How we built Draper's AI stack: automate the routine to amplify the human work

Written by Michelle Kwok, Andrew Hyun, and Patrick Blumenthal

Two years ago, Draper's company data lived in eight Excel sheets. People dropped them into AI chats and hoped the models would be able to parse really complex data. And therefore, all workflows were siloed, with limited visibility, and no cohesive automation.

The team was spending hours a week asking around for this siloed data that lived in other people's chats or inboxes. Asking for contacts we weren't sure we had, updates from founders scattered across inboxes, meeting notes that weren't transcribed, puzzling together a competitive landscape, the list goes on. Instead of incessantly information gathering manually, they could have spent this time being present with founders, making judgment calls on teams, and digging deep into emerging industries. The human work that AI cannot do.

Today, we've centralized all of that data into an evergreen base that is auto-updated with our companies' latest moves, from their key numbers to their weekly updates, via a series of automated workflows that everyone has access and visibility into.

Every company and founder, from the second we meet them to every follow-on check, has one singular record that is automatically updated with every new piece of info, every automatically transcribed meeting (using Otter.ai), and every update that any of our team members receives.

We've built a custom machine learning model to read through the hundreds of inbound deals we get every week, score them against four decades of our own decisions, and surface the most promising leads for our investment team to take over on. To keep us on top of every situation, our AI system briefs us on the day's meetings and the most urgent matters across our 400+ portfolio companies.

To best service our founders, our system drafts warm intros for them from a network of 15,000+ contacts.

And to wrap it all up with a bow, all this internal data was vectorized so that it could be used for semantic search, and we can now query it with confidence via our own MCP server.

We built our AI infrastructure to get to know more founders, expand our information gathering abilities, keep our internal data and ops smooth and easy to access, and really just take the routine work off everyone's plate, so that we can get into the human part of this job. Meeting people, making the final judgment. The critical thinking that AI cannot yet do in VC, at such an early stage of investment.

Huge thank you to Tim Draper, who inspired this journey. He challenged us to build repeatable infrastructure that could help our team answer every founder who reaches us, find the ones who haven't told anyone they're building yet, and service our own portfolio founders better every day.

The rest of this piece covers the five decisions we made before building anything, then each tool and what it runs on, and ends with the whole stack in one list.

Five decisions shaped everything we built

The first and most important one had nothing to do with AI. We decided where our data would live: those eight spreadsheets became one Airtable base, one record per company, and everything since has either fed that base or been built on top of it. Because we centralized from the beginning, every tool works from reliable, evergreen data, and each automation keeps the base current for the next one. Without that, the same tools would be automating on top of stale exports.

The second was to build on infrastructure we already own. Everything here runs on Airtable, Zapier, Power Automate, Google Drive, Slack, Claude, and Railway for the services we host ourselves. Every person on the team had their own workflow, so we wanted to custom build instead of buy off-the-shelf, to increase adoption and comfort for each team member. We added no new vendors and no external middleware, so when something needs to change we edit a prompt or a Zap rather than ship a deploy. (No-code automations for the win!) We customized the judgment inside the tools, because that part has to be ours: an off-the-shelf lead scorer doesn't know Draper's thesis or the companies we passed on, and a generic meeting brief doesn't know which meeting is a founder's first.

The third decision was about people: MBA interns at Draper pitch a tool to build on top of our foundation in their interview the way a founder pitches a company. Then they get the guidance, infrastructure, and the mandate to ship it to production. It's the same bet we make on founders.

The fourth was a rule for anywhere the data has to be right: when an automated system isn't sure, it stops and asks a person on the investment team instead of guessing.

The last decision was to document every tool the way we'd ship a product: what it is, why it exists, how it was built, how to use it, with a video walkthrough, so the next person can pick it up in five minutes and keep building.

A forwarded email creates the singular record each company will have in perpetuity at Draper

The foundation of the whole system is also the simplest part. To add a new deal, anyone on our team forwards the founder's inbound pitch email to a dedicated internal inbox, and the full opportunity record is created automatically: an AI-written company summary, the round, and the pitch deck converted to a PDF and attached.

