consistent thought leadership and engagement
Quantified results
0 → 4,000+
Followers in 2 months
Niche
Highly engaged audience
Organic
Growth engine established
Transportation & Manufacturing • AICase 02
Doubling connection acceptance for a deep-tech AI company.
Challenge
An AI solutions company was stuck at a 15–20% connection-acceptance rate and weak overall outreach.
Strategy
- ›Refined ICP targeting
- ›Personalised connection requests
- ›Improved messaging and follow-up
Quantified results
30%
Acceptance, up from 15–20%
15%
Response rate
5–10%
Call-booking rate
Martech & AEOCase 03
A predictable pipeline for a martech founder across two regions.
Challenge
A martech startup founder needed predictable pipeline among MSME founders in the US and Middle East.
Strategy
- ›Targeted LinkedIn outreach
- ›Sharp-ICP personalisation
- ›Structured multi-step follow-ups
Quantified results
40%
Connection acceptance
20%
Response rate
15–20
Qualified calls per month
Enterprise • AI VoiceCase 04
Opening enterprise doors for an AI voice-agent platform.
Challenge
An AI voice-agent startup needed access to senior enterprise decision-makers who are hard to reach cold.
Strategy
- ›Named enterprise accounts
- ›Senior stakeholder outreach
- ›Personalised account sequences
Quantified results
10–15
Enterprise opportunities in 2 months
Senior
Decision-makers reached
2–3%
Conversion rate
Financial Advisory • AICase 05
Winning trust first for an AI-powered financial platform.
Challenge
Prospects were reluctant to share financial information early, stalling qualification.
Strategy
- ›Trust-first outreach
- ›AI conversational workflows
- ›Chatbot-assisted qualification
Quantified results
20–25%
Connection acceptance
Higher
Trust during qualification
Better
Qualified-lead quality
Track B • AI automation workflows
The busywork, engineered away.
Five production workflows that research, qualify, validate, and recommend automatically. Each keeps a human in control exactly where judgment matters.
Lead QualificationWorkflow 01
AI lead qualification, from inbound form to scored prospect.
Purpose
High volumes of website enquiries made manual qualification slow, inconsistent, and resource-heavy.
How it runs
- 1Capture every website form
- 2Research the lead and company
- 3Score company size, industry, role, and relevance
- 4Categorise and store qualified prospects
Business impact delivered
Manual qualification eliminated Faster sales response Structured prospect database
Social EngagementWorkflow 02
Instagram DM automation that captures every warm commenter.
Purpose
An automated engagement workflow built with ManyChat and n8n for viral-content conversations.
How it runs
- 1Monitor posts and Reels
- 2Detect defined keyword comments
- 3Trigger a personalised Instagram DM
- 4Store lead details centrally for CRM
Business impact delivered
Instant engagement Automated capture More conversion opportunities
Marketing IntegrityWorkflow 03
Inventory validation that stops misleading promotions.
Purpose
Every product offer is verified before publishing, and revalidated when stock or discounts change.
How it runs
- 1Verify product and inventory
- 2Validate discounts and expiry dates
- 3Check product URLs
- 4Block offers when any check fails
Business impact delivered
Misleading promotions prevented Fewer advertising errors Customer trust protected
Decision SupportWorkflow 04
A business decision engine that recommends, but never acts alone.
Purpose
Data-driven recommendations keep every business decision under human control.
How it runs
- 1Collect data across ads, web, social, and product
- 2Identify high-performing and weak initiatives
- 3Recommend scale, pause, fix, or investigate
- 4Route every action to human approval
Business impact delivered
Faster decisions Better operational visibility Human oversight maintained
Ad ComplianceWorkflow 05
Compliance validation that protects the ad account.
Purpose
Campaigns are checked against Meta and Google Ads policy before launch and after every change.
How it runs
- 1Review creatives, copy, landing pages, and targeting
- 2Flag policy violations
- 3Recommend corrections
- 4Require approval and revalidate changes
Business impact delivered
Lower ad-rejection rates Accounts protected Ongoing compliance
The through-line
What every result above has in common.
A sharp ICP
Every growth number started by narrowing the target until the message could be personal, not generic.
Structured follow-up
Booked calls came from sequences, not single touches — persistence engineered into the system.
Human in the loop
Automation removed busywork, while people kept control of every decision that carried real risk.
Want results like these for your pipeline?
Tell us your market and stage. We will show you which play fits and what an engineered version would look like for you.