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!

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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

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Anyone who has managed files for a growing team (or even personal files for that matter), knows how quickly things can get messy. Digital assets and documents end up scattered across drives, tools, and folders, and suddenly no one knows where to find the “right” one. Is it “final draft,” “final-final,” “final-v3”...? Traditional Data Asset Management (DAM) tools exist to solve this, but they’re often built for enterprise budgets and typically require heavy setup. Stockpress is closing that gap with a DAM that’s intuitive and affordable enough for companies of every size. Using AI tagging, facial recognition, text extraction, video transcription, and other metadata tools, Stockpress makes files searchable by what’s actually in them rather than just a file name. In addition, they eliminate duplicates and provide version stacking so teams never have to guess which version of the file is the approved one.

Before co-founding Stockpress, Jessica Storry, CEO, built her career in digital design, web development, and creative agency work. She launched her own agency, where she led creative and client work for startups and enterprise brands. Jessica first connected with co-founders Bartosz Romanowski, and Kamila Romanowska, over 15 years ago, when she bought a WordPress theme that they had built. She then hired them for a freelance project and what began as an email-only working relationship grew into a close friendship and eventually a full partnership. Their co-founder Ian Parkes, then joined their digital agency to lead sales and marketing in the UK. The idea for Stockpress came when an enterprise client asked the agency to customize an existing digital asset management system, and Bart realized they could build something simpler and better themselves. So the four frustrated creatives built a tool to help people spend less time looking for files and more time using them.

What’s Stockpress’ North Star?

We want to make Digital Asset Management accessible to everyone. A lot of people don’t even know what a DAM is, or they can’t afford one. We’ve built something simple that anyone can start using without a big investment or learning curve.

What sets Stockpress apart?

Most Digital Asset Management platforms are built like enterprise software: complicated, expensive, and dependent on sales and onboarding teams. The more you can upsell, the more it costs per admin, per user, and the whole thing balloons. We built Stockpress to be self-serve and easy to use from day one. About 70% of our customers sign up and use the product without needing a demo.

We are also built to scale. Some customers have just three people in their account, while others have more than 12,000 users. Teams can start small without worrying that they will outgrow the platform as they scale. We also offer a free trial so teams can try Stockpress for themselves and decide if it’s the right fit before committing.

Tell us about some recent milestones Stockpress crushed.

We became profitable last quarter and have doubled our revenue every year since taking on investment. We’re already on track to continue that growth this year, even as we hire two additional team members. Also, our annual churn is below 4%, which we’re incredibly proud of.

How does Stockpress inspire “customer love”?

Customers often tell us, “This is so easy. I don’t even need help setting it up.” Our strongest customer segments are leisure and tourism, education, nonprofits, and e-commerce brands. These organizations tend to have a large volume of content, and their marketing and communications teams need a simple way to manage it all. Our nonprofit customers are especially meaningful to me, as I worked with nonprofits earlier in my career and I know how much they’re asked to accomplish with limited resources. Many are moving away from expensive enterprise DAM tools, where pricing can be out of reach. We offer nonprofits a 30% lifetime discount because they face the same file-management problems as everyone else, but often with far less budget.

How do you maintain a good work-life balance?

I adopted a dog named Charlie about a year ago, and she has completely changed how I spend my free time. I take her to agility classes, scent-work courses, and the beach almost every morning. We live about eight minutes from the beach in Florida, and that daily walk has become a real mental reset before I start work.

Fun fact:

I know American Sign Language. I first learned it in high school, loved it, and continued taking courses after college. I do not use it as often now, but it still brings me joy whenever I see it.

From the archives: Listen to Reto Bolliger with Harm-Julian Schumacher on the Venture Everywhere podcast: The Car Warranty Chaiz. Now on Apple & Spotify. Check out all our past episodes here!