To log a founder update, we forward it to another inbox, and it lands on the right company's already-created record automatically, matched by the founder's email domain, with the key numbers extracted.

New contacts work the same way, straight into our network map. And when a meeting lands on a calendar, Otter.ai automatically transcribes it and the notes are immediately tagged to the right company's record.

The same records can be created inside Claude through our MCP server: paste the founder's thread, review the preview, and it writes to Airtable, from a phone if that's where you are. This habit keeps the base evergreen without anyone doing data entry, and our team spends those minutes with founders instead.

From the second they pitch us in an email, to every meeting we have, to every follow-on investment we make, the company has one singular record here at Draper, tagged with all their relevant information, automatically.

Draper Brain answers questions from the firm's own records

Draper Brain is our own MCP server, a custom connector that plugs our internal data directly into Claude, so anyone at the firm can get answers from our records in plain English: 15,000+ contacts, records on every one of our 400+ portfolio companies, 4,900+ co-investors, and 1,900+ meeting notes, all vectorized for semantic search and reachable from a phone. It pulls from our Airtable and our Google Drive, and for companies outside our records it adds filtered private company data from Harmonic, a licensed dataset covering more than 35 million companies.

It writes too: paste a founder's email thread into Claude and it creates the deal record, converts the deck link to a PDF, attaches it, and pulls the contents into a summary. Mapping a competitive landscape for an investment memo used to take half a day of research. It now takes minutes.

The Deal Engine handles a different problem: picking which of hundreds of companies to get to know first.

The Deal Engine narrows hundreds of companies to the top 5 that best fit our thesis

We trained a machine learning model on our entire history: every company we screened, backed, passed on, or watched exit. Every week it ingests the newest startups from Harmonic's API, which returns every company in the same consistent shape a model needs, scores each one on eight dimensions, founder DNA and contrarian thesis among them, and emails our investment team the ones that look like a real fit for us. Out of the hundreds of companies every week we could plausibly talk to, it surfaces the top 5 or so that fit our thesis best, so our investment team's time goes to the founders we're most likely to back. Feed it a check size and valuation assumptions and it returns bull, base, and bear MOIC cases, and it retrains as real outcomes come in.

The recurring work runs on a schedule

Every weekday morning, a brief on the day ahead lands in each of our inboxes. It runs as a scheduled Claude task with no custom hosting. The system reads Outlook with read-only access, discards cancelled events and duplicate holds, checks every external attendee against our CRM, and has an AI read the actual email history to judge whether a meeting is a first conversation or a continuing one. When it isn't sure, it labels the meeting a first conversation and flags it for a person, because a founder's first meeting with us deserves our best. The brief also surfaces the most urgent matters across our 400+ portfolio companies, and research agents prep each meeting: who we're meeting, where things stand, what to ask.

Founder updates used to pile up across five inboxes throughout the whole team. Now every update lands on the company's record with ARR, runway, milestones, and raise status extracted, and any company that has gone 60 days quiet gets flagged so we reach out early and ask how we can help.

Each week, our finance lead sends the fund models as Excel attachments, so we have a scheduled Claude task that reads them and updates our invested amounts, ownership, valuations, and LP value into every portfolio record, moving newly funded deals to Committed. When a match is uncertain, the task writes nothing and asks a person on Slack.

Our LP investments get the same treatment. One of the Draper entities is an LP in more than 80 venture funds, and that portfolio lived in scattered spreadsheets too. A fund email forwarded to a dedicated inbox with a trigger word now gets logged, run through AI pre-diligence against our GP evaluation framework, and returned as a snapshot with green flags, red flags, call prep, and a meet recommendation. That pipeline is Zapier end to end, and a scheduled Claude task assembles the report that arrives every Thursday at 4pm, showcasing the funds we're looking at, the potential dealflow we could share, and any actions that are left to be done, just so that nothing falls through the cracks.

