Commercial insurance is one of the largest and most operationally complex markets in financial services.

Most insurance is still sold through human agents, and for good reason: the work is nuanced, relationship-driven, and highly specific to each customer. But the systems supporting those agents have not kept up. Brokers and agencies still spend enormous amounts of time on manual paperwork, application forms, document review, and administrative tasks that slow down the process for both customers and advisors.

Outmarket is building for that gap.

The company, founded by Vishal Sankhla, uses AI to help insurance agencies and brokers automate the tedious back-office work that sits behind commercial insurance. The opportunity is especially large in commercial lines, where businesses need coverage across a wide range of risks — from general liability and workers’ compensation to D&O and other specialized policies.

That complexity creates a real workflow problem. Different businesses need different coverage. Different coverage types require different applications, documents, and review processes. Brokers are expected to make sense of all of it while still serving customers quickly and thoughtfully.

Outmarket’s platform helps automate the repetitive administrative work so brokers can spend more time on the higher-value parts of the job: understanding a client’s needs, recommending the right coverage, and responding when something urgent happens.

The company’s momentum reflects how much demand exists for better infrastructure in insurance distribution. Outmarket has already attracted more than 300 insurance agencies as customers, including 25% of the top 100, only 14 months after launching its new product.

Now, Outmarket has raised a $34.5M Series B led by SignalFire, with participation from Fika Ventures, Permanent Capital Ventures, TTV Capital, and Dash Fund. The financing follows the company’s $17M Series A just four months earlier.

The broader market is enormous. The U.S. property and casualty insurance market alone represents more than a trillion dollars in annual premiums. As AI becomes more capable of handling complex, document-heavy workflows, insurance distribution is a natural category for transformation.

Outmarket is not trying to replace the human relationship at the center of insurance. It is giving brokers better tools so they can work faster, smarter, and with more time for the judgment-driven work customers actually value.

Read the full TechCrunch article.

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

The partnership will use Century Health’s CHARM AI platform to mine more than a decade of ophthalmology data and convert unstructured clinical information into structured, research-grade datasets. The work focuses on chronic retinal diseases including diabetic retinopathy and age-related macular degeneration, drawing from more than 200,000 de-identified patient records.

This is an important unlock for ophthalmology and life sciences research. Some of the most valuable variables in eye care, imaging findings, subtle structural changes, quantitative retinal measurements, and disease progression metrics, often live inside PDFs, scanned reports, and other unstructured files. That makes them difficult to use at scale for drug development, trial design, post-marketing research, payer evidence, and label expansion work.

Century Health is building the infrastructure to make that data usable. Its CHARM AI platform extracts and structures longitudinal clinical data so life sciences teams can better understand how patients progress and respond to therapies over years of routine care.

For Century Health, the Eye Health America partnership deepens the company’s footprint in ophthalmology and supports its broader strategy of building a specialty-focused data network across areas including neurology, immunology, and ophthalmology. The company now covers more than one million longitudinal records across 12 disease categories.

Congratulations to the Century Health team on this partnership.

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

Trebellar announced an $18M Series A led by Blossom Capital, with participation from Alt Capital, Haystack, 1Flourish, and Bynd.

The company is building the AI-native platform for corporate real estate. Enterprise real estate teams sit on a huge amount of operational data across facilities, workplace systems, sensors, occupancy tools, asset records, and planning workflows, but that data is often fragmented across disconnected systems. Trebellar brings that information together and turns it into actionable intelligence for teams managing complex real estate portfolios.

That matters because corporate real estate is becoming a more strategic function. Companies need to understand how space is used, where costs can be optimized, how employees experience the workplace, and how facilities decisions connect to broader business goals. Trebellar gives teams the data foundation and AI layer to make those decisions faster and with more confidence.

The company already counts Meta, Uber, and Merck among its approved customer references, and the new funding will support continued growth across engineering, go-to-market, AI capabilities, and enterprise adoption.

Congratulations to Diego Ferriero Val and the full Trebellar team!

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

Congratulations to Ilana Springer Borkenstein, Eric Gruskin, and the full M7 Health team on M7’s acquisition by Ascend Learning.

M7 was built around a problem that every health system understands: clinical staffing is one of the hardest operational challenges in healthcare. Nurse schedules need to balance coverage, cost, preferences, retention, burnout, and patient care needs, but too many teams are still stuck managing that complexity across manual processes and disconnected tools.

M7’s platform helps health systems forecast staffing needs, understand their workforce, optimize schedules, and plan ahead. The product gives nursing leaders and operational teams a better way to match staffing demand with the realities of the clinical workforce, while creating more flexible and predictable work environments for nurses.

The company has grown from a proof of concept into a workforce optimization platform powering hundreds of hospitals and supporting tens of thousands of clinicians every day. That progress reflects both the scale of the problem and the quality of the team Ilana has built.

