I build scoped agents, automation and custom software that survive real workflows, with measurement and handover built in.
AI projects stall when nobody owns the boring bits.
The demo is not the hard part. The hard part is choosing the right workflow, connecting the right data, setting guardrails, measuring value and handing it over so people trust it and use it.
AI Readiness Audit
You see AI saving time, but the useful start point is fuzzy.
Problem
The team has ideas, tools and pressure to move. The workflow worth fixing first is not obvious.
Risk
Without a workflow map, success criteria and a risk check, weeks go into automating the wrong thing.
Fix
I audit the process, data, users and handoffs, then give you a prioritised AI readiness plan.
Best for: AI readiness assessment, workflow automation planning, governance-first AI.
Find out moreCustom AI Agent Build
You need an agent that does a real job.
Problem
A generic chatbot will not handle messy data, unclear permissions or human review points.
Risk
The agent looks useful in a demo, then breaks when the real workflow gets involved.
Fix
I design and build scoped Copilot Studio agents, automations and custom workflows around the real task.
Best for: Custom AI agents, Copilot Studio agents, business process automation.
Find out morePrototype-to-Production Sprint
Your proof of concept works, but nobody trusts it in production.
Problem
The idea has legs, but ownership, measurement, testing and support are still vague.
Risk
No guardrails, no handover and no success signals means the pilot quietly dies.
Fix
I turn the prototype into a production-ready pilot with testing, documentation and ownership built in.
Best for: AI proof of concept, production AI, safe AI implementation.
Find out more- What is an AI readiness assessment?
- A short review of your workflow, data, users, risks and success criteria. It shows which AI use case is worth building first.
- When should a business build a custom AI agent?
- When the task needs business context, permissions, handoffs or review steps a generic chatbot misses.
- Why do AI proof-of-concepts fail before production?
- They often miss guardrails, measurement, support ownership and handover. The idea works, but the operating model is missing.
Proven Impact
Some projects and contributions I'm proud to have been part of
PetsDetect & Microsoft Copilot
AI Solutions Engineer and lead developer for PetsDetect, a Microsoft Copilot Studio agent supporting retail fraud case compilation for skilled human review.
Humanising Public Health Data
Skilled Volunteer responsible for core UI components, dark mode implementation, and accessible data definitions for the Scottish COVID-19 dashboard.
Skilled Volunteering
How giving time to tech for good work built real delivery confidence while supporting charities and public interest projects.
What Others Say
Short notes from people who have worked with me on production AI, purpose-led websites and public-good delivery.
"From concept to reality, Becky worked with the business, Microsoft product teams and internal teams at Pets at Home to deliver a working solution in production."
"She took the time to understand, research, explore and refine our ideas, even when we were still figuring them out ourselves."
"Becky took a lead role in improving the user interface of the Scottish Covid Dashboard, researching best practice and accessibility requirements."
My Approach: Building with Purpose
I believe the most impactful technology is built with a deep understanding of human needs. My work focuses on crafting solutions that are not just technically sound, but also ethically responsible and genuinely beneficial to people, leveraging the right tools for the job.
Read My Responsible AI Use Pledge