Our crypto book has its own dashboard, built in-house because much of its value sits in locked, vesting, or pre-launch tokens that normal portfolio tools can't represent. It tracks every unlock schedule and answers questions in plain English.

A single form handles founder intro requests

Our founders see one piece of this directly. We rebuilt our founder hub around quick actions, perks, and discounts, and the warm intro requests that used to arrive over email, text, and WhatsApp became a single Airtable form. A founder submits it, a Zapier flow calls Draper Brain to search our full network, and a ready-to-send opt-in email lands in an investment team inbox. Usage is up 10x since the relaunch.

The whole stack at a glance

• Adding deals, updates, and contacts: dedicated internal inboxes, parsed by Zapier flows into our Airtable base. The same records can also be created directly through our MCP server in Claude.
• Meeting capture: Otter.ai transcripts tagged to the company record automatically.
• Lead and opportunity scoring: Airtable automations calling a language model.
• Deck capture: the MCP server converts DocSend, Drive, Slides, Dropbox, and OneDrive links to PDFs and attaches them to the record.
• Draper Brain: our custom MCP server, hosted on Railway, reading Airtable, Google Drive, and Harmonic's licensed external data, vectorized for semantic search.
• Deal Engine: our custom ML model and web app trained on our deal history, with Harmonic's weekly feed of new companies, emailed to the team weekly.
• Daily briefs: a scheduled Claude task reading Outlook (read-only), our CRM, and portfolio updates.
• Fund financials sync: Power Automate plus a scheduled Claude task reading the weekly Excel models.
• LP fund platform: Zapier plus a scheduled Claude task, fed by fund emails to a dedicated inbox.
• Warm intros: an Airtable form and a Zapier flow that calls Draper Brain.
• Crypto dashboard: our in-house web app tracking token positions and vesting schedules.

Three of those are custom in-house-built software: the MCP server, the Deal Engine, and the crypto dashboard. The rest run on the same Zapier, Airtable, and Claude accounts we already had.

Each tool improves the data the others rely on

None of these tools stands alone. The Deal Engine trains on records the weekly syncs keep current, and the morning brief reads the same base that the forwarded emails and lead scores keep rich. Each new tool starts from data the others already maintain, which is the payoff of putting everything in one place first. The time it frees up goes back to meeting founders and making the final judgment.

The AI gave us back the part of venture capital that has to stay human

The point of all this was never about building AI to build AI. It was the hours. The data entry, the deck chasing, the founder updates scattered across inboxes, the contacts we didn't know we had, the half day of competitive research before a memo, all of that used to sit between us and the work only people can do. Now it runs on a schedule and lands in one record, so our team spends that time in the room instead. Being present in a founder on their first call, instead of desperately searching for pre-meeting info and previous notes. Asking the question the model would not have thought to ask. Making the judgment call on a company with three employees and no revenue, where the only real signal is the person in front of you. AI gave us back the part of venture capital that has to stay human.

We wanted a place to tell our own story, on our own terms, without waiting for someone else to write it. So we built one.

From here on, fund announcements, portfolio milestones, and the ideas we are thinking about will land here first.

We co-led Scout AI's $100 million Series A because the next decade of defense will not be decided by who has the most hardware. It will be decided by who has the best software running it.

The AI brain for autonomous defense

Scout AI is building Fury, a vision-language-action model that turns a commander's intent into coordinated action across fleets of drones, ground vehicles, and unmanned craft, including in the GPS-denied and communications-jammed conditions where today's systems fail. Think of it less as a better drone and more as the brain that lets thousands of them act together.

Founders Colby Adcock and Collin Otis started the company in 2024. In its first year, a team of 34 people booked $11 million in Department of War contracts, unveiled an orchestration layer called Ox, and publicly demonstrated a fully autonomous strike mission run end to end by AI agents.

