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AI-enabled operations · Interactive prototype

Operations Intelligence Hub

From operational complexity to intelligent, actionable workflows.

Operations Intelligence Hub command centre interface with prioritised operational items and an operations health score

Inspired by real experience coordinating international publishing, partnerships and operational workflows across Spain and Latin America, I designed Operations Intelligence Hub to explore how fragmented operational processes could be transformed into a centralised, intelligent system.

The concept is industry-agnostic and designed to demonstrate how AI and automation can support better operational decision-making without replacing the tools teams already use.

Problem

Operational teams often manage projects, partners, deliverables, deadlines, issues and communications across multiple systems.

The challenge is not simply storing more information. It is identifying what requires attention and turning that insight into action.

Solution

Operations Intelligence Hub creates an intelligence layer above existing operational tools. It analyses workflow signals to identify:

  • Priorities
  • Risks
  • Bottlenecks
  • Delayed responses
  • Partner issues
  • Deadline risks
  • Required follow-ups

It then recommends or triggers actions through tools such as Asana, n8n and email.

My approach

1Real operational experience
2Workflow analysis
3Problem identification
4Process redesign
5AI decision support
6Automation
7Human oversight

Key features

  • AI Operations Copilot
  • Smart Operations Inbox
  • Operations Health Score
  • Partner Health
  • Bottleneck Detection
  • Risk Analysis
  • Weekly Team Planning
  • Asana Task Automation
  • Email Follow-up Automation
  • Scenario Simulation
  • Executive Reporting

Automation architecture

1Operational data
2Operations Intelligence Hub
3AI analysis
4Human approval when required
5n8n
6Asana / Email
7Updated operational status

Human in the loop

AI is used to identify patterns, prioritise information and recommend actions, while important external communications and operational decisions can remain subject to human approval. This keeps automation useful while maintaining operational control.

Scope & transparency

  • Live functionality: the interactive interface, prioritisation logic, filtering, pipeline movement, QA checks, scenario simulation and generated planning and reporting views.
  • Prototype functionality: the AI Copilot answers and risk analysis are built on rule-based logic over a fictional demo dataset.
  • Simulated integrations: Asana, n8n and email actions are demonstrated end to end but are not connected to live systems, and no real emails are sent.
  • All companies, partners, people and figures in the demo are fictional. No confidential or client information is used.

Outcome

A functional portfolio prototype demonstrating how real operational experience can be translated into a scalable system for decision support, workflow optimisation and AI-enabled automation.

Skills demonstrated

  • Project Operations
  • Process Improvement
  • Workflow Design
  • Stakeholder Operations
  • AI Workflow Design
  • Automation Strategy
  • Operational Risk Analysis
  • n8n
  • Asana
  • AI-assisted Decision Support

Where this came from

This prototype is the designed answer to the operational challenges described in my Publishing & Content Operations case study: real experience, identified challenges, improved solution.

Have an operational challenge or an idea?

Whether you're looking for someone to join your team or want to explore an AI-enabled solution for your organisation, I'd be happy to hear about it.

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