Performance advertisers often hit the same wall: they can see which ads are winning, but not why. So scaling creative output becomes expensive guesswork with a lot of losing tests along the way. Segwise solves this with AI creative analytics that tags and analyzes every ad a brand runs, surfacing the patterns behind its top performers and turning those insights into new, on-brand statics, videos, and playables that can lift ROAS by up to 30%. The platform serves some of the largest mobile games, mobile apps, CPG brands, DTC brands, and performance agencies, giving creative teams a data-backed shortcut from “what’s working” to “what’s next.”

Co-founder and CEO Brijesh Bharadwaj brings 12+ years of Growth and Product leadership across AdTech and fast-scaling mobile apps. He teamed up with co-founder Shobhit Gupta, CTO, whose engineering background spans WhatsApp, Uber, and Yahoo. The two met at a previous company and they decided to focus on turning real customer and market data into ads that consistently outperform.

What’s Segwise’s North Star?

Our North Star is helping businesses find their best customers. I believe advertising, when done well, is really matchmaking. It helps someone with a real problem discover a product that solves it, while helping the business grow. We measure that through ads that produce better results, stronger returns on ad spend, and customers who genuinely value what they buy. Because we want every advertiser to grow, we’re offering a free trial to interested teams at Segwise.ai.

What sets Segwise apart?

Most AI ad tools help customers turn a prompt the customer makes into an image or video. We focus on the harder question: what should you make in the first place? We synthesize performance data, competitor ads, reviews, Reddit research, customer insights and brand guidelines to determine the next ads a company should run, then we make them. Our advantage is turning data into the right creative direction, not simply generating a video from a prompt.

Tell us about some recent milestones that Segwise crushed.

We have grown 4x over the last year and added as much new ARR in 1 month as we had in total 1 year ago, which is a strong sign of accelerating traction. We have also hired our first VP of Sales, moving from founder-led sales toward a more scalable sales organization. Our team now spans the U.S., Europe, and Asia, making us a truly global, all-time-zone company.

How has your background shaped you as a founder?

I have worked in product and growth throughout my career, including at InMobi, where I built app-install advertising products. Product work trains you to make decisions with incomplete information, constantly test assumptions, and learn from mistakes, which is exactly what founding a company requires. Becoming a founder felt like a natural next step in building products and challenging myself to take something from zero to one.

Any favorite resources and books?

Reforge was one of the most valuable experiences for accelerating my product thinking. For leadership, I recommend Radical Candor by Kim Scott. It is the best book I have read on managing people while building trust. For strategy, I recommend 7 Powers by Hamilton Helmer, which offers a clear framework for thinking about durable competitive advantages.

Fun fact:

I used to box competitively. I started boxing to lose weight, got deeply into it, and ended up competing for a couple of years. I got pretty good at it, but eventually decided that getting into a good undergraduate program was probably a better long-term investment than continuing to get punched in the head.

From the archives: Listen to Kate Lambridis with Scott Hartley on the Venture Everywhere podcast: Human-Driven Health. Now on Apple & Spotify. Check out all our past episodes 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.

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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.

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Ticketing is an intensely competitive, low-margin industry with complex technology requirements spanning checkout, scanning, venue access, security, fraud, and chargebacks. Attend is rethinking how teams and venues compete by supporting a wide range of ticketing and revenue use cases. Their flexible platform layers on top of the ticketing infrastructure teams already use, integrating directly with primary systems like Ticketmaster, MLB’s ticketing system, Tickets.com, and SeatGeek. Attend helps reach fans through subscriptions, last-minute inventory, student offers, seat upgrades, flex plans, credit-based products, and premium and suite experiences. Attend helps sports and entertainment brands create more flexible offers that better match how fans want to experience live events.

Co-founders Aaron Holland, CEO, and Robert Beadle, COO, met at a CrossFit gym in Los Angeles, where the two quickly connected over their shared entrepreneurial backgrounds and a ticket-sharing problem they had both experienced as season-ticket holders. In 2019 they launched Season Share to help fans split tickets with friends more easily. When the pandemic disrupted live events, they pivoted to a white-label B2B platform for teams and venues, laying the foundation for Attend. Today, as fans demand more flexibility and teams look for smarter ways to grow revenue, Attend is helping organizations reimagine ticketing for the next generation of live events.