Why we backed it

We have spent years backing founders who take on hard, unglamorous problems before the market is ready. Autonomous defense is one of the hardest. The round, which we co-led with Align Ventures, was oversubscribed and drew in Decisive Point, Booz Allen Ventures, and a deep bench of defense and venture investors.

“Scout AI is exactly the company this moment demands.”
Tyrone Lee, Draper Associates

Founder Colby Adcock put it more bluntly: this historic raise is a signal to every patriot in Silicon Valley. We agree, and we are proud to help build the brain behind the West's autonomous edge.

Your blood stem cells are the source of your entire immune system. As they age, your body's defenses weaken. We led HexemBio's $10.4 million seed round because the company found a way to make old blood stem cells young again, without gene editing.

Rejuvenation outside the body

HexemBio uses a proprietary synthetic niche, an engineered environment that mimics the conditions where stem cells are born, to rejuvenate a patient's own blood stem cells outside the body. The renewed cells are then returned through a standard IV infusion. The first clinical target is blood cancer, where rebuilding a healthy immune system can be the difference between recovery and relapse.

The company emerged from stealth with our round. It was founded by CEO Gabriel Levesque Tremblay alongside CTO Samira Kiani and CBO Samet Yildirim. We led the seed, joined by SOSV, Seraphim Space, and Treeo VC.

Why we led the round

We fund the future first, and few futures are bigger than changing how we age, extending healthy human lifespan. The premise is simple: the decline of blood stem cells is a major driver of aging itself. Start with the bone marrow transplant patients who need it most, prove the science in the clinic, and the long-term implications reach far beyond any single disease. That is precisely the kind of audacious, well-grounded bet we look for, and we are proud to lead it.

Every passenger jet you have ever flown shares the same basic shape: a tube with wings. It has barely changed in seventy years. We led Natilus's $28 million Series A because Aleksey Matyushev and his team are finally changing it.

A new shape for flight

Natilus builds blended-wing-body aircraft, where the fuselage and wings merge into a single lifting surface. The result is dramatic: up to 30 percent less fuel burned, half the carbon emissions, half the operating cost, and 40 percent more cargo volume than a conventional plane of the same footprint. Its first aircraft, the KONA, is a regional freighter carrying 3.8 tons. A larger passenger model, Horizon, follows.

Why we led the round

Aviation is one of the hardest industries in the world to break into, which is exactly why almost no one tries. Natilus already has an order book of more than 570 aircraft worth roughly $24 billion, from customers including Flexport, SpiceJet, Nolinor Aviation, and Ameriflight. That is real demand pulling a new airframe into existence.

“The aviation market is ripe for a new aircraft manufacturing entrant.”
Tim Draper

The $28 million round, which we led, takes Natilus from design and demand to building airplanes. As founder Aleksey Matyushev puts it, the company is not just building aircraft, it is reshaping how the world moves goods and people. We could not agree more, and we are proud to be the lead investor backing it.

We led Radiant's Series D of more than $300 million, alongside Boost VC, because the company has done something the nuclear industry has talked about for decades and never delivered: it built a reactor you can ship.

What Radiant is building

Radiant builds portable nuclear microreactors small enough to fit on a truck. The first unit, called Kaleidos, produces one megawatt of clean power, enough to run a remote community, a disaster zone, a military base, or a data center, with no connection to the grid. It runs on TRISO fuel, the most rugged nuclear fuel ever made, goes five years between refuelings, and is designed to operate for twenty.

Founder and CEO Doug Bernauer started Radiant in 2020 after years at SpaceX, where he went looking for a way to power a base on Mars and realized the same problem was unsolved on Earth. The Series D, which values the company north of $1.8 billion, funds the leap from prototype to production.

Why we backed it

Most energy bets are bets on a slightly better version of what already exists. This is not that. Radiant is moving toward its first fueled demonstration at Idaho National Laboratory in 2026 and is building its R-50 production reactor in Oak Ridge, Tennessee, on the same ground where the Manhattan Project began. Commercial demand is already arriving ahead of the first unit. We were joined in the round by Founders Fund, Chevron Technology Ventures, the Ark Venture Fund, and Friends and Family Capital.

