For growing B2B companies

Build the GTM system behind your sales motion.

SilverGTM helps B2B teams find the right accounts, turn them into actionable intelligence, and connect that intelligence to the sales motion.

GTM Engineering for B2B companies ready to build a repeatable, predictable revenue machine.

ICP→
Accounts→
Signals→
Data→
Intelligence→
CRM→
Rep
Experts in
Built and operated GTM systems behind
$0M+
Pipeline
0+
Meetings / month
0%
Peak reply rate
Enterprise meetings
GE HealthcareMedtronicJohnson & JohnsonPfizer
Who this is for

This Is For You If You're

01

Starting outbound

You know who you want to sell to, but don't have the infrastructure to reach them consistently.

02

Already running outbound

You have a motion in place, but too much of the work is still manual, disconnected, or difficult to manage.

03

Selling into hard-to-reach markets

Your best accounts aren't sitting neatly inside Apollo or ZoomInfo. You need custom sourcing, enrichment, research, and qualification.

04

Building a more sophisticated GTM motion

You need your data, signals, CRM, research, and outbound workflows to work together around how you actually sell.

Whether you're building outbound from scratch or improving a motion that's already running, we build the system around your market and sales process.

The problem

Building an outbound system is harder than just sending emails.

  • You don't know which tools you actually need.
  • You don't know how to set up the infrastructure properly.
  • You don't know how to make Clay, your data sources, CRM, and outbound tools work together.
  • You don't have a reliable way to find and qualify the right accounts.
  • Too much of the process still depends on manual research and spreadsheets.
  • You've run outbound before, got results, but never turned it into a repeatable system.
The process

How We Build It.

A six-step process from ICP to working GTM system.

01 / Diagnose

Understand the business

Map how you sell, who you sell to, where data comes from, what tools exist, and where the current process breaks.

GTM motion → ICP → Data → Tools → Bottlenecks
02 / Define

Turn your ICP into rules

Translate the ICP into criteria the system can actually evaluate: accounts, personas, qualification rules, signals, scoring, and exclusions.

Accounts → Personas → Signals → Scoring → Priorities
03 / Source

Build the market

Find the accounts that matter, including the ones traditional databases don't capture cleanly.

Apollo → Sales Navigator → Funding → Filings → Websites → Directories
thenResolve → Deduplicate → Normalize → Structure
04 / Enrich & Understand

Turn accounts into intelligence

Identify the right people, enrich the account, research what's happening, surface buying signals, and score it against your criteria.

Contacts → Firmographics → Technographics → Signals → Research → Score

AI agents and enrichment workflows handle the research that would otherwise take hours manually.

05 / Activate

Put intelligence into action

Connect the system to wherever your team works so useful information automatically reaches the right place.

CRM → Routing → Slack → Rep Workflows → Outbound → Dashboards
06 / QA & Handoff

Make it reliable and yours

Test the data, workflows, integrations, edge cases, and routing logic. Document everything and hand over a system your team can operate.

Test → QA → Document → Launch → Handoff
Proof

GTM Systems, Proven in Production.

AI Reserve · AI Infrastructure

Built the GTM infrastructure that helped find message-market fit.

They were a stealth, recently funded company selling into a very specific emerging market. The challenge wasn't simply finding leads. They wanted to find out who actually responded and what message got them into conversations.

Their target market was recently funded, AI-native startups spending over $50k per month on AI. You don't find these in a database.

How we did it
  • Scraped SEC Form D filings and VC/PE Portfolios for funded companies.
  • Built a tight rubric, and then sent AI Agents to classify each website based on the rubric.
  • Reviewed campaign data to identify who was actually responding and what messages they resonated with. It turned out to be the technical owners of AI: CTOs, Heads of AI, and VP Platform.
Outcome

"The GTM data was insanely valuable."

Meetings booked from the resulting ICP. The GTM data also became a meaningful input into how the team approaches conversations and evaluates fit.