Joining Ascend Learning gives M7 more resources, distribution, and reach to continue its mission of transforming how healthcare work gets done. We are proud to have been part of the M7 journey and excited for this next chapter.

Read more: https://lnkd.in/gBw7yi8p

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

Congratulations to Andrew McCarthy and the Axo Longevity team on raising an oversubscribed $5M seed round.

Axo is building a preventive health membership designed to make deeper health insight more accessible. The platform combines 100+ biomarker blood tests, ongoing tracking, and personalized guidance across nutrition, sleep, movement, and supplements so members can better understand what is happening in their bodies over time.

The need is clear: most healthcare still operates reactively, and many consumers only get meaningful testing or interpretation after something has already gone wrong. Axo’s model gives members a more structured way to monitor their health, identify imbalances earlier, and make targeted changes with clearer data behind them.

The company has already expanded across multiple European markets and built a broad partner lab network, making the experience more convenient for members who want preventive testing without navigating the traditional healthcare system on their own. Axo’s annual membership includes recurring biomarker analysis and an expert-backed plan, with the company continuing to add capabilities like an AI health copilot and wearable integrations.

We invested in Axo because we believe preventive health will increasingly look like an ongoing membership, not a one-off check-up. As biomarker testing becomes more affordable and consumers become more comfortable using data to manage their health, companies that can combine access, interpretation, and behavior change in one product will be well positioned.

This new financing will help Axo expand into additional countries, grow its laboratory network, and continue building a product experience that makes preventive health practical, personalized, and more affordable. We’re excited to see Andrew and the team continue building toward a new standard for proactive health across Europe.

Read the full Business Wire announcement.

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

Congratulations to Jeff Wald and the BoomerangHR team on emerging from stealth and announcing a $12.7M seed round, as covered by HR Brew.

BoomerangHR is building alumni management software for the modern HR team. The platform connects with a company’s existing HRMS and ATS systems, then automates key workflows around offboarding, exit compliance, alumni engagement, referrals, and rehire matching. Instead of treating an employee’s last day as the end of the relationship, Boomerang helps companies maintain a structured, active alumni network.

That matters because former employees can be one of the strongest pools of future talent and relationship capital. They already understand the company’s culture, systems, and customers. They can come back as high-signal rehires, refer strong candidates, become customers or partners, and continue to strengthen the employer brand if the exit experience is handled well.

The HR Brew piece highlights how BoomerangHR is designed to run with minimal lift from HR teams. The platform integrates into existing systems, supports offboarding workflows like COBRA administration, 401(k) rollovers, equipment returns, and exit interviews, and keeps verified alumni profiles current so companies can match former employees to new roles.

Warby Parker is cited as an early customer, with Chief People Officer Chelsea Kaden noting that BoomerangHR gives the company a streamlined way to stay connected with former team members, whether they return, refer someone great, or simply remain part of the broader team community.

We’re excited to see BoomerangHR bring more structure to a part of the employee lifecycle that most companies still manage manually, if at all. Congratulations again to Jeff and the team on this milestone.

Read the original article here.

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

That is a big deal because many scientific and manufacturing workflows still depend on brittle, bespoke integrations. A lab may have multiple automated machines, but each device often speaks its own language. Connecting them into a single workflow can take specialists weeks or months. Anthropic’s goal with MHS is to reduce that integration work to hours or minutes while giving AI agents safer, standardized ways to discover devices, understand what they can do, operate within safety limits, and coordinate work across instruments.

Tetsuwan, one of our portfolio companies, is directly aligned with that future.

Tetsuwan is building an automated biology lab available to researchers and agents through an API. Its platform, ResearchOS, lets users generate, run, and manage automated workflows from natural-language protocols. Claude can help translate those protocols into scripts, which are then processed by Tetsuwan’s custom compiler into automation code for lab equipment.

In Anthropic’s research preview, Tetsuwan integrated MHS with ResearchOS to run qPCR workflows for a citizen science project studying pollution in California’s San Pedro Creek. The workflow involved coordinating across lab devices, detecting issues during liquid handling, and recovering from errors in real time.

One example captures why this matters. qPCR workflows often involve viscous reagents that can bubble or foam during pipetting, which can compromise an experiment. In the Tetsuwan pilot, a camera detected bubbles in a transfer. Claude, operating through MHS, helped identify a recovery strategy: move the tube to a centrifuge and briefly spin it to draw the liquid down. Through MHS, Claude could then issue the appropriate commands to the centrifuge.

That kind of orchestration is the real unlock. It is not just “AI plus robot.” It is a system where protocols can become more hardware-independent, devices can be discovered and coordinated dynamically, and experiments can adapt when conditions change. Anthropic’s post also notes that Tetsuwan used Claude and MHS in a closed-loop optimization experiment to improve compiler heuristics, testing 9,143 individual dispenses, 300 unique transfer types, and 1,508 measured conditions across four liquid types.