“Radiant Nuclear just raised $300M+ and we were honored to lead the financing. Radiant's team is both visionary and able to execute, a powerful combination.”
Tim Draper

Clean power that arrives by truck and switches on anywhere is exactly the kind of bet we exist to make.

Patents are where the world's best ideas are written down, and also where they go to get buried. The system for searching them is slow, expensive, and decades behind. We co-led NLPatent's $3 million seed round to fix that.

AI that reads patents like an expert

NLPatent uses natural language processing and patent-tuned language models to do in seconds what used to take a specialist days: find the prior art that matters, monitor competitors, draft stronger claims, and assess infringement risk. Founders Stephanie Curcio and James Stonehill built it in Toronto for the people who live in this work every day, from leading law firms to Fortune 500 legal teams to universities.

Why we backed it

Two forces are colliding: an explosion of AI-generated invention, and a patent system still running on keyword search. The companies that can move through intellectual property quickly will have a real edge, and NLPatent is building the tool that gives it to them. The round, which we co-led with Mighty Capital, funds expansion across North America and Europe and the move from assisting patent work to completing it.

“Our vision is an agentic platform that goes beyond supporting patent workflows to completing them.”
Stephanie Curcio, NLPatent

We back founders who pick hard, valuable problems that everyone else finds boring. The future of intellectual property is exactly that kind of problem, and we are glad to be early.

When GPS goes dark, most drones go blind. We led the extension of Vermeer's Series A, bringing it to $10 million, because Vermeer is teaching drones to see without it.

Vision where GPS fails

Vermeer builds a visual positioning system that lets a drone navigate using up to four electro-optical and infrared cameras matched against map data, running on Nvidia chips, with no satellite signal required. In modern conflict, where jamming and spoofing are constant, that capability is the difference between a mission that works and one that fails. Vermeer's technology is already combat-proven, deployed with the Armed Forces of Ukraine against active electronic warfare.

Why we backed it

Vermeer is an American-Ukrainian company founded by Brian Streem, built quite literally in a war zone. The team has grown from 10 to 40 people, eight of them in Ukraine, and has earned more than 30 partners including the U.S. Army, the U.S. Air Force, Lockheed Martin, and Northrop Grumman, on top of more than $7 million in non-dilutive SBIR and AFWERX funding before our round.

“One of the reasons we backed Vermeer is the incredible rate of success they've achieved specifically in helping Ukraine strengthen its drone fleet.”
Andy Tang, Draper Associates

Brian says it best: building advanced technology in a war zone is not easy, but it is the only way to make it real. The goal is not just to give drones mass, but precision, intelligence, and purpose. That is a bet we are proud to lead.

The single biggest thing standing between most people and self-custody of their Bitcoin is a string of words on a piece of paper. Lose the seed phrase, lose everything. We led Ryder's $3.2 million seed round to retire it for good.

Self-custody without the seed phrase

Ryder's hardware wallet sets up in under a minute and replaces the seed phrase with TapSafe, a recovery system based on coin-sized NFC tags. To restore access, the physical tags must be brought back together, so there is no single point of failure and nothing to memorize or hide in a drawer. It is self-custody designed for people who are not crypto experts, which is to say almost everyone.

Founded by Louise Ivan Payawal, Ryder raised from a strong group of backers, including angels such as Solana co-founder Anatoly Yakovenko.

Why we backed it

We have championed Bitcoin for over a decade, and the next billion users will not arrive through complexity. They will arrive through products that feel effortless and stay secure.

“What the crypto industry needs more than anything right now are solutions that don't require in-depth technical knowledge while maintaining high security standards.”
Tim Draper

Ryder is building exactly that, and we are proud to anchor the round that gets it into people's hands.

A resume tells you what someone has done. It tells you almost nothing about how they will actually perform. We led Mappa's $3.4 million seed round because the company closes that gap with something every candidate already has: their voice.

