Tim is a portfolio CEO, so the most interesting part of the conversation is not simply what VetraFi does. It is the lens he brings to the work: how veterans move from military service into civilian life, how they make sense of what comes next, and how that experience can shape the companies they build.

The group discusses several parts of that transition. They talk about the pressure many veterans feel to follow familiar civilian paths, whether that means graduate school, a large company, or another more conventional next step. They also talk about the role of veteran networks, the adjustment to civilian workplaces, and the process of figuring out which instincts from military service still serve you in a new context.

The conversation gets beyond the usual shorthand of military experience as “leadership.” The founders talk about operating habits, team expectations, cultural rituals, and mission-driven work. Tim also brings up examples like challenge coins, showing how traditions from military life can carry meaning inside a company when they are adapted thoughtfully.

That is what makes the episode useful: it is not just a story about leaving one institution and entering another. It is about translation. What do you keep? What do you leave behind? What becomes an advantage once you are building something from scratch?

That connects directly back to VetraFi. Building for military families requires more than a generic fintech playbook; it requires understanding how service shapes people’s financial lives, communities, and expectations. Tim’s reflections in the conversation reinforce why founder-market fit matters, and why VetraFi’s mission is rooted in lived experience as much as product opportunity.

Watch the full Founder Group Chat from Inc.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

Say “tech founder” and most people picture the same guy: young, bold, a little reckless, definitely male. Zuckerberg. Elon. Kalanick. Move fast, break things, never apologize.

But that’s one archetype. Not the only one.

Anna Barber and Jenny Fielding have spent the last two decades building our own companies and investing in hundreds of others. Four years ago we built a framework for the founder types we kept seeing over and over again - and it’s held up, even through the AI boom.

We call them: the Wallbreaker, the Empath, the Scientist, and the MBA. Each has strengths, each has blind spots. We find this framework useful because when you can name your archetype, the strengths and blind spots become easier to identify and then compensate for.

It’s useful for us as investors too. We each gravitate toward certain types and go easy on their flaws, which also means we’ve definitely passed on great founders simply because they weren’t “our type.” I have one painful example of this that I won’t name - a “wallbreaker” founder I was just allergic to and passed on, who went on to have great success with his company. The more we understand these archetypes and our own leanings as investors, the better decisions we can make.

The Wallbreaker

The Wallbreaker is part visionary, part tyrant. They see something no one else can see, and they’ll go through (not around) anything in the way. Ambitious, hard-driving, magnetic. They can raise money, tell a big story, and pull top talent into their orbit. Inside the company, that same intensity has a dark side - control and impatience. People describe Wallbreakers as both charming and arrogant.

Elon Musk is the archetype of this archetype. He projects a vision so big that investors, customers, and the internet at large rally around it - even while running multiple companies at once. The company becomes an extension of him. We all saw Gwynne Shotwell ringing the bell at the SpaceX IPO - but whose name do you think of when you think of SpaceX?

From Jenny: I’ve worked with plenty of Wallbreakers who became great CEOs. They’re not always open to feedback at first, but some come around once trust is built. I’ve also walked away from a few who were just too arrogant and argumentative to deal with.

Wallbreakers are unafraid of the impossible, exactly what you need when you’re building something with a hundred unknowns. They tend to be pioneers, not iterators: you’ll find them in robotics, crypto, and spacetech. They take heavy pushback simply for being bold, and their singular focus (obsession) is what keeps the ship moving forward.

That same focus can turn into a bunker mentality. Wallbreakers often keep a tight inner circle and control the flow of information, which can breed a toxic, siloed culture if left unchecked. A Wallbreaker without self-awareness makes for a hard place to work.

The Empath (Crusader)

Mission-driven. Deep founder-market fit. Usually an accidental entrepreneur. The Empath starts a company because they can’t stop thinking about a problem, not because they set out to build a business. Like the Wallbreaker, they’ll do slightly unreasonable things to get it off the ground.

Empaths tend to start with no plan and no product, just an urgency to help their chosen customers. What begins as a side project snowballs into a company. They’re natural “line leaders”: charismatic, inspiring, and they understand their customers better than anyone else in the building, because they actually listen.

Where they get into trouble is scale. They’ll put the customer ahead of the team, struggle to hire for skills they don’t have, and spend too little time thinking about how the business actually makes money. Given time to learn and the right hires around them, Empaths grow into strong CEOs.

From Anna: Empaths are my favorite founders to work with. Their passion is contagious, and it usually attracts a founding team that’s just as purpose-driven, which becomes the backbone of a strong culture. Their gifts - courage, presence, deep market knowledge - are hard to teach. When they also commit to learning resilience, focus, and management, they become exceptional leaders.

The Scientist

The Scientist is the deep-thinking, technical founder, mission-driven but relentlessly practical. They live in the product, obsess over the details, and can spiral into perfectionism. Because they tend to be introverted, they process internally instead of asking for help.

Scientists thrive on identifying a problem and solving it systematically. At their best, they surround themselves with other independent thinkers, which is great for diversity of thought, but their networks tend to be smaller, so their pool of hires, investors, and advisors is often thinner too.

From Jenny: I love working with Scientists. They’re quirky, offbeat, genuinely open to new ideas. When a Scientist is open to feedback, it’s magic. They absorb new information fast, and when they are self-aware, they hire people who aren’t like them.