What’s Attend’s North Star?

Attend is built to help sports teams, entertainment organizations, and venues create more flexible ticketing programs for the next generation of fans. We want to make live experiences more accessible and bring people together in an increasingly digitally connected world. That means tracking business KPIs like revenue, conversions, and seats sold, but it also means caring about how many people we help get out of the house and into meaningful, shared experiences.

How has your customer base evolved over time?

Sports remains our foundation, but we have grown well beyond it. Over the past several years, we have expanded into new areas of live entertainment, partnering with leading organizations across theater, concerts, music, comedy, and more. Today, Attend supports a growing range of arts venues and entertainment organizations across North America, bringing our technology to an increasingly diverse set of live experiences.

What’s on the horizon for Attend?

The next step is automation at scale: setting up offers more quickly and creating real one-to-one personalization based on factors like purchase history, interests, location, spending patterns, and family context. Teams have traditionally relied on repetitive, broad “spray-and-pray” sales tactics. We are giving them tools to make offers more relevant, flexible, and aligned with what individual fans can spend and care about.

How has your background influenced you as a founder?

Entrepreneurship is deeply embedded in my family. I am a third-generation entrepreneur, so owning and operating a business always felt like the path I was meant to pursue. In college, I started a marketing agency and used digital-marketing work to put myself through school. That evolved into building profitable technology products for other companies, then reinvesting our earnings to launch standalone businesses of our own. I studied sports management while building technology and SaaS businesses, and I always wanted to find my way back to sports. Ticketing is a difficult but rewarding part of sports technology, and it remains an area with significant room for innovation.

Any advice?

My biggest advice is: sell it, then build it. It is not about what you can build; it is about what customers will actually pay you to solve. Especially now, with AI making it easier to launch fast products, founders need to optimize for what they can sell, not just what they can raise money against. Profitability matters more than ever. Fundraising can depend heavily on timing and luck, but you can control whether you are building something that solves a real market problem and gets you to sustainable revenue. Investors do not want to buy a job; they want to buy a business.

Fun fact:

My family moved from Los Angeles to Bozeman, Montana during COVID and it’s been great because we love the outdoor lifestyle: camping, fishing, and skiing.

From the archives: Listen to Aaron Holland, with Jenny Fielding on the Venture Everywhere podcast: Swipe, Tap, Attend. Now on Apple & Spotify. Check out all our past episodes here!

Mito is the Spanish word for “myth” and mythology is one of humanity’s oldest ways of sharing stories across generations. So it’s a fitting name for a company reimagining how stories are created and told. MITO is an AI-native video platform where filmmakers and AI agents work together to create long visual stories, from the first idea to the final cut. Its customers range from film production companies and ad agencies to internal creative teams at large corporations. Some generate entire videos with AI, while others use MITO in a hybrid workflow that combines studio shoots with AI-powered post-production. MITO is free to try, with enough credits on the free tier to create a few videos before deciding whether to upgrade. They are also hiring across growth, sales, product, marketing, engineering, and operations, so check out the open roles if you’re interested in helping shape the future of storytelling.

Co-founder and CEO Dr. Iñaki Berenguer is one of Spain’s most successful serial tech entrepreneurs and investors, having previously founded CoverWallet (acquired by Aon for $300M in just 4 years), Contactive/Klink (acquired by Thinkingphones), iPronics (raised $100M), and Pixable (acquired by SingTel). He holds a Master’s and PhD in Engineering from Cambridge, an MA from Columbia (as a Fulbright scholar), and an MBA from MIT. His co-founders, Danny Saltaren, CDO, and Arantxa Barcia, CCO, are both celebrated creatives from Spain. Arantxa is a filmmaker, and Danny is a designer who received Spain’s National Design Award from the King of Spain. They teamed up to create a next-generation film studio with an intelligent creative suite built for directors, brands and teams.