Hiring based on how people actually work

Mappa analyzes more than 30 vocal signals from a short conversation, drawing on over 100,000 data points in under a minute, to measure the things resumes miss: communication, ownership, empathy, and composure under pressure. For employers the payoff is concrete. Mappa reports more than $30,000 saved per hire and hundreds of hours saved per open role, and already serves more than 100 employers across the United States and Latin America.

The company was founded by Sarah Lucena, Pablo Bérgolo, and Daniel Moretti, with roots in Miami and Brazil. They bootstrapped Mappa to multimillion-dollar revenue before raising a dollar from us, and the seed round was oversubscribed.

Why we led the round

We love founders who prove the model before they ask for capital, and who build for markets others overlook. Latin American talent is some of the most underestimated in the world, and Mappa is building from there outward.

“Resumes tell you the highlights of what someone has done, Mappa AI shows you how they'll perform in the real world.”
Tim Draper

That is the kind of practical, global, founder-proven company we are proud to back early.

Bitcoin is the most secure, most valuable network in crypto, and for most of its life it has been the hardest to build on. We led Midl's $2.4 million seed round because the team is changing that without compromising what makes Bitcoin Bitcoin.

Smart contracts, native to Bitcoin

Most attempts to make Bitcoin programmable push activity off to sidechains, bridges, or separate layers, adding risk and friction at every hop. Midl takes a different path. Its execution environment lets developers build and run decentralized apps directly on Bitcoin, and even bundle multiple smart-contract interactions into a single Bitcoin transaction. No bridges. No detours.

Founded by Iva Wisher, Midl is already live on testnet with mainnet expected shortly, and more than 20 projects are lining up to deploy.

Why we backed it

Our thesis on Bitcoin has never wavered, and the next chapter is about turning the world's best store of value into a platform developers can actually build on. We led the round alongside Draper Dragon.

“It's rare to be this early to something this big. Midl makes Bitcoin programmable in a way that's never been done before.”
Iva Wisher

Being early to something big is the whole job. We are proud to lead the round backing Midl as it brings real software to Bitcoin.

What if the bottleneck on scientific progress is not ideas or funding, but the sheer number of hours a human scientist can spend at the bench? We led Potato's $4.5 million seed round because the company is removing that bottleneck.

AI scientists, not AI tools

Potato builds autonomous AI scientists: agents that read the literature, form hypotheses, design experiments, run them across code and chemistry, and hand back reproducible results. This is not a smarter search bar. It is a research collaborator that works around the clock. The early proof is where it already lives, in labs at MIT, Stanford, Harvard, Caltech, and Berkeley.

The company was founded by Nick Edwards and Ryan Kosai. We led the seed, joined by Dolby Family Ventures, Boost VC, and Ensemble VC, among others.

Why we led the round

We do not say this lightly, but we believe accelerating science itself is one of the largest opportunities in the world. Tim put it plainly when we announced the deal:

“We at Draper Associates believe that accelerating science, and unlocking runaway knowledge production, is a bigger unlock than the internet itself.”
Tim Draper

Every drug, material, and energy breakthrough downstream of faster science is a reason this matters. If software can compress the time between a question and an answer, the compounding effects are hard to overstate. That is a future worth funding first, and we are proud to lead it.

If Bitcoin is going to hold serious institutional money, it needs serious institutional plumbing. We backed Torram because that is exactly what the team is building.

Institutional rails for Bitcoin

Torram is building the infrastructure layer that financial institutions need to operate on Bitcoin: a decentralized oracle network, on-chain data indexing, a security framework, cross-chain tooling, and the ability to tokenize real-world assets. It is unglamorous, foundational work, the kind that has to exist before the more visible applications can.

Led by Vakeesan Mahalingam, Torram was one of just eight companies selected from more than 200 applicants for the inaugural cohort of our BitcoinFi Accelerator, the program we run with Thesis and Boost VC. It went on to close an oversubscribed pre-seed round, which we joined.