Curious, technical, discovery-obsessed. Scientists will go deep on one problem until they crack it, with a kind of endurance most people don’t have. Growing up as free thinkers makes them resilient to social pressure, too.

The flip side: They can be perfectionists and avoid shipping until the product reaches their bar. They may be blind to this tendency because they are so focused on the product and not the market.

The MBA

Methodical. Clinical. Spreadsheet-first. The MBA founder finds the white space, builds the playbook, and executes with precision. Planning, research, and a well-tended network are the strengths. What’s often missing is a personal “why.” MBA founders often have deep conviction about the opportunity, but not always deep passion for it.

MBAs are built for businesses that reward planning and execution over sudden insight. Competition doesn’t scare them, which makes MBAs excellent fast followers in a market someone else pioneered. Where they struggle is when the plan breaks down: without an emotional stake in the problem, it’s harder to push through the hard stretch.

Warby Parker’s four Wharton founders are the classic example. They looked at a consolidated industry with one giant (Luxottica) and saw an opening for a digital-first, DTC challenger. They approached the business like a class project, working with their own professors on pricing, mining every scrap of customer feedback for the next move. Data and market response drove the company forward, not gut instinct. Side note: In today’s market - there are a LOT of MBA founders chasing the AI gold rush. We think in this market these founders can build great cash flow businesses but the Scientists and Wallbreakers are probably more venture-backable.

From Anna: While most people love to critique MBA founders, they have some great strengths. They treat the business like a learning problem. They ask for advice, chase customer feedback, and follow the data even when it means killing an idea they loved. They can also build strong brands, because they’re wired for consistency and a clean, end-to-end customer experience.

So, what’s your type?

If you’re a founder, you probably already know. If you don’t, ask your co-founders, your team, your family. (Side note: asking for feedback is itself a leadership strength.)

No framework this tidy captures everyone perfectly - most people are a dominant type with streaks of the others. Anna’s an Empath with a dose of MBA and a sprinkle of Scientist. Jenny’s a Scientist with a healthy dose of Wallbreaker and a touch of MBA. We both had to learn to shore up our tendencies and strengths with other skills.

Does this resonate? Jenny and Anna would love to hear your thoughts, and your type!

AI security is moving from a future concern to an immediate infrastructure problem.

As enterprises deploy more AI applications, coding agents, MCP-connected workflows, and autonomous systems, the security question is no longer just whether an AI model is safe in isolation. It is whether the full application and agent stack can be discovered, monitored, governed, and protected in real time.

That is why it is great to see Operant AI recognized by CRN as one of the 10 hottest AI security startups of 2026 so far.

CRN’s list focuses on emerging vendors building in areas like AI security posture management, agent security, AI governance, runtime protection, and AI red teaming. Operant was highlighted for its work to embed security for AI and agents directly within AI inference infrastructure.

In March, Operant announced its AI Infrastructure Ecosystem Partnership Program, designed to bring Operant‘s runtime defense capabilities directly into the inference stack with leading AI infrastructure companies. The idea is simple and important: as AI becomes part of core production infrastructure, security needs to live where those systems actually run.

That follows another channel-focused move from the company: the launch of Operant AI‘s Channel Partner Program, led by Katherine Mills, to help VAR partners bring advanced security for AI and agents to customers.

This is a useful signal for the category. AI security is not just about prompts or policy. It is about protecting the runtime environments, APIs, agents, tools, and infrastructure pathways where AI systems take action.

Operant AI has been building around that reality from the start.

Read the full CRN article here.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

At the earliest stages of company-building, there usually is not much hard evidence to lean on yet.

No long operating history. No mature metrics. No consensus view from the market. Just a founder, a problem, and the quality of the thinking around what comes next.

That is why standards matter so much in early-stage investing.

Mercury recently featured Jenny Fielding in its Points of View series, which explores how different people think about standards: where they come from, how they hold up, and what it means to set or challenge them.

For Jenny, the standard she refuses to compromise on is founder-first honesty.

She puts it plainly: she will not tell a founder an idea is great when she does not believe it, and she will not soften a hard truth just to preserve the relationship. That perspective comes from having been a founder herself. At the beginning, clear feedback is not a nicety. It can be the difference between moving with conviction and losing time to false reassurance.

The conversation also gets at what Jenny looks for in founders. The strongest ones do not hide the hard part of the business behind a polished pitch. They lead with what is broken, what they are still working through, and how they are thinking about the problem.

That kind of honesty is a signal. So is judgment.

Jenny talks about protecting a founder’s judgment when everything else cannot be protected, and about the danger of second-guessing someone into paralysis. She also pushes back on venture’s habit of confusing pedigree for quality. Great founders can come from Lagos, Bogota, Tallinn, and everywhere in between.

That is core to the Everywhere mindset: talent is not concentrated in a few familiar places, and pattern matching can become a liability when it starts replacing curiosity.

One of the sharpest lines in the interview is Jenny’s reminder that conviction and correctness are not the same thing. Early-stage investing requires conviction, but the real test comes later, when the story changes and you have to separate what you actually believe from what you want to be true.

It is a concise conversation, but a useful one for founders and investors alike.

Read the full Mercury interview with Jenny Fielding here.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

Trade businesses often run on a messy stack. Inventory in one place. Invoices somewhere else. Payments in another system. Customer credit and collections tracked across spreadsheets, chats, and memory.