What’s the origin of MITO?

Last summer, my co-founder showed me an AI-generated video, and I immediately had that rare feeling that something major was about to change (the same feeling I had when I first used an iPhone, ChatGPT, or Waymo). AI video will transform entertainment and advertising, but also education, robotics, communication, and entirely new industries that have not been invented yet. I wanted to be a protagonist in that shift, not just an investor watching from the sidelines. At the time, creating long-form AI video was complicated and required technical knowledge. We saw an opportunity to make it accessible: a platform where people can create rich, long-form visual stories without needing to understand AI or code.

What sets MITO apart?

MITO is built by filmmakers for filmmakers, with a focus on long-form storytelling rather than short social-media clips. A 10-second TikTok or Instagram video is very different from a film, commercial, or music video that requires character development, story continuity, locations, visual style, music, and a coherent narrative from beginning to end.

We also built MITO as a multiplayer platform from day one. Teams can collaborate with one another inside a project, but they can also work with an AI director. Instead of dragging and dropping tools, users can describe the story they want to tell and have a conversation with the AI, which helps develop the creative direction and builds the project alongside them.

How does MITO inspire customer love?

Customers love three things: lower budgets, much faster turnaround times, and far more room for experimentation. A national TV commercial that once would have required two months of planning (permits, actors, locations, crews, lighting, sound, wardrobes, and equipment) can now go from brief to broadcast in roughly two weeks. More importantly, MITO dramatically expands creative exploration. With traditional footage, teams can only edit what they captured. With AI video, they can test different backgrounds, lighting, styling, characters, locations, and versions of the same concept before committing to a final cut. That makes it possible to prototype a film or commercial as an actual visual experience, not just a script or storyboard.

Tell us about some recent milestones that MITO crushed.

• About a month ago, we launched our AI Director. Previously, users had to configure a lot of elements themselves: selecting characters, prompting, choosing a model, setting duration, and more. Now they can simply chat or speak with the AI Director about the story they want to create. It can suggest shots, ask questions about orientation and style, offer creative options, and then build the video project while the user stays in the loop.

• We also recently acquired a small, highly technical AI company, Kluster AI. Their team is helping us build our own video model, while fine-tuning other parts of the product. It is helping MITO become much more technically ambitious behind the scenes.

How has your background shaped you as a founder?

Across my career, I have tried to build at the beginning of major technology waves. My first company was in photo-based social networking before Instagram; my second was SaaS; my third was insurtech; and my fourth built networking chips for AI data centers before AI infrastructure became a mainstream topic. With Mito, I believe we are again early in an inflection point because AI video will be central not only to entertainment and advertising, but other industries as well.

The sectors have changed, but the DNA of how I build companies has stayed consistent: a strong culture, deep respect for product and engineering, and an urgency to move quickly when a new opportunity appears. In AI, a product advantage can be copied in months rather than years, so the rule is simple: if you have a good idea, run as fast as possible.

Personally, I grew up in a very small town near Alicante, Spain, far from major cities. My father never went to school, yet I eventually studied at MIT, Cambridge, Columbia, and Princeton, built global companies, and had global exits. Coming from where I come from and ending up where I am, it’s almost impossible not to be an optimist. People sometimes call me a paranoid optimist: deeply optimistic about what’s possible, but with a constant sense of urgency.

Any advice for founders?

A great product matters, but distribution matters even more. You can build something exceptional, but if nobody knows it exists, it cannot create value. Strong distribution and growth attracts customers, talent, capital, and attention, resources that can be reinvested into making the product better. The goal isn’t simply to build something you’re proud of; it’s to create value and build the reach necessary to sustain innovation.

Fun fact:
I have run 19 marathons.

From the archives: Listen to Laura McDonald with Scott Hartley on the Venture Everywhere podcast: Fertility in Full FLORA. Now on Apple & Spotify. Check out all our past episodes 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.

