pl8ypus

About Greg / pl8ypus

I spent 20 years inside marketing systems. Now I build the AI layer above them.

pl8ypus is my AI builder identity and portfolio. It is built on 20 years of working across the Eloqua and Salesforce stack as a lead developer and consultant, including enterprise delivery environments connected to firms such as Infosys, Deloitte, and PwC.

The switch into AI development was not a reset. It was a continuation. I moved toward AI because I see systems, I see the gaps between tools, teams, data, and process, and I know where automation needs governance before it can be trusted.

Origin Story

The AI work comes from years of fixing the places where enterprise marketing systems break.

From platform specialist to AI builder

My background is not generic AI enthusiasm. It is marketing operations under real pressure: Eloqua programs, Salesforce handoffs, campaign architecture, forms, landing pages, data capture, reporting, localisation, QA, stakeholder reviews, and the operational mess that appears when teams, platforms, and deadlines collide.

Around three years ago I started making the switch into AI development because the pattern became obvious: the next major advantage was not another isolated tool. It was an orchestration layer that could sit across existing systems, close the gaps, reduce manual work, and still keep the controls that enterprise teams need.

> 20 years on Eloqua, Salesforce, and marketing operations workflows

> Lead developer and consultant experience in enterprise delivery environments

> Consulting context connected to Infosys, Deloitte, and PwC scale expectations

> Master's degree in Digital Marketing, with build experience grounded in business outcomes

> AI builder focus: plug the gaps, expose the controls, and make systems usable

Why The Switch

I became an AI builder because the gaps are now bigger than any single platform.

Enterprise marketing teams already have platforms. They have CRMs, automation tools, analytics tools, translation vendors, reporting dashboards, spreadsheets, approval processes, and service desks. The problem is that work still leaks through the cracks: copy and paste translation, inconsistent campaign data, manual QA, disconnected reporting, brittle handoffs, and unclear ownership when something fails.

I see systems

Not isolated tasks

I look for the source, state, owner, rule, handoff, failure mode, and recovery path. That is where AI can become useful rather than impressive for five minutes.

I plug gaps

Between people and platforms

The strongest AI builds often sit between existing systems, turning messy work into a structured route with rules, checks, approvals, and evidence.

I govern output

Because trust is the product

AI output needs boundaries before it enters real operations: protected content, QA gates, approval, versioning, rollback, and clear evidence of what happened.

Career Spine

The story is not consultant to coder. It is systems operator to AI systems builder.

01

Enterprise marketing systems

Years of hands-on work across Eloqua, Salesforce, campaign operations, integrations, forms, landing pages, segmentation, tracking, and reporting.

02

Consulting delivery discipline

Lead developer and consultant work shaped by enterprise expectations: clear ownership, controlled releases, stakeholder explanation, QA, and auditability.

03

Digital marketing strategy

A Master's in Digital Marketing gives the build work a business frame: audience, conversion, channels, data, positioning, and the operational cost of slow manual work.

04

AI systems builder

The current focus is governed AI systems for translation, marketing intelligence, review workflows, and automation that can be demonstrated, inspected, and improved.

What pl8ypus Is

A public proof layer for the AI builder work.

pl8ypus gives this work a home outside client delivery. It is where I can show the build logic, document the architecture, explain the controls, publish the progress, and turn the active systems into demos that make sense to builders, marketers, senior stakeholders, and event organisers.

Builds

Working systems

Active AI systems with a visible route from problem to architecture to demo.

Proof

Evidence layer

Screens, diagrams, build notes, decisions, controls, and delivery status.

Voice

Builder narrative

A place to explain why the systems matter and what the build is teaching.

Stage

Demos and speaking

A surface for live demos, event conversations, and serious AI systems discussions.

Operating Model

Frame the workflow. Build the proof. Add the controls. Ship the evidence.

01

Frame

Define the user, workflow, input, output, risk, success measure, and decision point.

02

Build

Create the smallest useful system that proves the process under realistic conditions.

03

Govern

Add rules, review states, version control, audit records, QA checks, and rollback paths.

04

Show

Turn the build into a demo, page, log entry, architecture note, or stakeholder readout.

Active Builds

The current systems portfolio.

Build 01

Translation AI

A governed AI orchestration system for translating structured marketing assets while protecting formatting, terminology, review states, and audit evidence.

Open Translation AI

Build 02

Marketing Intelligence AI

A governed intelligence system concept for campaign, competitor, social, search, web, and performance signals with AI-ready summaries.

Open Marketing Intelligence AI

Contact

Want to discuss a governed AI build?

Use the contact form for demos, speaking requests, collaborations, or practical AI systems conversations.