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Work

A closer look at the work behind the systems.

A featured partnership, experience from more than six years in B2B operations, and selected systems I have built in the Lab.

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Featured partnership

Strategic Computing

Connecting outreach, proof and the next conversation.

Strategic Computing is a Dublin-based specialist in enterprise negotiation and IT procurement. Its commercial journey needed to make better use of the expertise and customer evidence already in the business.

Start with the journey

I began by examining what happened after someone encountered the business: where outreach led, what proof they could inspect, how interest was captured and what supported follow-up.

That connected the diagnosis to a practical set of changes across the buyer journey and HubSpot.

The foundational work

I worked on HubSpot restructuring, contact intelligence and structured outreach. A landing page and lead asset gave outreach a destination; existing customer proof was brought into the market-facing journey.

The point was to connect an initial expression of interest to useful evidence and a clear next step, rather than leave each activity to carry the commercial conversation on its own.

Completed foundation, continuing partnership

The foundational diagnosis and build are documented in the published case study. The partnership continues around the commercial systems supporting the business.

The design aim is a setup proportionate to a founder-led consultancy, with a clear path from interest through capture to follow-up.

“Working with Osama brought a lot more structure and direction to what I was trying to build. He helped make sense of the tools, the outreach, and the bigger go-to-market picture, and he was especially strong at bringing HubSpot and AI into the process in a way that was practical and useful.”

Ray Murphy, CEO & Founder, Strategic Computing

Illustrated journey, in two connected layers

Buyer-facing

  1. 01Target accounts and outreach
  2. 02Useful content and proof
  3. 03Consultation or enquiry

An enquiry enters the operating layer, where the systems decide what happens next.

Operating layer

  1. 01Contact and account intelligence
  2. 02Capture and context
  3. 03HubSpot, lifecycle and ownership
  4. 04Follow-up
  5. 05Signals and learning
Illustrated journey from the foundational work.
Read the published case study(opens in a new tab)Discuss a similar system problem

Selected Experience

Six-plus years inside B2B marketing operations and revenue systems.

Before MarOps Lab, I worked across technology businesses in SaaS, fintech, insurance and cybersecurity, most recently as Associate Director, Marketing Operations at 2X.

That experience includes lifecycle and qualification design, nurture, routing, CRM workflows and connected marketing tools. It is the background I draw on when tracing a commercial requirement through the system that has to implement it.

Career context

Most recently Associate Director, Marketing Operations at 2X.

Employment history, not a MarOps Lab client engagement. 2x.com(opens in a new tab)

Selected organisations from my practitioner experience

  • Digital Hands
  • HRsoft
  • Duck Creek
  • Picus Security
  • Sandler
  • Hyland
  • Baldwin Group
  • Lytho

Built in the Lab

Systems I build to examine how the work can be done.

The Lab is a working environment for research, prototypes and internal tools. I use it to explore practical questions about CRM, data, automation and AI, including what makes an output useful and what happens when the evidence is incomplete.

These are selected builds. Further work appears when there is something concrete worth showing.

Account Intelligence

Purpose

Prepare account context before a commercial decision.

The work

Research brings public evidence and available account context into a structured assessment: what is happening, why it might be relevant and what is still unknown.

Why it is useful

I can review the evidence before deciding where to put attention. An unanswered question stays visible instead of becoming an assumed buying situation.

The possible human decisions are ACT, HOLD or no meaningful signal. The selected example shows weak evidence and a recommended verification step; it does not record a final commercial decision.

Inspect the selected research output

Trigebra

Purpose

Turn HubSpot configuration evidence into diagnostic findings a practitioner can examine.

The build

Trigebra reads portal and configuration data through the HubSpot API. Deterministic checks collect evidence, and an LLM synthesises findings within those constraints, with confidence treatment and QA.

Why it is useful

The finding can be examined alongside the evidence that supports it. Where information is insufficient, the diagnostic can return an unassessable result rather than force a conclusion.

How a finding is assembled

Build architecture
  1. 01HubSpot API
  2. 02Configuration evidence
  3. 03Deterministic checks
  4. 04Constrained synthesis
  5. 05Confidence and QA
  6. 06Finding

Explore Trigebra(opens in a new tab)

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