AI Systems & Automation Portfolio

Built to run.Not to impress.

Five production AI systems designed around specific business problems — research, competitive intelligence, lead generation, marketing automation, and personal branding. Built on n8n, OpenAI API, and Python to solve operational constraints, not demonstrate technical capability.

01 · Marketing Research02 · Competitor Intelligence03 · Lead Generation04 · Marketing Automation05 · Personal Branding
5
Systems Built
3
Tech Layers
100%
Automated
∞
Ongoing
Browse Systems View Services →
What These Systems Solve

Every system starts
with a business problem.

No tool was chosen before the problem was defined. Each system exists because a real operational constraint needed a structural solution — not a workaround.

Problem 01

Research takes days. Competitive and market intelligence requires hours of manual source-gathering, synthesis, and formatting before it's usable.

solved by

AI Research + Competitor Systems

Hours → Structured intelligence

Problem 02

Pipeline is inconsistent and manual. Prospecting, qualifying, and reaching out to leads requires repetitive effort that doesn't scale with team size.

solved by

AI Lead Generation System

Manual effort → Automated pipeline

Problem 03

Content and marketing workflows are repetitive. Creating, distributing, and maintaining consistent brand output requires time that compounds weekly.

solved by

AI Marketing Automation + Branding

Repetitive work → Automated systems

Business Outcomes

From → To

Slow researchResearch faster

Compress Research Timelines

Market and competitive research that previously required days of manual effort is compressed into structured, decision-ready output delivered in hours.

From → To

Inconsistent pipelineBetter leads

Generate Better Leads

Automated prospect discovery and qualification that surfaces the right opportunities continuously — improving targeting precision without increasing manual overhead.

From → To

Manual repetitionAutomated work

Automate Repetitive Work

Marketing workflows that follow predictable patterns — content generation, distribution, reporting, outreach — are automated end-to-end, freeing capacity for higher-order work.

From → To

Data without insightBetter decisions

Make Better Decisions

Structured business intelligence delivered in formats that directly inform strategy — not raw data or log files, but synthesised analysis with clear implications.

Five Systems

Production AI systems,
built for specific business problems.

Each system is designed around a defined operational constraint — and built to run continuously without manual intervention after deployment.

🔬

System 01 · AI Research

AI Marketing Research System

Business problem: Research timelines are too slow to serve live strategy decisions.

The Problem

Market research is valuable only when it arrives in time to inform decisions. Traditional research cycles — manual source identification, synthesis, and formatting — take days that strategy timelines don't have. The result is decisions made on stale or incomplete intelligence.

How It Works

01n8n triggers research pipeline from defined source list or query input
02OpenAI extracts, synthesises, and structures intelligence from raw source material
03Structured research report delivered to Google Sheets with categorised findings

What It Produces

  • Structured market intelligence reports ready for immediate use in strategy decisions
  • Research cycle compressed from days of manual work to hours of automated processing
  • Consistent research format across all outputs — comparable, searchable, and archivable
n8nOpenAI APIGoogle SheetsWorkflow Automation
Related Service
🧠

System 02 · Intelligence

AI Competitor Intelligence System

Business problem: Competitive landscapes shift faster than manual monitoring can track.

The Problem

Competitors move daily — new content, pricing shifts, positioning changes, product updates. Manual competitive monitoring is either too infrequent to be useful or too time-consuming to be sustainable. Most organisations track competitors reactively, after the signal has already become obvious.

How It Works

01Python scripts crawl defined competitor sources on a scheduled trigger
02OpenAI analyses content for positioning shifts, messaging changes, and strategic signals
03Structured competitive intelligence report logged to database with delta tracking

What It Produces

  • Always-on competitive monitoring that surfaces signals before they become obvious to the market
  • Structured competitor database with historical tracking — see how rivals have evolved over time
  • Actionable intelligence reports that directly inform positioning and strategy decisions
PythonOpenAI APIGoogle SheetsScheduled Automation
Related Service
⚡

System 03 · Pipeline

AI Lead Generation & Outreach System

Business problem: Inconsistent lead flow is a systems failure, not a sales failure.

The Problem

Most lead generation processes are either entirely manual — requiring consistent effort that doesn't scale — or poorly targeted, generating volume without quality. The result is a pipeline that fluctuates with team capacity rather than running as a reliable business system.

How It Works

01n8n pipeline sources prospects matching defined ICP criteria from target channels
02OpenAI qualifies leads against ICP and generates personalised outreach messages with contextual relevance
03Qualified leads and messages routed to CRM with follow-up sequences triggered automatically

What It Produces

  • A continuously running pipeline that surfaces qualified prospects without manual prospecting effort
  • Context-aware personalised outreach generated at scale — improving response rates vs generic templates
  • Full CRM integration with automated follow-up — time between prospecting and first contact reduced from days to hours
n8nOpenAI APICRM IntegrationOutreach Automation
Related Service
⚙️

System 04 · Automation

AI Marketing Automation System

Business problem: Marketing execution is bottlenecked by repetitive, high-frequency production work.

The Problem

Marketing teams consistently lose capacity to work that is predictable, repetitive, and rule-based — content generation, reformatting for different channels, distribution scheduling, and performance reporting. These tasks follow patterns that can be automated end-to-end, freeing teams for strategy and relationship work.

