#FoundHerWorld – Lucy Yu

Lucy Yu Spent 45 Minutes Finding One Plumber. So She Built the One App That Does It All.

Five apps open. Three browser tabs. A handful of reviews you’re not sure you trust. And still no certainty about who’s actually showing up at your door.


It started with a plumber. Lucy Yu spent 45 minutes hunting across platform after platform just to book a single service, never quite confident in who she was letting into her home. But the deeper she looked, the clearer it became that the problem wasn’t plumbers. It was everything. Finding a tutor, a cleaner, a nail tech, a dog walker, a designer, a personal trainer every one of them meant a different app, a different search, the same friction. People had simply learned to tolerate it.


Lucy stopped tolerating it. A three-time founder, she’d experienced the frustration firsthand — and she realized the answer wasn’t another single-category app stacked on top of the pile. It was one place for all of it.
What she found on the provider side was just as broken. Service providers such as plumbers, cleaners, tutors, stylists, people building real livelihoods were trapped in a pay-to-play lead-generation model that charged them fees whether or not they ever got the job. The platforms profiting from both sides had optimized for transactions, not trust.


“Services were broken on both sides,” she says. “Customers are stuck juggling a dozen apps, providers paying lead fees with no guarantee of work. So we built the ultimate all-in-one AI marketplace — one app for every service, where customers feel safe, and providers join free, learn skills, post social feeds, and only pay when they actually earn.”


FairyAiO is the unified answer: a single platform serving customers, business providers, and individual providers across every category imaginable home, beauty, wellness, education, professional, and beyond delivered however you need it, whether someone comes to you, you go to them, or it happens online. It’s powered by AI that matches, predicts, and acts before users even know they need something.
Pre-launch and building two-sided liquidity across her Seattle and New York City markets, Lucy is raising her pre-seed round while finishing the MVP and building in public, sharing every lesson along the way.
The services market has long rewarded whoever could hold the most friction. Lucy Yu is betting the future belongs to whoever can remove it.


Fairy AiO is the unified answer, a single platform serving customers, business providers, and individual providers, powered by AI that matches, predicts, and acts before users even know they need something. Pre-launch and building two-sided liquidity across her Seattle and New York City markets, Yu is raising her pre-seed round while finishing the MVP and building in public, sharing every lesson along the way.
The home services market has long rewarded whoever could hold the most friction. Lucy Yu is betting the future belongs to whoever can remove it.

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#FoundHerWorld – Sinmi Adeoye-Esene

The Deals That Never Close: How Sinmi Adeoye-Esene Is Building the Trust Layer Global Trade Has Always Needed

Somewhere between a copper mine in Zambia and an institutional investor in London, a deal dies. Not for lack of supply. Not for lack of demand. For lack of proof.

Who is the counterparty, really? Is the origin verified? Does this transaction meet compliance standards? Can it actually close? In the world of critical minerals, energy, and commodity trade, these questions have historically been answered with phone calls, relationships, and hope. For the capital providers who need certainty before they move, that has never been enough.

Sinmi Adeoye-Esene saw this breakdown up close. As an Energy Futures Lab Fellow working across complex global trade corridors, she watched deals collapse not because the fundamentals were wrong, but because no one could verify the people, the provenance, or the readiness on either side of the table. Buyers couldn’t trust suppliers. Suppliers couldn’t prove compliance. Capital couldn’t confirm what could actually close.

“The broken system was the global trade without trust,” she says. “Critical minerals and energy deals were moving through opaque networks where capital could not verify who was real, what was compliant, or what could close. I built Daniola to make trade verifiable, bankable, and ready for institutional capital.”

Daniola is the infrastructure layer she wished had existed. Using AI-powered verification and deal intelligence, it gives every party in a complex transaction, suppliers, buyers, investors, and development finance institutions, a shared, auditable picture of readiness. The company’s proprietary CloseReady™ framework translates that verification into something institutional capital can act on.

Based in Alberta and operating across active corridors in Zambia, Nigeria, and the DRC, Adeoye-Esene is now converting that framework into repeatable, scalable products, including Africa Trace™ and the Daniola Alignment Score™, built for the volume of deals the energy transition demands.

Global trade has always run on relationships. Sinmi Adeoye-Esene is making sure it can finally run on proof.

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#FoundHerWorld – Yogita Parulekar

Yogita Parulekar Spent Years Watching Over and Over Again Security Teams Unable to Fix Misconfigured Infrastructure, InviGrid with Secure By Design Infrastructure Is Her Way Out of the Loop

The vulnerability report lands on the security team’s desk. They flag it. They escalate it. And then, almost inevitably, it stays unfixed, because fixing it properly would mean rebuilding the infrastructure which is expensive and time consuming.


This is the quiet dysfunction at the heart of enterprise security: a system designed to find problems it was never empowered to prevent. The underlying architecture and the code needs to be fixed but needs expertise and time. Next quarter, the report looks familiar.