For wholesalers, distributors, and manufacturers, that fragmentation creates real operational drag. Teams spend too much time reconciling information, chasing payments, monitoring credit exposure, and trying to understand what is happening across the business. FusePay is building for that problem.

Tech in Africa recently covered the company’s launch of Fuse360, an AI-powered business management platform designed for trade businesses. The platform brings together inventory management, orders, invoicing, customer credit, collections, and retailer relationships in one system.

That is already useful on its own. But Fuse360 is also integrated with FusePay‘s licensed payments platform, which means businesses can manage operational workflows and financial transactions inside the same ecosystem.

The AI layer is focused on the repetitive but important work that slows teams down: payment reconciliation, collections, reporting, credit monitoring, and business analysis. FusePay describes the goal as supporting employees rather than replacing them, which feels like the right framing for a category where trust, context, and relationships still matter.

Fuse360 also includes a retailer portal where customers can place orders, view invoices, download statements, and monitor outstanding balances. KYB and KYC onboarding tools help suppliers assess customers before extending trade credit, while AI-powered credit intelligence analyzes payment behavior, historical patterns, and outstanding exposure.

That matters because trade credit is one of the quiet engines of commerce. Better data and more connected workflows can help suppliers make faster, more informed credit decisions without losing control of risk.

FusePay was founded by Vidhyasahar Thiyagarajan and Francesco Rocchi, both of whom grew up around family-owned retail and wholesale businesses. That lived experience shows up in the product: Fuse360 is not generic back-office software. It is built around the operational reality of trade businesses in markets where payments, credit, inventory, and customer relationships are deeply connected.

The company launched Fuse360 in Seychelles in July 2026 and plans to expand to Mauritius in September, followed by selected East and Southern African markets before the end of the year.

We have always liked companies that use software to bring structure and intelligence into overlooked operational categories. FusePay is doing that for trade businesses, starting with the workflows that determine how money, goods, and credit actually move.

Read the full Tech in Africa article.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

For professional athletes, deciding when and how to start a family can be especially complicated.

A recent New York Times article explores how women on the professional tennis tour are increasingly turning to egg freezing and IVF while continuing to compete at the highest level. Players described navigating hormone injections, training restrictions, recovery, treatment costs, and the uncertainty that comes with fertility care.

Their experiences reflect a much broader challenge. Women across industries are balancing demanding careers, relationships, financial considerations, and the biological realities of fertility.

Everywhere Ventures portfolio company Cofertility is building a new model around that challenge.

Traditional egg freezing can cost tens of thousands of dollars, putting fertility preservation out of reach for many women. Cofertility allows women to freeze their eggs for free when they choose to donate half of the eggs retrieved to a family seeking an egg donor.

The model creates value on both sides. Women can preserve their fertility without carrying the full financial burden, while intended parents gain access to donor eggs through a more transparent and human-centered process.

Cofertility is also rethinking the traditional egg-donation experience. Rather than approaching donation as an anonymous transaction, the company gives donors and intended parents more agency over the relationship and level of communication they want to have.

The article also notes Maria Sharapova’s investment in Cofertility After delaying motherhood during her professional tennis career, Sharapova began investing in companies helping women gain greater flexibility around when and how they build their families.

Professional tennis provides a visible example of the trade-offs women face, but the underlying need extends far beyond sports.

As more women seek greater control over their reproductive timelines, Cofertility is expanding access to fertility preservation while building a more thoughtful model for egg donation and family building.

Read the full New York Times article.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

Most gas stations were built around the fastest possible version of a stop: fuel, snacks, payment, back on the road.

Maggie’s Refuel is asking a better question: what if that stop could actually be worth lingering for?

SlashGear recently covered the company’s planned Beverly Hills flagship, which is expected to open in 2027 alongside the existing Union 76 station on Santa Monica Boulevard. The site is already a local landmark, known for its midcentury modern canopy, and Maggie’s is building around that sense of place rather than flattening it into another generic convenience format.

The concept comes from Alex Canter, a fourth-generation member of the family behind LA’s iconic Canter’s Deli. That hospitality background shows up in the product vision. Maggie’s is not just adding nicer shelves to a gas station. It is combining fuel, curated food and beverages, EV charging, local restaurant collaborations, app-based ordering, and rewards into one modern roadside experience.

According to SlashGear, the flagship is expected to include staples like soda and chips alongside carefully selected snacks from emerging food brands around the world. The store will also offer fresh food and drinks, including craft lattes, ceremonial-grade matcha, fresh juices, artisan soft-serve ice cream, and pastries from Beverly Hills bakeries.

The app layer matters too. Customers will be able to order drinks and snacks before they arrive, turning the gas station visit into something closer to a hospitality and commerce experience than a pure utility stop. EV charging adds another reason to rethink the format: if drivers are already spending more time on site, the quality of that time becomes part of the product.

We have always liked companies that take an overlooked everyday category and rebuild it around changing consumer expectations. Maggie’s Refuel fits that pattern. Fuel may be the anchor, but the opportunity is broader: food, beverage, hospitality, rewards, real estate, and a brand that can make a routine errand feel considered.

If the Beverly Hills flagship works, it could become the launch point for a concept that expands across the West Coast. That is what makes this exciting. Maggie’s is not just trying to make one gas station nicer. It is testing a new operating model for what the next generation of convenience retail can feel like.

Read the full SlashGear article.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

Digital fraud is becoming more sophisticated, coordinated, and difficult for businesses to detect using traditional rules-based systems alone.