This is why we invested in Tetsuwan. Biology is dynamic. Experiments vary from run to run. The long tail of scientific work cannot be automated with rigid, one-off configurations alone. It needs an operating system that can turn scientific intent into reliable execution across real-world instruments.

ResearchOS and MHS point toward that future: labs where researchers can express what they want to test, agents can help translate that intent into workflows, and automated equipment can execute, monitor, recover, and improve over time.

Congratulations to Cristian Ponce, Théo Schäfer, and the Tetsuwan team on being part of Anthropic’s Model Hardware Standard research preview. This is an exciting step toward making experimentation more accessible, reproducible, and programmable.

Read Anthropic’s announcement.

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

Congratulations to OneLot on being named to Forbes Asia’s 100 to Watch list.

OneLot is building financial infrastructure for used-car dealers in the Philippines. The company provides working capital loans that help dealers expand inventory, paired with a dealership management system for operations like inventory tracking, marketing tools, and market insights.

The market need is straightforward: used-car dealers often need capital before they can grow. Inventory drives sales, but buying inventory requires financing, and many small and mid-sized dealers do not have access to flexible credit products built around how their businesses actually operate. OneLot addresses that gap with credit lines secured by vehicles, using AI and in-person inspections to assess dealer inventory before extending financing.

That combination of lending and software is what makes the model interesting. Financing helps dealers buy more cars. Software helps them manage those cars more effectively. Over time, the operating layer can also create better visibility into dealer performance, inventory quality, and market demand.

Forbes Asia’s 100 to Watch list highlights rising startups and small businesses across Asia-Pacific, with companies selected across categories including enterprise technology, fintech, robotics, and other high-growth sectors. OneLot’s inclusion is a strong recognition of the team’s work bringing better financial tools to a fragmented and important market.

Congratulations to Harm-Julian Schumacher and the OneLot team on the recognition. We’re excited to see the company continue building for dealers across the Philippines.

Read the Manila Bulletin piece

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

We invested in Starcloud because the team is working on one of the most important infrastructure questions of the AI era: where will the next generation of compute live?

AI is often discussed as a model, software, or chip story. But the more it scales, the more it becomes a physical infrastructure story. Data centers need power. They need cooling. They need land, permitting, interconnection, supply chains, and massive capital deployment. The constraints are not theoretical; they are already shaping where and how AI systems can be built.

Starcloud is taking a very different approach: orbital data centers.

The company is developing compute infrastructure in space, where satellites can use continuous solar power and the thermal environment of orbit to support AI workloads beyond the limits of terrestrial facilities. That idea sounds futuristic until you look at the direction of AI demand. If compute keeps becoming one of the defining scarce resources of the next decade, then expanding the geography of compute is not a novelty. It is infrastructure.

The team is already proving pieces of the system. TechCrunch notes that Starcloud is the only company it knows of currently operating an Nvidia H100 terrestrial data center GPU in orbit, and the first to train a model using it. That experience is informing Nvidia’s work on a purpose-built space GPU, the Vera Rubin Space-1 chip.

The company is also thinking beyond one spacecraft. TechCrunch reports that Starcloud has requested permission from the FCC to operate 88,000 spacecraft and is working to secure future launch capacity as access to space becomes more constrained. Near term, the company is focused on launching two Starcloud-2 satellites in 2027, each designed for 8 kW compute and intended to perform orbital inference tasks for customers including U.S. government agencies. Longer term, Starcloud is building toward a much larger orbital inference layer.

This is exactly the kind of deep tech company we are excited to back: technically ambitious, infrastructure-defining, and built around a constraint that is only becoming more important. Orbital data centers sit at the intersection of space, AI, energy, chips, launch, and manufacturing. It is a hard problem, but it is also a category-defining one.

Congratulations to Philip Johnston, Ezra Feilden, Adi Oltean, and the entire Starcloud team on a major financing milestone and an even bigger vision for the future of compute.

Read the full TechCrunch article.

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

Fishwife’s new limited-time partnership with Sweetgreen brings the brand into one of the most visible fast-casual food routines in the country. The collaboration includes two menu items: the Fishwife Summer Niçoise, made with Spanish lemon albacore tuna, soft egg, summer vegetables, and lemon-tarragon vinaigrette; and Omega Glow, a rice bowl with miso-glazed salmon and Sweetgreen’s new miso sesame ginger dressing.

Food Network’s review gave the clearest read on why the collaboration works. The writer called the Fishwife Summer Niçoise the best and most sophisticated salad they had ever had from Sweetgreen, praising the lemon-tarragon dressing and Mediterranean feel of the bowl. Their only real ask: make it permanent.

