#FoundHerWorld – Marcia Tal

Marcia Tal Spent Decades at the Intersection of Customer Data and Corporate Blind Spots. PositivityTech Is What She Built When She’d Seen Enough

The complaint sits in a database somewhere. Filed, logged, and forgotten. What nobody noticed is that it was trying to tell you something.


Long before the negative review, before the churn, before the regulatory inquiry lands on the wrong desk at the wrong moment, there is a customer narrative. A word choice. A tone. A pattern hiding in plain language that, if anyone were paying close enough attention, would have predicted exactly what was coming next.


Most companies collect massive amounts of customer feedback but rarely treat it like usable business data.
Marcia Tal is changing that.


Her platform helps companies analyze reviews, surveys, and customer conversations to uncover patterns, product insights, and blind spots that would otherwise go unnoticed.

Marcia Tal has spent a career at that intersection, the place where what customers say meets what businesses do with it. As Citigroup’s EVP of Decision Management, she built and ran a global analytics function spanning thirty markets, close enough to the numbers to understand what they could reveal and close enough to the customers to understand what the numbers were missing. What she kept finding, buried inside complaint data and customer narratives, was intelligence that organizations were systematically leaving on the table.


“Companies are sitting on a goldmine they barely touch: customer narratives,” she says. “Their mindset is broken; they approach customer narratives as they always have, disconnected from P&L. PositivityTech closes the gap, turning those signals into predictive intelligence and negatives to positives to profit.”


PositivityTech under Tal Solutions LLC is the AI-powered platform she built to change that. Drawing on CFPB customer complaint data and proprietary sources, it breaks down language, derives variables, and ranks risk, surfacing early indicators of regulatory exposure, reputational shifts, and operational vulnerabilities before they show up in traditional metrics. What started as a tool for bank executives and risk leaders is now finding traction with traders, research analysts, and portfolio managers who have recognized what Tal understood years ago: customer narratives are not a service problem. They are a predictive dataset.


Available on Microsoft Marketplace and backed by decades of institutional credibility, PositivityTech is the rare fintech product built not from a gap in the market, but from a gap in how entire industries think.
Marcia Tal has been told she is ahead of her time more than once. She has decided to take that as a timeline, not a limitation.

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#FoundHerWorld –  Laura Massetti

No One Teaches This at Work. Laura Massetti Built the Program That Does.

Laura Massetti spent fifteen years inside organizations watching the same thing happen. A new hire would arrive capable, motivated, and ready. Within months, they’d be struggling, not with their job, but with the unwritten architecture of professional life: how to respond to an email in a way that builds trust, on how to receive feedback without deflating. And essentially, on how to read a room.
She kept writing it in performance reviews, over and over, in different words. And she kept wondering why no one had ever taught it.


The runway that used to absorb this learning is gone. AI raised the floor on what early-career professionals must deliver. Margins tightened. Managers who once mentored now spend those hours covering gaps that the university and onboarding never close. A 2024 survey found 55% of hiring managers had let a recent graduate go, not for lacking skills, but for lacking the operational fluency that no one had ever explicitly taught them.


So Massetti built the operating system she wished had existed. Real Work Ready™ is a structured professional readiness program organized around what she calls the Performance Model Framework™, in which six operating dimensions that managers are already scoring are made visible and teachable for the first time. Members move through a seven-module curriculum, live coaching sessions, and role-play on real workplace situations. The behaviors shift in week one.


“The runway to teach early-career hires the basics is gone. AI raised the bar, margins tightened, and senior operators don’t have hours a week to mentor anymore,” she says. “I spent 15 years writing performance reviews inside fast-moving organizations, then built the operating system to close the gap at scale.”


The hardest part hasn’t been the building. It’s been reaching the right people, the HR and L&D leaders with the budget and the mandate, the ones who already know Gen Z retention is broken and are looking for something that actually works.
Massetti is working to get in front of them. Real Work Ready is, as she puts it, defining a category. She intends to be the one who names it.

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#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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