Fraudsters are increasingly combining tactics such as account takeovers, SIM swaps, phishing, , voucher fraud, and social engineering. These attacks are not always isolated incidents. They are often connected to larger syndicates that can quickly change tactics, locations, and targets.

That is the problem Orca is working to solve.

Orca is an anti-fraud technology company that helps businesses identify suspicious activity and stop fraudulent transactions. Its platform currently protects more than R82 billion in monthly transaction volume across several industries, giving the company visibility into how fraud networks operate and evolve.

MyBroadband recently profiled the company and the patterns emerging from its monitoring software. According to Orca CEO Thalia Pillay, KwaZulu-Natal consistently appears as the South African province with the highest level of digital fraud and active fraud syndicate activity.

Orca has also observed fraud networks beginning to migrate into other regions, including the Eastern Cape. By analyzing activity across transactions, accounts, devices, and locations, the company can identify not only individual instances of fraud, but also broader movements and connections between criminal operations.

The article highlighted an alleged scam call center uncovered in Umhlanga in April 2026. Authorities arrested 23 people suspected of participating in banking scams from an upscale property. The operation allegedly used vishing tactics to convince victims that their bank accounts were at risk before directing them to transfer money into accounts controlled by the syndicate.

This reflects the increasingly professional nature of digital fraud. For many fraudsters, these schemes operate like full-time businesses, with teams simultaneously running phishing campaigns, managing SIM card farms, laundering funds, and recruiting money mules.

Artificial intelligence is making these attacks easier to scale. Fraud networks can now produce more convincing messages, target more people, and coordinate multiple forms of fraud at the same time.

That makes real-time intelligence increasingly important. Businesses need systems that can recognize behavior and connections across a network rather than evaluating each transaction in isolation.

We have always liked companies that turn fragmented and difficult-to-detect activity into actionable intelligence. Orca fits that model by helping companies understand not only whether an individual transaction appears suspicious, but how it may connect to a broader fraud network.

As digital payments continue to grow, fraud prevention will need to become faster, more adaptive, and more collaborative. Orca is building the infrastructure to help businesses stay ahead of the syndicates operating across an increasingly complex digital economy.

Read the full MyBroadband article.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

Wellness is becoming a bigger priority for consumers, employers, and hospitality teams. But access has not always kept up.

Traditional spa services can be expensive and inflexible for consumers. Independent therapists often struggle to build a steady book of business. Hotels and companies want to offer wellness experiences without taking on the cost and complexity of operating a full spa. That is the gap Scape is building into.

Scape is an on-demand wellness marketplace that connects certified therapists with individual clients, companies, and hotels. Through its mobile app, customers can book premium massage and wellness services, choose therapists, and manage the experience from one place.

Pro Network recently profiled the company and its model, highlighting how Scape is combining technology, a managed therapist network, and a premium customer experience to make wellness services more accessible and scalable.

What started as a consumer offering has expanded into a broader platform across B2C, corporate wellness, and hospitality. For companies, Scape supports employee wellness programs through digital campaigns, online registration, and on-site massage sessions. For hotels, it offers a way to provide spa-quality services without major infrastructure or specialized staffing investments.

That expansion is showing up in the numbers. According to the article, Scape has served more than 250 corporate clients, delivered more than 33,000 consumer services, grown B2B 71.5% quarter-over-quarter, and is projecting $4 million in revenue while expanding further in the U.S.

We have always liked companies that use technology to modernize large, offline categories without losing the human experience that makes the service valuable in the first place. Scape fits that pattern: software makes the marketplace work, but trust, quality, and therapist-client experience remain at the center.

As wellness becomes a more consistent part of how people work, travel, and take care of themselves, Scape is building the infrastructure to bring premium services to more places with less friction.

Read the full Pro Network article.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

Keeping the grid reliable starts with knowing what is happening in the field.

For electric utilities, that work is still harder than it should be. Inspection programs are expensive, senior qualified workers are in short supply, and the findings often end up trapped in PDFs, spreadsheets, and systems that are difficult to use across the organization.

At the same time, utilities are under pressure to move faster. Wildfire mitigation plans, storm hardening commitments, resiliency programs, and federal inspection requirements all depend on asset-level visibility that can stand up to regulatory review.

ThreeV is building for that operational reality.

The company develops AI infrastructure for electric utility operations, helping utilities turn inspection data into usable intelligence across asset strategy, remediation, compliance, and planning. Its platform processes visual field data, classifies assets, detects defects, and makes inspection records searchable and actionable across existing workflows.

Now, ThreeV is partnering with Reliability Transformation Solutions (RTS) to launch Vision, a managed agentic AI inspection offering for U.S. electric utilities.

The model is practical: combine RTS‘ senior Certified Journeyman Linemen and Qualified Electrical Worker expertise with ThreeV‘s Vision inspection platform, AI model training, and inspection software. Utilities can start with a bounded special project on a single circuit or area, or use Vision for a broader routine inspection program.

That matters because many AI programs in industrial settings struggle to get past the pilot stage. Utilities need expert-grade inspections now, not a multi-year data science side project. Vision gives them the inspection capacity and defensible records they need today, while each completed inspection creates ground truth for customer-specific computer vision and agentic inspection models.

Over time, that creates a flywheel. The first inspection cycle produces validated data. Future cycles can shift more routine inspection work to AI agents, with expert linemen focused on quality assurance, spot checks, and the findings that require senior judgment.