John Snow Labs · Medical AI

Built the outbound infrastructure, then operated it as the SDR.

John Snow Labs was selling AI/ML solutions into medical-device and healthcare-data markets. The goal was to create a repeatable outbound motion capable of reaching enterprise decision-makers and consistently generating qualified pipeline.

How we did it
  • Built prospecting and enrichment workflows using Clay, Apollo, and custom data workflows.
  • Researched and qualified enterprise accounts and identified relevant C-level decision-makers.
  • Built and iterated cold-email frameworks across multiple personas.
  • Managed CRM records and sales notes to maintain clean handoffs to AEs.
  • Operated the outbound motion across phone, LinkedIn, and email, continuously testing targeting and messaging.
Outcome
20+Meetings / month
$2M+Qualified pipeline
Enterprise meetings booked
GE HealthcareMedtronicJohnson & JohnsonPfizer
Pixel Pirate Studios · Video Production

Built the outbound engine for $30K video-production deals.

Pixel Pirate Studios sold high-ticket video production with deals worth around $30K. The challenge was finding companies where that kind of creative spend made sense, then turning those accounts into qualified sales conversations.

How we did it
  • Built the ICP and account criteria around high-value creative buyers.
  • Identified and qualified prospects against the characteristics that made a $30K conversation commercially relevant.
  • Built outbound playbooks, messaging frameworks, and sales assets around the offer.
  • Created and A/B tested cold-email campaigns across target segments.
  • Operated the campaigns end to end, from prospecting through outbound execution.
Outcome
$5M+Pipeline
2%Meeting rate

6–12 qualified meetings / month.

US Magazine Advertising · Local Advertising

Built the outbound system to reach local businesses conventional databases couldn't reliably find.

The client sells $2,500 advertising packages to local businesses in specific metros. Apollo and ZoomInfo couldn't reliably surface the businesses they needed in the right geographic areas, so the outbound motion needed a different approach.

How we did it
  • Built a targeted account universe from Google Maps, focused on the client's specific metro.
  • Targeted professional services, healthcare, home services, and retail businesses.
  • Built separate campaigns around the benefit that mattered to each business type — more clients, more jobs, or more customers.
  • Personalized outreach to the exact city and business type rather than sending generic local-business messaging.
  • Ran approximately 3 campaigns simultaneously, continuously refining the targeting and messaging.
15+Meetings / month

~1 in 6 meetings closed. An ongoing outbound motion generating qualified conversations with local business owners.

PE Growth Partners · Private Equity & Investment Banking

Built the data and outbound system for a market conventional databases couldn't cleanly capture.

PE Growth Partners needed to reach decision-makers across private equity and investment banking, where firm-level information, portfolio data, and decision-maker contacts were fragmented across multiple sources.

How we did it
  • Matched Crunchbase data with SEC Form ADV filings to estimate firm AUM without relying on a premium data source.
  • Used AI agents to extract portfolio companies and sectors from PitchBook profiles.
  • Built an enrichment waterfall to identify the relevant decision-makers.
  • Connected the resulting intelligence to Email Bison for campaign execution.
  • Routed positive replies directly into Slack for immediate follow-up.
  • Ran 12 campaigns per month, continuously testing messaging and targeting.
2.5%Reply rate

~50% positive reply rate. Meetings booked with Lex Capital Group and Aurum Capital.

Who we are

Who We Are.

SilverGTM was built by Victor Kalu, a GTM engineer who started in outbound and moved into building the systems behind it.

The work has spanned prospecting, enterprise sales, data pipelines, Clay workflows, enrichment systems, scoring logic, market intelligence, and outbound infrastructure.

The goal is simple: build GTM infrastructure that sales teams actually use.

Victor Kalu, founder of SilverGTM
Victor Kalu · Founder, GTM Engineer

Your GTM stack is already expensive. Make it work together.

Build the system that gives your sales team better data, clearer priorities, and more leverage.

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