Agree.com is closing a gap that traditional e-signature platforms leave open. A signed contract feels like a finished deal, but the work isn’t really done until the payment clears. Agree.com combines free e-signatures with automated invoicing and payment processing in one platform. This gives revenue teams a single system instead of a patchwork of tools. The company works closely with founders, operations leaders, and finance teams (a.k.a the people who send agreements, collect signatures, and chase down payments.) Agree.com folds all three steps into one flow with the goal to provide revenue that runs itself. From agreements to billing, payments, collections, and reporting, Agree.com automates the entire contract-to-cash stack. The platform continues to expand its reach, working with companies of all sizes that want revenue to move without friction.

The partnership between co-founders Will Hubbard, COO, and Marty Ringlein, CEO, actually started at a poker table. Will was hosting a game for founders and investors in the Bay Area. Will was in the process of selling his first company and Marty had just sold his second company to Eventbrite around that same time. Will asked Marty for help making sense of a mountain of legal paperwork. That conversation sparked a friendship, working relationship, and the idea for Agree.com. Marty later introduced Will to longtime friend Evan Dudla, an experienced founder and software engineer to become co-founder and CTO. Marty and Will’s collaboration goes beyond the company too. They co-teach a course on AI and product development at Northwestern University, where they sometimes update their slides the night before class to keep up with how quickly the field is evolving. This is a reflection of how they work at Agree.com, staying flexible, moving quickly, and adapting as they build.

Let’s agree to Agree!

What’s Agree.com’s North Star?

Agree.com is an all-in-one contracting and billing platform built to put revenue on autopilot. Early on, our North Star was getting as many people as possible to send contracts through our free e-signature product. That created a viral loop: someone receives an agreement or pays an invoice through Agree.com, has a great experience, and wants to use it for their own business. Right now we’re focused on invoice volume and helping more established businesses (primarily companies doing seven or eight figures in revenue) run more of their contracting, invoicing, subscriptions, and payments through Agree.com.

What sets Agree.com apart?

We replace a fragmented workflow. Before Agree.com, companies often needed separate tools for e-signatures, invoicing, subscriptions, payments, accounting, CRM, and internal coordination. We bring those workflows into one place, helping teams collapse steps, improve visibility, and make their operations more efficient.

How does Agree.com inspire “customer love”?

The stories I love most are when someone receives an invoice through Agree.com and becomes a customer themselves. I recently onboarded someone who told me, “I just paid an invoice to somebody else on Agree.com, and it was so good that I reached out and booked a demo with you guys.” They wanted to give their own customers that same experience. We’ve signed some big AI companies like Anthropic, Cursor, Eleven Labs, as well as more traditional companies, like JPMorgan Chase. For me, it is incredibly meaningful to see those logos come through. It validates that Agree.com is becoming part of how serious companies actually do business.

How is AI changing what’s possible with Agree.com?

We create some really powerful “wow” moments with AI. Through our MCP server, customers can use Claude or ChatGPT to create agreements, send invoices, create subscriptions, update contacts, and run reports. I have finance teams tell me they can finally run highly specific reports they have wanted for years. We use it internally, too: Claude can review my meeting notes, identify when a prospect has said yes, generate the contract with the agreed pricing and contact information, and hand it to me ready to review and send. That level of automation can make an entire revenue workflow feel like it is on autopilot.

How has your background influenced your approach to building Agree.com?

I’m a repeat founder, and I have personally lived the accounts-receivable pain we are solving. I started my first business when I was about 22 and landed six-figure deals with Fortune 500 companies. Those contracts had net-60 payment terms, and I assumed that meant I would be paid on day 60. Instead, many of those companies paid months late. I was the person manually sending reminders and feeling like the bad guy just for asking to be paid. That experience shaped Agree.com’s founding thesis: e-signature is a commodity that people do not want to pay for, so we can offer it for free and build a much better payments and accounts-receivable business around it. My co-founders and I have brought that firsthand experience into many of our product decisions.

Any advice?

Prioritize your health, because if you’re not mentally, physically, and emotionally healthy, the business isn’t going to be healthy either.