As ThreeV CEO Eren Aksu put it, the goal is value in weeks, not years: humans and agents working together to serve utility customers.

The launch also fits ThreeV‘s broader mission. The company is focused on asset-heavy industries where inspection quality is not just an efficiency problem. It is a safety, reliability, compliance, and resilience problem. Better inspection intelligence can help utilities prioritize remediation, reduce avoidable field work, and move from static records to decisions that actually reach the people responsible for the grid.

For a sector where trust, domain expertise, and regulatory defensibility matter, Vision is a strong wedge: not AI in search of a workflow, but AI embedded directly into the inspection work utilities already have to do.

Read the full announcement in Morningstar.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

From the archives: Listen to Oban MacTavish with Jenny Fielding, on the Venture Everywhere podcast: In the Club with Spade. Now on Apple & Spotify. Check out all our past episodes here!

Healthcare access is often shaped by more than clinical need.

It is shaped by time, cost, geography, stigma, and whether the system feels built for the realities of everyday life. In the Philippines, those barriers can be especially visible: crowded hospitals, long wait times, stretched physicians, and health concerns that many people delay addressing because the process feels too difficult or too exposed. &you is building around that gap.

The company is a telehealth platform designed to make care more private, convenient, and supportive for Filipinos navigating health categories that are common but often under-discussed, including weight management, hair loss, sexual health, and mental wellness.

As Rolling Stone Philippines reported, the response has been immediate. &you launched in 2025 and saw 10,000 people sign up within days. More than 100,000 Filipinos have now taken the company’s health assessment.

That demand points to a larger shift. People aren’t disengaged from healthcare. Many are looking for care that feels less intimidating, less judgmental, and easier to fit into their lives.

One of &you’s core offerings is a doctor-supervised weight management program, including access to GLP-1 treatment where appropriate. The company’s approach emphasizes licensed physician oversight, safety, and consistency, aiming to give patients a more responsible alternative to navigating shortcuts or unverified options on their own.

That matters because weight management is not only a cosmetic category. Obesity is a modifiable risk factor for heart disease and diabetes, two of the leading causes of death in the Philippines. Better access to proactive, medically guided support can become part of a broader preventive care model.

Founder Emil Eriksen frames the opportunity around removing judgment from care and designing a system that feels private, normal, and supportive. &you is also developing an AI-driven telehealth engine to improve how consultations are conducted and how treatment plans evolve over time.

The bigger opportunity is not simply moving healthcare online. It is redesigning the experience around privacy, trust, affordability, and the actual constraints people face.

For categories where stigma and friction have historically kept people from seeking help, that can be a meaningful unlock.

Read the full article in Rolling Stone Philippines: https://rollingstonephilippines.com/radar/filipinos-healthcare-system-fix-andyou/

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

From the archives: Listen to Neha Govindraj with Jenny Fielding, on the Venture Everywhere podcast: Catch You on the Bonside. Now on Apple & Spotify. Check out all our past episodes here!

Egg freezing has historically been expensive, complicated, and difficult to access.

For many people, it is also tied to deeply personal questions around health, family planning, timing, and choice. Yet the traditional process has often felt fragmented and transactional, with high upfront costs, limited access, and donor systems that can feel outdated.

Cofertility is building around a different model.

The company was co-founded by Lauren Makler, a Northeastern alum who experienced the fertility system firsthand after a rare health diagnosis put her own fertility in question. That experience helped shape Cofertility’s approach to making egg freezing more accessible while also supporting intended parents who need donor eggs.

Cofertility’s egg-sharing program allows clients to freeze their eggs for up to 10 years at no cost if they donate half to another family that otherwise may not be able to conceive. Those who choose to keep all of their eggs can access discounted freezing through Cofertility’s network of partner clinics and lenders.

The company also emphasizes a less transactional, more human-centered approach to egg donation. Rather than relying on anonymous, compensation-driven donor matching, Cofertility focuses on a non-anonymized model that gives donors and intended parents the opportunity to understand more about each other and the meaning behind the match.

That is the larger opportunity here. Fertility care is not only a clinical process. It is an access problem, a cost problem, and an experience problem.

As more people think proactively about reproductive health, platforms that can make fertility services easier to understand, afford, and navigate may become an increasingly important part of the healthcare system.

Read the full article in Northeastern Global News.

Interested in investing alongside Everywhere Ventures? Learn more about joining our investor community here.

Every task does not need the same model. Some workflows require frontier-level reasoning, while others can be handled by smaller, more specialized models. But for enterprises, deciding which model to use, when to use it, and how to manage performance across a fast-changing market is becoming its own operational problem.

Neurometric is building around that problem.

The company raised $4 million in pre-seed funding from Betaworks, ex/ante, Everywhere Ventures, Encoded Ventures, Vermillion, Abstraction, Mu Ventures, Jason Calacanis, and Dharmesh Shah.

Neurometric provides an automated token engineering platform for companies running agentic AI workloads at scale. Its platform helps organizations route tasks to the most cost-effective and accurate language models, with tools including an automated task endpoint manager, an SLM marketplace, and an auto-SLM creator.

That is the larger opportunity behind the round. As AI usage grows inside the enterprise, the question is no longer just which model is best. It is how to build systems that can continuously optimize across cost, latency, accuracy, and reliability.

Neurometric will use the new capital to expand its engineering and AI research teams and continue developing optimization tools for a language model market that is changing quickly.