Yogita Parulekar ran security and IT long enough to know this loop by heart. Reactive by design, expensive to escape, and increasingly untenable as the pace of development accelerated around it. The tools were built for a world where infrastructure moved slowly, and developers waited. That world is gone.


AI-driven development, what the industry is beginning to call vibe coding and now vibe engineering, has changed the equation entirely. Citizen developers are building and deploying at speeds that leave traditional infrastructure and compliance processes gasping to keep up. Security, already reactive, is falling further behind.


“With AI vibe coding, citizen developers expect infrastructure to be built at the same pace at which they are developing their applications,” Parulekar says. “We redesigned the broken SDLC-infraOps process that allows developers to deploy audit-ready, secure infrastructure rapidly.”


Invi Grid is her answer to the acceleration problem, a platform that makes secure, compliant cloud infrastructure the default rather than the afterthought. Targeting CIOs, CTOs, and CISOs at regulated enterprises with significant cloud investment, the company is defining an entirely new category: Secure Agentic Infrastructure. Patents approved. Customers validating. Partners aligned.
The security industry has spent decades learning to move fast after a breach. Yogita Parulekar is building the infrastructure that makes the breach less likely to begin with.

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#FundHerWorld – Chukwufumnanya Michelle Isichei

Millions of Gig Workers Are One Bad Month Away From Losing Everything. Chukwufumnanya Michelle Isichei Is Building the Net.

The moment you leave a traditional job, something disappears so quietly you almost don’t notice it until you need it.
Health coverage. Income protection. The quiet assurance that if something goes wrong, there is a system designed to catch you. For decades, these protections were built into formal employment, so automatic that most workers never had to think about them. Then the gig economy arrived, and millions of people stepped into a new way of working without any of those protections following them.


Chukwufumnanya Michelle Isichei experienced that shift herself. After years in traditional banking, where insurance and financial protection were simply part of the package, she transitioned into the remote and gig economy space. Suddenly, something as basic as protection became her responsibility to figure out.
She did. But what struck her wasn’t just the inconvenience; it was the scale of the problem.


Millions of freelancers, remote workers, delivery riders, and platform workers across emerging markets were building livelihoods entirely outside the safety systems traditional employment once guaranteed. One unexpected illness, one lost contract, one bad month, and everything they had built could begin to unravel.


What began as a personal realization quickly became a much larger question: how do you build financial protection for an entire generation of workers operating outside traditional systems?
“Insurance was automatic in traditional jobs, but in the gig economy, you’re on your own,” she says. “I’m building GigSecure to change that, creating simple, flexible protection designed for how gig workers actually live and earn.”


GigSecure is an insurance platform built around the realities of irregular income. Its AI-powered risk assessment helps tailor coverage to how gig workers actually earn and live, rather than relying on traditional insurance models that often exclude them. A marketplace for tailored insurance premiums is rolling out in the coming weeks, connecting gig workers with insurers and fintech partners willing to meet them where they are.


The MVP is live. Demand is growing. And millions of gig workers have waited far too long for financial protection designed with them in mind.

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#FoundHerWorld – Lisa Ann Edwards

Lisa Ann Edwards Saved a Coaching Program by Proving Its ROI. Twenty Years Later, She’s Doing the Same Thing for Enterprise AI.

The program was working. The executives just couldn’t see it.


Three months into her first talent management role at an organization where every executive had a coach, and coaching was genuinely embraced, Lisa Ann Edwards watched the budget get cut. Not because the results weren’t real. Because no one had built the financial case to prove they were.


She built it. The coaching program came back. And the question that forced her hand, “What are we actually getting back from this?” never really left her.
That was twenty years ago. Since then, Edwards has collected more than two million data points on leadership performance, coaching effectiveness, and ROI across some of the most demanding organizations in the world. The methodology she developed to answer one CFO’s skepticism became the foundation of a career, and eventually, a company.


Excelia exists because the question hasn’t changed. It has simply gotten more expensive.
“Companies are spending millions on AI and still can’t explain the business impact,” she says. “I built Excelia to connect AI, coaching, workflow improvement, and ROI so organizations can turn AI from expensive experimentation into measurable ROI.”


The platform combines performance coaching with technology to help enterprise organizations identify high-value AI workflows, build practical solutions, measure impact, and surface it all in an executive dashboard that speaks the language CFOs actually need. It is, at its core, an argument that enterprise AI is not purely a technology problem, it is a coaching, performance, and implementation problem with a financial model attached.


Edwards works with Fortune 500 organizations across defense, financial services, pharma, and healthcare. The kinds of institutions where the pressure to show AI’s value is matched only by the difficulty of actually doing it. These are not organizations experimenting casually. They are organizations that have already spent the money and now need someone to show them what they bought.

Lisa Ann Edwards has always had an answer. Now, for the first time, she has a platform powerful enough to prove it at scale.

Learn More & Get Involved
🎬 Watch the ICONS Movie — Meet the women behind the movement. icons by Women in Cloud
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