That response matters because Fishwife has never been just about canned seafood as a commodity. The brand has helped reframe tinned fish as colorful, design-forward, premium, and culturally current. It is the kind of category work that turns a shelf-stable product into something people talk about, gift, photograph, and build meals around.

Sweetgreen is a natural next stage for that story. The collaboration takes the Fishwife brand out of the pantry and into an everyday lunch decision, showing how tinned fish can fit into the habits of customers who may not have thought of it as part of their regular rotation.

It is also a reminder that consumer-category shifts often show up first as taste, design, and culture before they show up as scale. Fishwife made tinned fish feel modern and desirable; Sweetgreen gives that movement a mainstream, highly visible format.

Congrats to Becca Millstein and the Fishwife team on a partnership that captures where the category is headed: premium, playful, and increasingly part of everyday food culture.

Read the Food Network review.

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

Nearshoring is often framed as a logistics story: shorter routes, lower geopolitical exposure, faster turnaround, and closer customer relationships. But in practice, one of the biggest barriers is much more basic: buyers need to know what factories can actually make.

In a Mexico Business News interview, Yumari’s Andrés Díaz lays out the core challenge. China’s manufacturing ecosystem has spent decades digitizing factory offerings through platforms like Alibaba, Global Sources, and Made-in-China. In Latin America, no equivalent data layer has existed at scale. The region has technically sophisticated factories, but structured information on capacity, materials, quality levels, pricing ranges, timelines, compliance, and specialization is fragmented or missing.

That missing infrastructure makes it difficult for global buyers to move programs from Asia into the Americas, even when the underlying manufacturing capability is already there.

Yumari is addressing that gap with AI agents that gather and structure operational data from both sides of the market. On the factory side, those agents help capture the real context behind production claims: available capacity, material constraints, quality standards, shift schedules, delays, logistics steps, and price targets. On the buyer side, agents identify exact procurement needs, from product specifications and volumes to delivery timelines.

The result is a more precise model of what regional factories can execute, when, and under what conditions. That matters because nearshoring only works if buyers can trust the visibility behind the match. Proximity alone is not enough; the market needs a reliable way to map demand to real manufacturing capacity.

The interview also highlights why this shift is timely. As brands face greater pressure around supply chain resilience, sustainability, labor standards, and tariff exposure, Latin America has a compelling opportunity to become a more competitive manufacturing hub. Yumari’s platform helps make that opportunity legible by digitizing the specialized capabilities that already exist across the region.

Congrats to Andrés Díaz and the Yumari team on the Mexico Business News feature and on building critical infrastructure for the next chapter of regional manufacturing.

Read the full Mexico Business News interview.

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

It is an exciting moment for Eudia, which recently announced a collaboration with Microsoft to bring enterprise intelligence and specialized AI agents directly into the tools where knowledge work already happens.

Eudia is integrating across the Microsoft 365 ecosystem, including Word, Outlook, SharePoint, and OneDrive, while building on Microsoft Azure infrastructure. The collaboration also includes a joint go-to-market motion with Microsoft’s enterprise sales organization and plans for Eudia to become available through the Microsoft Marketplace.

For us, the announcement is particularly interesting because it reflects an important evolution in how enterprises are beginning to adopt agentic AI.

The opportunity is not simply to automate repetitive tasks. The much larger opportunity is to scale the judgment, expertise, and institutional knowledge of an organization’s best operators and make that intelligence available to the broader organization.

That is the idea behind Eudia’s Expert Digital Twins and specialized AI agents. Rather than functioning as generic assistants, these systems are designed to capture how experts within an organization think and operate, then make that knowledge accessible across teams and workflows.

Eudia initially built deeply within the legal function, where institutional knowledge, judgment, and context are particularly important. But the same intelligence can increasingly extend into the business teams legal supports, including sales, procurement, marketing, and finance.

Embedding that intelligence directly into Microsoft 365 is an important part of the equation. Enterprise AI becomes significantly more useful when employees do not need to leave their existing workflows to access it. Instead, the intelligence can appear inside the documents, emails, files, and collaboration environments where work is already taking place.

Eudia is already working with major enterprises including ServiceNow, Cargill, Toshiba, Ecolab, and Bayer, with its technology being used within Microsoft 365 environments.

The Microsoft collaboration provides another meaningful distribution channel for Eudia as enterprises increasingly move from experimenting with general-purpose AI toward deploying specialized agents that understand their organizations, workflows, and institutional knowledge.

We continue to believe that some of the most valuable enterprise AI companies will not simply replace individual tasks. They will create a new intelligence layer across organizations, enabling expertise that was previously concentrated in a small number of people to become available much more broadly.

Big congratulations to Omar Haroun, Ashish Agrawal, and the entire Eudia team on this milestone.

Read more: Eudia Announces Collaboration with Microsoft

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

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.