As agentic AI moves from pilots into production, infrastructure that makes model usage more efficient, measurable, and cost-effective may become a critical layer of the AI stack.

Read the full article on The SaaS News.

We’re in the era of the General Contractor CEO.

In Asia there’s been a rise of One Person Companies, or OPCs. In the West, many are speculating that soon billion dollar businesses could be single-founder creations, leveraging the output and coordination advantages with AI. I wrote on this idea a few years ago in what I called “The Rise of the Thin Company,” which I first referenced in terms of our portfolio company, Finalis, in May 2023.

The idea around Thin Companies, those enabled largely by AI, builds on the premise that not only can AI can supercharge a founder’s skillset, but also help them dynamically coordinate inputs based on business demands. More like creating a house, a circus or a movie, where skills are assembled and disassembled based on the immediate goals, AI can help in this task coordination and optimization. The company itself need not fully employ everyone to have those output advantages.

CEOs may yet become like General Contractors, bringing together loose ties to achieve organizational objectives, dynamically enabled by marketplaces and AI, rather than needing to bring all of these skills in-house permanently. A GC need not understand every part of the home building process, but they are the coordination authority bringing together foundation, electrical, plumbing, etc. The CEO has long been a lauded position; it’s moving the way of coordination maven.

Federico Baradello, CEO of Finalis, expanded further on this idea. “When we founded Finalis, we asked a radical question: what if the next elite investment bank wasn’t a skyscraper of analysts—but a lean, AI-enabled network of independent dealmakers working from anywhere?” Finalis aims to build the platform that enables 1,000 “investment banks OF one,” rather than a single skyscraper full of 1,000 investment bankers IN one. The reason this is possible, is because the economies of scale, the former advantages of established organizations with regulatory licenses, processes, are dwindling. In other words, you used to have to join a bulge bracket to get your laptop, get your market access, get your licenses, get your capital. No longer.

As the AI-enabled advantages accrue to the independent “General Contractor” CEO or GC-CEO, and to the Thin Company, they soon begin to outweigh the disadvantages associated with bureaucratic scale, working inside the skyscraper.

History repeats as a series of aggregations and disaggregations. The industrial revolution took independent craftsmen and consolidated processes and automation that led to economies of scale, and an inability for a single car manufacturer to compete. Now AI is doing the opposite, pulling on the string that unravels the benefits of being part of a large organization, and providing sufficient advantages to independent operators that they can not only compete, but win with AI.

As Baradello points out, “A Thin Company is lean in headcount but thick in leverage. Rather than scaling with humans, it scales through networks, automation, and intelligent infrastructure.” And so this General Contractor CEO must be adept at assembly, like a movie producer bringing together the components of a film (actors, DPs, gaffers, editors etc), to create art, and stay on budget. These new Thin Company leaders will increasingly be the conductors of AI tools, an agentic workforce, and the fluid human networks when episodic loose-ties are required. Finalis allows bankers to operate independently, but where they are thin on headcount, they’re thick on leverage around deal origination, market making, and info sharing.

I’m not of the belief that every new unicorn will be developed by a single AI-enabled vibe coder in a basement, but I do think we are in a burgeoning period of disaggregation, where AI enabled tools, and loose-tie networks like Finalis will empower far more Thin Companies to compete with bulge bracket players. There will be a break-even where the costs of bureaucracy are outweighed by the AI-enabled advantages of speed, independence, and coordination.

And as to that break-even point, we’re probably already there.

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Thanks to Michael Barone and Federico Baradello for contributions to this piece.

Scott Hartley is Co-Founder and General Partner at Everywhere Ventures, a $100 million-dollar early stage venture capital fund that has backed over 250 companies

Freight forwarding remains one of the most relationship-driven parts of global trade. Local expertise, customer trust, and operational judgment still matter deeply. But smaller and mid-sized forwarders are increasingly under pressure from thin margins, manual workflows, and larger competitors with more advanced technology. Starboard is building for that gap.

In a recent feature in The Loadstar, Sumeet Trehan shared how the company is using AI to help smaller forwarders compete more effectively. Trehan’s perspective is shaped by his experience across Maersk, BCG, and Flexport, where he saw firsthand that digital freight was not always solving the right problem.

The issue is not that small forwarders lack expertise. In many cases, they are closer to their customers and better understand the operational nuances of each shipment. The challenge is that much of their day-to-day work is still buried in emails, PDFs, spreadsheets, carrier portals, agent replies, and constantly changing rates.

That friction is especially visible in the quoting process. A forwarder may receive dozens of quote requests a day, with each one requiring manual work across multiple systems and sources. When response times stretch from hours into days, business can be lost to whoever replies first.

Starboard’s approach is to bring AI into the quote desk. The platform connects to a forwarder’s inbox, reads incoming RFQs, extracts cargo and routing details, breaks shipments into legs, searches contract and spot rates, and helps gather missing information from agents or co-loaders.

The goal is not to replace the forwarder. It is to give them the kind of speed, structure, and procurement intelligence that larger players have historically been better positioned to access.

That distinction matters. Freight forwarding is still exception-heavy and local by nature. The person who knows which carrier office to call, which routing may fall apart, or which customer needs extra attention remains central to the process. Starboard is building around that reality rather than trying to erase it.

The company’s broader thesis is that AI can help turn messy, unstructured freight data into something usable without forcing forwarders to rip out their existing systems. For an industry that still runs on inconsistent documents, emails, and fragmented workflows, that is a meaningful unlock.