Fun fact:

I rescued two small parrots. I found one on the side of the road, tried to find its owner through vets, pet stores, and flyers, and eventually realized it had likely been abandoned. Since parrots are social animals, I had to get her a companion. I never imagined I would become a bird person, but now I have two little parrots chirping away in the other room.

From the archives: Listen to Marty Ringlein with Andy Ambrose on the Venture Everywhere podcast: Let’s Agree to Agree.com. Now on Apple & Spotify. Check out all our past episodes 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.

Nobody should put their financial future at risk trying to stay healthy, but for millions of Americans on employer-sponsored insurance, that’s exactly the challenge. Handl Health started out connecting consumers directly to healthcare price-transparency data, but quickly realized the best way to cut costs at scale was to focus on the employers, brokers, and carriers who actually design and manage health plans. That shift led to Handl giving employers everything they need to build better health plans and, more importantly, see results. On the ground, that means Handl gives those decision-makers the data and tools to build smarter benefits, track their impact, and reduce waste. For employees, that translates into guidance toward high-value providers and support navigating the healthcare system when they need it most.

Co-founders Ria Shah, Chief Product Officer, and Ahmed Marmoush, CEO, met while working together in healthcare analytics at Ernst & Young-Parthenon. Ria’s background is in data analytics and actuarial modeling, and her work at EY-P on value- and outcomes-based contracting showed her firsthand how broken healthcare’s information layer can be. Ahmed’s background in healthcare management consulting gave the pair a shared perspective on the challenges facing the system. Ria shares more about the company and vision for a more transparent healthcare system.

Why Handl Health and why now?

In 2022, Ahmed and I received an NIH SBIR grant to study how federal price-transparency laws were affecting employers and consumers. The data was difficult to access and nearly impossible to interpret—despite being called “machine-readable.” But we realized that, when combined with other datasets and the right technology, it could help make healthcare more affordable and accessible. Handl began as a passion project and grew into a company built to turn that insight into action.

What’s Handl Health’s North Star?

Our North Star is helping people get the right care at the right time for a price they can afford. We do that by helping employers build more personalized, cost-effective health plans around the real needs of their people. We believe access to essential care at a fair price should be a given—not a privilege.

What sets Handl Health apart?

Handl Health is an end-to-end health-plan design and execution platform built on healthcare data. While many companies stop at analytics, Handl helps employers, brokers, and carriers turn insights into action: from designing and implementing plans to managing benefits and measuring results. As healthcare reaches an inflection point, Handl is using AI and better data to make plan design faster and more precise, with tools like episode-of-care provider tiering and variable-copay plans that give employers new ways to lower costs and rethink health insurance.

Tell us about a recent milestone that Handl Health crushed.

We closed our Series A a few months ago with a diverse group of investors. It reflects growing demand for better tools to untangle employer-sponsored healthcare and help employers, brokers, and carriers create more meaningful health insurance for patients.

How has your background influenced you as a founder?

This mission is personal to me, especially for the people and families who need support the most and should not have to go broke trying to stay healthy. My parents emigrated from India to California and built their own business in the jewelry and watch industry. I grew up watching them take risks, work with purpose, and always have another project in motion. It was a busy but fulfilling environment, and it showed me early on what it means to build something from the ground up. At the same time I saw the barriers my family and community faced when navigating U.S. healthcare. I initially thought becoming a frontline caregiver was the only way to make a meaningful difference, but my work with healthcare data showed me another path.

Fun fact:
I go to a lot of concerts. Live music is one of the few places where I am perfectly happy to stand still, put everything else aside, and focus completely in the moment.

From the archives: Listen to Kate Lambridis with Scott Hartley on the Venture Everywhere podcast: Human-Driven Health. Now on Apple & Spotify. Check out all our past episodes 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.

