Case Studies

How we build revenue
operating layers

Anonymized examples of how Ombrik diagnoses, builds, and operates the systems that make growth repeatable.

Turning pipeline noise into forecast clarityFeatured
Series B SaaS

Turning pipeline noise into forecast clarity

A fast-growing SaaS team had demand, headcount, and tools. What they did not have was a revenue operating layer everyone could trust.

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Building a shared operating layer across the portfolio
PE / VC Portfolio Ops

Building a shared operating layer across the portfolio

A lean investment team needed sharper visibility across portfolio company growth motions without forcing every operator into the same playbook.

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Turning market signals into GTM action
FinTech

Turning market signals into GTM action

A fintech company had more data than its sellers could use. Ombrik built the signal layer that turned noise into next-best action.

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Engineering GTM experiments before scale
Pre-Series A

Engineering GTM experiments before scale

A pre-Series A team needed to validate where the market was pulling before hiring around assumptions.

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From zero RevOps infrastructure to a working GTM engine
Series A Startup

From zero RevOps infrastructure to a working GTM engine

A newly funded startup needed the operating layer for sales, marketing, and customer success before growth exposed every gap.

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From GTM workshop to embedded managed service
EdTech

From GTM workshop to embedded managed service

A workshop exposed enough operating friction that the client moved from advisory into a full managed GTM build.

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Automating the manual work inside pipeline operations
HealthTech

Automating the manual work inside pipeline operations

A healthtech revenue team was losing hours each day to updates, reconciliations, reminders, and manual pipeline hygiene.

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Building the RevOps bench around the system
Series D Scale-Up

Building the RevOps bench around the system

A scale-up needed more than hires. It needed the right operating roles, ownership model, and nearshore support to run the GTM engine.

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Taking a GTM proof-of-concept into production
DevTools

Taking a GTM proof-of-concept into production

A devtools company needed to prove a technical GTM automation idea quickly, then turn it into a production-ready workflow.

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Building an AI agent for deal risk and priority
Cybersecurity

Building an AI agent for deal risk and priority

A cybersecurity sales team needed a better way to identify deal risk before it showed up in missed forecasts.

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Modernizing a Frankenstack into AI-native RevOps
Series C B2B

Modernizing a Frankenstack into AI-native RevOps

A scaling B2B company had years of patched workflows, duplicate fields, brittle automations, and reports nobody fully trusted.

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Replacing manual outbound with an engineered system
B2B Marketplace

Replacing manual outbound with an engineered system

A marketplace team needed outbound to become a repeatable revenue channel instead of a collection of rep-specific workflows.

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Every engagement starts with a strategy call. We map your systems, identify what's broken, and outline the path forward.