As AI becomes more embedded in logistics, the most valuable applications may not be the flashiest demos. They may be the tools that make core workflows faster, more accurate, and more profitable.

For smaller forwarders, Starboard is positioning AI not as a replacement for local operators, but as a way to help them respond faster, quote better, and protect the customer relationships that make them valuable in the first place.

Read the full article in The Loadstar.

Led by founders Marc Hermann and Anshul Jain, Everlab is building around a different model: identify risks earlier and make it easier to act on them.

The team raised a A$65 million in Series A funding led by Airtree, with participation from Plural, b2venture, Left Lane Capital, and several angel investors, including Australian cricket captain Pat Cummins.

Everlab combines advanced diagnostic testing with doctors, specialists, prescriptions, wearable data, and AI-supported care through a single platform. Rather than leaving patients to interpret isolated test results, the platform organizes their health information and helps coordinate the screenings, interventions, and follow-up steps that come next.

The company has already analyzed more than 20,000 clients across Australia and New Zealand. The company’s testing has uncovered previously undetected health issues in more than one-quarter of clients.

That is the larger opportunity behind the round. Preventive care is not only about running more tests. It requires an operating layer capable of connecting fragmented health data to meaningful clinical action.

Everlab will use the new capital to expand into the UK and continue building its clinical and technology infrastructure. As healthcare shifts from episodic treatment toward continuous prevention, platforms that can hold the full picture of a person’s health may become an increasingly important part of the system.

Read the full article on the Startup Daily.

As technologies roll out, initial advantages go to incumbents who can adopt the new technologies for efficiency gains, and margin expansion. I’ve heard a number of friends say, “If companies like Harvey and Legora are growing so quickly, how come my law firm bills haven’t gone down?” If a lawyer is able to perform commoditized legal work in a fraction of the time, shouldn’t this hit billable hours, and therefore the cost for services? In the short run, this margin accrues to the incumbents.

But let’s take radiology as an example.

A decade ago many heralded the death of radiology as a field. The logic went as follows: radiologists predominately look at pictures of MRIs, AI driven image recognition and cognition was getting better and better, so therefore an image-heavy field like radiology would be one of the first things to disappear.

What happened, however, was two-fold:

1. AI impacted hardware (atoms): MRI machines became more powerful, faster, cheaper to build, manage and operate, and more came online

2. AI impacted software (bits): image-processing obviated the need for radiological review on rote and routine cases, and shifted their focus to the edge, where practitioner experience mattered, nuance and context were needed

These two impacts meant that more MRI machines became available to more people, and the number of radiologists needed to process the images went down. For a brief interregnum, image labs could have accrued margin due to being able to run MRI scans more cheaply, and perhaps with fewer doctors on staff as overhead.

But then something perhaps curious, or perhaps obvious, happened. New entrants flooded the market offering MRI scans for orders of magnitude cheaper prices, harvesting the delta between old price and new cost, and offered these services at prices that drastically undercut historical offerings. And because at these new price points there were entirely new use cases for MRIs, like preventative scans, demand skyrocketed, new companies were formed, further compressing margins in a race for user acquisition, and the total number of not just MRI machines and scans, but radiologists reviewing these scans, went through the roof.

This is a phenomena known as the Jevons Paradox, dating back to 1865. William Stanley Jevons first observed the phenomena with coal. Technological efficiencies lead to a rise in production capabilities, a reduction in price, and an ensuing expansion of demand. The very efficiencies thought to eliminate jobs create such a great expansion in production, and fall in price, that it’s net positive for both demand expansion and therefore the need for more human labor, not less. NPR recently did a great deep dive on exactly this phenomena as relates to the expansive effects of AI.

This three part movie will likely play out in legal, and many other industries:

1. AI affords advantages to incumbents who harvest new margins, and there’s a brief interregnum where incumbents continue to dominate, and prices don’t change (this is the valley of disbelief, where people think AI hasn’t changed much)

2. New entrants leveraging these new cost advantages undercut industry norms, and attack this new margin, closing the gap between price and cost

3. Prices for the same services fall, and there is net new demand for these services at new price points, probably leading to market expansion and growth

Both incumbent and new player may continue to exist, but because the incumbent’s fixed costs are likely commensurate with old price points, they’ll have a structural disadvantage to the new players who are AI-native, and don’t carry some of the same deadweight fixed costs, making them more nimble and immune from margin erosion.

Overall, like we saw with Prenuvo, Ezra (now Function Health), EverLab, Axo and many of the consumer-facing health companies offering preventative MRI scans at a fraction of the traditional costs, we’ll likely see new supercharged AI-native law firms who will be able to offer commensurate quality to a top-tier firm, at a fraction of the price. They’ll eat into those incumbent law firm margins and profits, drive the fee per service down, and in turn perhaps create net new market expansion.

At firms like Omar Haroun’s Eudia supercharging in-house counsel with AI tools, they’re providing an AI-native toolbox for in-house counsel to drastically slash legal budgets. While they still may pay premium dollar for white-shoe litigators, mainly for the optical threat of power against peers, commoditized legal will be a race to the bottom, with new entrants cutting into incumbent partner rate charts by being able to do comparable quality work at a fraction of the cost for clients.