Cloud costs are climbing as companies juggle AWS, Azure, and GCP bills alongside a fast-growing new line item: AI spend. North.cloud is a financial automation platform that uses AI to help companies autonomously control cloud, data, and AI spend. Trained on years of data achieving over $100M of savings, North takes just 5 minutes to set up and can cut a company’s cloud expenses by 30% or more within the first day. Originally focused on AWS and GCP, the platform has since expanded to Azure and is now integrating with AI and data platforms like Anthropic, OpenAI, and Snowflake. Their goal is to give companies a single tool to manage cloud, data, and AI spend.

Co-founder and CTO Yassine Açoine spent years leading engineering organizations where cloud spend was a constant challenge, even when it wasn’t directly his responsibility. Ready for something new, he began exploring AI startup ideas before meeting co-founder and CEO Matt Biringer, who brought over a decade of experience selling datacenter technology and had seen firsthand how companies struggled to make smart AWS commitment decisions. Convinced by the opportunity, Yassine built a working MVP in just 40 days. It was a simple prototype, but it proved the concept and became the foundation for North.

North is growing quickly and actively hiring engineers and builders who want to work at the intersection of AI and cloud infrastructure. If you’re excited about solving complex infrastructure challenges and helping define the future of AI-powered cloud operations, they’re looking for talented people to join the team.

What is North’s North Star?

North helps companies take control of their cloud spend by enabling meaningful savings in several ways. We help teams restructure their codebases and infrastructure so they’re properly optimized. We guide engineers away from over-provisioning and help them strike the right balance between high reliability and minimal waste. We also give companies a clear view of where every dollar is going, who owns that spend, and how costs should be allocated across teams, products, and business units.

Why will North win?

We’re not trying to solve one tiny slice of the problem, and then force customers to use five other tools to complete the story. We want to be the one application for everything related to cloud financial operations. Another key differentiator is our methodology and customer success approach. Customers aren’t just buying a SaaS product; they’re buying a product plus a team that’s always there to support them, which makes adoption and impact much smoother.

How does North inspire “customer love”?

We inspire customer love by turning cloud savings into fuel for growth, giving teams real dollars back to reinvest into R&D, hiring, and new products. We focus upmarket, where leadership has already told engineering to cut spend and mature cost allocation. North delivers the visibility and maturity that makes those savings possible. Brave is a great example: North helped them save about 40% on cloud costs, freeing up capital to build their own LLM-based search engine to rival Google Chrome. They’ve said North helped make them a leading AI company. Another case is AssemblyAI, whose team told our investors they’re not sure they’d have reached profitability without North. We’re not just cutting bills, we’re impacting the balance sheet and giving leaders room to reinvest.

Tell us about a recent milestone that North crushed.

We’re approaching $1 billion in annual cloud spend under management. That’s the combined cloud spend of all the companies using or signed up for our platform. We’ve also delivered over $100 million in direct savings to customers so far. Both numbers feel massive, and they’re good indicators of the scale of the problem we’re tackling and the value we’re providing.

How has your background influenced you as a founder?

I’ve always gravitated toward leadership roles. In high school, I was captain of three sports teams (soccer, badminton, and volleyball) and I’ve always been driven to challenge myself. I grew up switching between Arabic, French, English, and Amazigh in Morocco, so talking to people from different worlds has always felt natural to me. Traveling a lot since then has only sharpened that instinct. I try to meet people where they are and explain things in a way that actually clicks. I’m very tuned in to how people react to complex topics, so I try to explain abstract, esoteric concepts using diagrams, concrete examples, and scenarios from user, product, and engineering perspectives. Professionally, my first job was in a small team that grew to over 100 people; being there early gave me deep exposure to the cloud and forced me to prove myself as a young leader. That combination of communication, early leadership, and sensitivity to how people learn has been crucial for building products and leading teams at North.

Fun fact:
When I was 13, my dad’s company couldn’t find a translator, so I spent three weeks in China translating business meetings from English to French. It was a real crash course in interpretation and international business for an eighth-grader.

From the archives: Listen to Matt Biringer with Jenny Fielding on the Venture Everywhere podcast: Cloud Cover. Now on Apple & Spotify. Check out all our past episodes here!