How It Works

01Long-form content or source brief entered as input trigger to the n8n pipeline
02OpenAI generates channel-specific content variants — LinkedIn posts, email copy, summaries, social assets
03Formatted outputs routed to appropriate channels or content database for review and scheduling

What It Produces

  • One content input repurposed into multiple channel-ready formats — eliminating manual reformatting work
  • Brand-consistent content output at scale — maintaining tone, voice, and messaging across every asset
  • Full marketing workflow automation from content creation through distribution to reporting
n8nOpenAI APIGoogle SheetsContent Workflows
Related Service
👤

System 05 · Branding

AI Personal Branding System

Business problem: Consistent personal brand output requires production effort that competes with the actual work.

The Problem

Building a strong professional brand requires consistent, high-quality output over extended time — daily or weekly content, strategic positioning, audience engagement. For most professionals, this consistency is the constraint: not lack of ideas, but lack of a system that makes showing up continuously sustainable alongside primary work.

How It Works

01Topic ideation pipeline generates content ideas aligned to brand positioning and audience signals
02OpenAI generates on-brand LinkedIn posts, articles, and engagement responses calibrated to voice and audience
03Content routed to posting workflow with engagement tracking and performance signals fed back into ideation

What It Produces

  • A complete personal brand production system — from topic ideation through content creation to publishing and engagement tracking
  • Consistent brand voice maintained across all output — audience experiences the same positioning regardless of post volume
  • Performance feedback loop — engagement signals feed back into content strategy, improving output over time
OpenAI APIPythonGoogle SheetsLinkedIn Workflow
Related Service
Architecture

Three layers.
All connected.

Every system in this portfolio is built on the same three-layer architecture — orchestration, intelligence, and data. The combination is what makes them production-grade rather than experimental.

Layer 01 · Orchestration

n8n Workflow Engine

The coordination layer — manages triggers, data routing, conditional logic, and the sequencing of every automated step. n8n provides visual workflow architecture that makes complex pipelines maintainable and auditable.

n8nWebhooksScheduled TriggersConditional LogicAPI Routing

Layer 02 · Intelligence

OpenAI API

The reasoning layer — handles extraction, synthesis, generation, and classification. Prompt engineering determines output quality; the intelligence layer is only as good as the instructions it receives and the structure it's given to work within.

OpenAI APIGPT ModelsPrompt EngineeringStructured OutputContext Windows

Layer 03 · Data

Python · Sheets · Storage

The persistence layer — stores structured outputs, manages data pipelines, enables historical comparison, and serves as the interface between automated systems and human users. Python handles data transformation; Sheets provides accessible, queryable output storage.

PythonGoogle SheetsExcelData StructuringPipeline Management

How the layers connect

n8n orchestrates
OpenAI reasons
Sheets / Python stores
Output delivered

n8n manages the sequence and routing of every step. OpenAI receives structured inputs and returns structured outputs. Python and Google Sheets persist, format, and surface those outputs to end users. No layer is optional — each depends on the one before it. This architecture is what makes the systems maintainable and extensible over time.

Design Philosophy

How I think about
building AI systems.

Three principles that run through every system in this portfolio — from the first architecture decision to the final output format.

01

Start with the business problem.

Never with the tool.

Every system here was built backwards from a specific operational constraint — not built forward from a technology. The tool choice follows from the problem definition. When the problem is research velocity, the answer is an automated pipeline. The technology is always in service of the business outcome, never the other way around.

02

Systems should run without you.

If it needs weekly intervention, it's not a system.

A workflow that requires manual triggering, daily oversight, or regular correction is an assisted process — not a system. Every system here is designed to run continuously and autonomously after initial setup and calibration. The test: can it produce consistent output for a month without manual intervention?

03

Output must be usable.

Not raw data. Not a log file. A decision.

The most common failure mode of AI systems is producing output that requires significant human processing before it's actionable. Every system here produces output that can be acted on directly — structured reports, prioritised leads, formatted content, specific recommendations. If someone needs an hour to process the output before using it, the system has failed.

Building Next

What’s in the pipeline.

The systems portfolio is an active practice, not an archive. Three new systems are in various stages of design and development.

In Progress

AI Business Dashboard v2

Expanding the existing Power BI + Python + Claude API dashboard into a full automated intelligence layer — with scheduled data pulls, AI-generated narrative summaries, and strategic performance flagging built into the reporting workflow.

Power BIPythonClaude APIAutomated Reporting
Planned

AI Market Monitoring System

A continuous market signal monitoring system — tracking industry news, funding announcements, regulatory changes, and emerging trends across defined market categories, with AI-synthesised weekly intelligence briefings delivered automatically.

n8nOpenAIMarket IntelligenceTrend Monitoring
Planned

AI Strategic Report Generator

An automation layer built directly on the J.A.R.V.I.S. framework — a system that orchestrates the seven research layers programmatically, feeding AI-gathered data into the analytical structure to accelerate the production of full strategic analyses.

J.A.R.V.I.S.n8nOpenAIStrategic Analysis

From Systems to Services

These systems are available as services.

Every system on this page has a corresponding service offering — adapted to your business context and deployed to your operational environment.

Explore Services Get In Touch →

Explore the rest
of the portfolio.

The AI systems are one part of a broader body of work spanning strategic analysis, marketing, and the Marketing J.A.R.V.I.S. framework.

Marketing J.A.R.V.I.S. — Strategic FrameworkFull Portfolio — All WorkAbout — The Person Behind the Work