Early AI efficiencies accrue to legacy incumbents. Net new AI-native players leverage new cost advantages to attack margin. Prices reduce and clear. Net demand increases for services, market expands, and net new jobs are likely created due to growth. Like was experienced with coal, with radiology, legal might be next. If my legal bills fell from $2,000 an hour to $200, I might actually ask more than 10x my demand. But this new value accrual won’t go to legacy players hoarding margin. It’ll go to new players, or those AI-native firms with the structural cost advantages to support it.

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Scott Hartley is Co-Founder and General Partner at Everywhere Ventures, a $100 million-dollar early stage venture capital fund that has backed over 250 companies.

Special thanks to Omar Haroun at Eudia, and Michael Barone at Everywhere.

Tax season creates a familiar kind of urgency. Refunds, assessments, payment notices, and compliance updates all arrive at once, often through the same digital channels people already trust. That familiarity is exactly what scammers are using.

Orca Fraud CEO Thalia Pillay is warning South Africans to watch for a predictable spike in SARS impersonation scams this filing season. The messages vary, from fake settlement notices and refund SMSes to letters of demand and auto-assessment prompts, but the playbook is the same: make the message feel official, make the deadline feel urgent, and push people to click before they verify.

What makes these scams more convincing is the shift to digital. With SARS now relying fully on digital correspondence for system-generated letters, legitimate communication is already happening through inboxes and SMS threads. That gives fraudsters more cover to imitate the process.

The core advice is simple: do not trust the link, trust the source. SARS will not ask for banking or credit card details by SMS or email, will not send payment instructions through random accounts, and will not route taxpayers to external sites for compliance steps. Anything suspicious should be checked directly through eFiling or the SARS website.

For Orca, the broader issue is not just scam awareness. It is about helping people recognize fraud in the moment it matters, before urgency turns into action. As more financial and government interactions move online, that layer of trust and verification is becoming increasingly important.

Read the full article on the Business Explainer.

Insurance remains one of the largest industries in the world, but many brokerage workflows still depend on manual processes, disconnected tools, and institutional knowledge.

Outmarket AI is working to change that by building an AI platform purpose-built for insurance brokerages.

The team announced its $17 million Series A, led by Permanent Capital Ventures, with participation from SignalFire, Fika Ventures, TTV Capital, Dash Fund, and strategic investors across the insurance ecosystem. The round brings Outmarket’s total funding to $21.7 million and reflects growing confidence in the company’s vision for the future of insurance operations.

Outmarket’s platform connects directly to agency management systems and transforms structured and unstructured brokerage data into an intelligence layer that powers key workflows across commercial, benefits, personal lines, and specialty insurance.

The company is already seeing strong market adoption. Since launching in March 2025, Outmarket has grown ARR 5x year-over-year and is now used by more than 250 leading insurance brokerages. Its platform processes millions of quotes, policies, applications, and loss runs documents, helping customers save more than a decade of manual work each month.

The impact extends beyond efficiency. Customers have reported up to a 65% reduction in errors and omissions through AI-assisted policy comparison and gap detection. Brokerages are also using Outmarket to improve win rates, identify cross-sell opportunities, and deliver better service to clients in less time.

The broader shift across insurance is clear. Brokerages are moving from manual, fragmented processes toward connected, AI-enabled infrastructure that can support every stage of the brokerage workflow.

The funding will support continued platform expansion, including new AI-driven workflows for complex, high-stakes insurance processes. Outmarket also plans to more than double its product capabilities in 2026 as it expands across commercial lines, benefits, personal lines, and specialty insurance.

For Vishal, Anshu, and the team, the opportunity is to build the operating system for the modern insurance brokerage and help define how the industry works in the years ahead.

Read the full article on PRNewswire.

Every day, marketplaces need to move money to thousands of people at once: hosts, creators, sellers, contractors, and distributed workers across different markets. The workflow sounds simple, but behind it is a complex web of banking integrations, compliance requirements, reconciliation, and local payment infrastructure.

Radar is focused on making that infrastructure work.

The company automates financial operations for platforms that need to pay large groups of people simultaneously. Its specialty is payment dispersion, helping companies like Airbnb, TikTok, and Booking move money across Latin America more efficiently and reliably.

In a region where many fintechs are competing for the largest markets, Radar has gone after countries that are often underserved by global payment infrastructure, including Ecuador, Bolivia, and Paraguay. These markets may be smaller individually, but together they represent a meaningful opportunity, especially for global platforms looking to operate across Latin America without rebuilding payment rails country by country.

That focus has shaped the company’s operating discipline as well. Founded in 2022, Radar has raised just $1.5 million, became profitable within three years, closed 2024 with $2.9 million in revenue, and is projecting $12 million by 2026.

Early on, when banks would not give Radar direct access to their systems, Herbert Schulz and the team built their own workaround using a physical bank token, a webcam, and AI to read authentication codes in real time. It was scrappy, imperfect, and exactly what the moment required.

Today, that shoebox is no longer needed. Radar now connects directly into banking systems and processes more than one million transfers per month.

From our lens, this is where durable infrastructure companies are often formed: in the messy operational gaps that incumbents are too slow to solve and larger players are too broad to localize.

As marketplaces, creator platforms, and cross-border commerce continue expanding across Latin America, payment infrastructure will need to become more embedded, more flexible, and more regional by design.

Radar is building in that direction, toward a world where global platforms can move money across overlooked markets with the same speed and reliability they expect in the largest ones.

Read the full article on Diario Sustentable