Why we backed it

We have backed Bitcoin since almost no institution would touch it. What has changed is the gravity around it.

“We believe in Bitcoin and there's now a gravitational pull towards Bitcoin.”
Tim Draper

Founder Vakeesan Mahalingam sees the same demand we do: serious capital wants infrastructure built to institutional standards. Torram is building it on the most proven chain in the world, and we are proud to have been there from the first cohort.

We have believed in Bitcoin longer, and more loudly, than almost anyone in venture. So when it became clear that Bitcoin was outgrowing its role as digital gold and turning into a platform to build on, we did not want to watch from the sidelines. We helped start the BitcoinFi Accelerator.

What it is

The BitcoinFi Accelerator is a six-week program we launched with Thesis and Boost VC to fund and mentor the founders building decentralized finance, social apps, and infrastructure directly on Bitcoin. Each team gets capital, mentorship, and access to our network, and the first cohort began in November 2024. The goal is simple: find the best builders in the ecosystem early, and back them the day they need it.

Why we are doing this

Boost VC, run by Adam Draper, launched the very first Bitcoin accelerator more than a decade ago. Thesis has spent years shipping real Bitcoin products. We have seen what happens when you back conviction founders before the rest of the market understands the opportunity. Some of our earliest bets, from Coinbase to Tesla to SpaceX, came from exactly that instinct.

“Bitcoin is entering its next chapter as a platform for real-world solutions. The potential of Bitcoin as both a global currency and a technology stack is enormous, and this program will help unlock it.”
Tim Draper

Companies from the first cohort, including Torram, are already building the rails for institutional finance on Bitcoin. This is how we fund the future first: not by waiting for the winners to appear, but by helping create them.

Bitcoin is a remarkable store of value and a clumsy way to buy a coffee. We led Ark Labs's $2.5 million pre-seed round because the team is fixing the second part without breaking the first.

Making Bitcoin spendable

Ark Labs is building on the Ark protocol, a design for moving Bitcoin quickly and cheaply enough to use in everyday commerce, including at the point of sale. Today a simple Bitcoin payment can be slow and expensive at exactly the moments it needs to be fast and cheap. Ark's approach is built to change that, with a payment experience that feels instant and settles on the most secure network in the world. If Bitcoin is going to be money, and not only digital gold, it has to move like money.

Co-founded by Marco Argentieri, Ark Labs raised alongside Fulgur Ventures and Axiom Capital, with angels including Stephen Cole.

Why we backed it

We have said for years that the world is moving toward a Bitcoin standard, where Bitcoin is not only held but spent. That future depends on infrastructure that makes everyday payments practical. Ark Labs is building that layer at the base, and we are proud to lead its first round and help bring spendable Bitcoin to people everywhere.

Bitcoin holders sit on the most valuable asset in crypto, and most of it just sits there. We led Zest Protocol's $3.5 million seed round to put it to work, safely.

A lending market built on Bitcoin

Zest is a lending protocol that lets people earn yield on their Bitcoin or borrow against it on-chain, built on Stacks and the native sBTC peg. It is the first money market for Stacks-based assets, which means Bitcoin can finally function the way other major crypto assets do in decentralized finance, without leaving the security of the Bitcoin economy behind.

Founded by Tycho Onnasch, the Zest team was incubated at Trust Machines and contributed to two of the most important upgrades in Bitcoin's recent history, the Stacks Nakamoto release and sBTC. We led the round, joined by Binance Labs, Flow Traders, and Asymmetric, among others.

Why we backed it

Our conviction in Bitcoin has never been about price. It has been about what gets built on top.

“Bitcoin L2s like Stacks are set to play a key role in unlocking Bitcoin DeFi.”
Tycho Onnasch

If Bitcoin is going to be the foundation of an open financial system, it needs lending, borrowing, and yield that anyone can access. Zest is building that foundation, and we are proud to lead it early.