Welcome back to Product Market Fit 🔥

Today I’m sharing a curated set of AI pitch decks from frontier labs like OpenAI and DeepMind to early-stage startups backed by top-tier investors.

Some of these companies are already category leaders. Others are just getting started.

But that’s exactly the point.

This is a rare chance to study how both giants and early teams think, position, and pitch when they’re trying to build something that doesn’t fully exist yet.

1. Why This Matters

Most people look at pitch decks to copy slides.

That’s not the value.

The real value is understanding:

• how great founders frame a problem before it becomes obvious

• how they simplify complex technology into a clear narrative

• how they justify why this moment matters now

And in AI, this matters even more.

Because many of the things that feel “normal” today were just bold claims inside these decks a few years ago.

2. What You Will Find Inside

+ other Pitch Decks from: Aisera, Arga Labs, Artificial Societies, Axle Health, Charta AI, Code Four, Epiminds, Feroot AI, Gojiberry AI, Gradient, Hedra AI, Lightsprint, MITO AI, Nas.com, Nexad AI, Octave, Omnia, Onti, Sazabi, Thomas, Trellis…

Inside this collection you’ll find:

• Frontier AI companies like OpenAI, DeepMind, Anthropic, Mistral AI, ElevenLabs and Synthesia shaping the direction of the AI industry across foundation models, voice, video and enterprise adoption

• Agent infrastructure and AI workflow layers such as Nozomio, Aisera, Artisan, Boardy, Arga Labs and Lightsprint, showing how AI systems are becoming more autonomous, contextual and embedded in day-to-day work

• Vertical AI applications across healthcare, security, public safety and enterprise operations, including Axle Health, Charta Health, Feroot, Code Four, Sazabi and Scribe

• Creative and media platforms like MITO, Hedra, FLORA AI and Synthesia, building new categories around AI-native content creation, design and video production

• GTM, marketing and AdTech platforms such as Octave, Letter AI, Nexad, Omnia and Epiminds, showing how AI is reshaping sales, brand visibility, advertising and distribution

• Early-stage AI startups from YC and emerging ecosystems, including Gojiberry, Artificial Societies, Trellis, Thomas and others, offering a view into where the next wave of AI-native companies may emerge.

3. Why These Decks Give You an Edge

1. You learn how top founders think (not just what they build) → You see how they go from insight → narrative → company.

2. You understand what great positioning actually looks like → Clear problem, sharp angle, strong “why now”.

3. You get a preview of where AI is going → Before it becomes consensus.

If you’re building in AI, these are worth studying.

This database is available exclusively to paid subscribers!

If you’re not subscribed yet, you can unlock this and our full library (200+ startup decks, 10,000+ investors, AI Agent playbooks and fresh high-signal content every week) by upgrading below:

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Here are some examples:

🤖 AI Agent Templates

↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks

↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library

↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools

↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

4. The 40+ AI Pitch Decks

👇 Get access here:

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Masayoshi Son stood before shareholders and made a strange admission: SoftBank’s most valuable asset is worth nothing.

Not literally. SoftBank’s net asset value is 74 trillion yen. Its market cap is roughly half of that. The pieces inside the company, mostly listed stakes with market prices attached to them, add up to far more than the stock market value of SoftBank itself.

Son’s point was simple: investors are counting the eggs, but not the goose.

The “eggs” are SoftBank’s holdings: ARM, OpenAI, T-Mobile, Alibaba in the past, and the rest of the portfolio. The “goose” is SoftBank itself: the capital allocator that turned 3 trillion yen of net asset value into 74 trillion yen over 16 years.

That was the argument at SoftBank Group’s 46th Annual General Meeting on June 24, 2026. Not just that AI is early. Not just that ARM is valuable. But that the market is still pricing SoftBank like a pile of assets, rather than a company that can keep producing new ones.

What follows comes from Son’s own words, with the numbers as he stated them.

In this newsletter youll learn:

1. Why SoftBank Trades at Half Its Asset Value

2. How Son Turned ¥3 Trillion Into ¥74 Trillion

3. Why ARM Alone Is Worth More Than SoftBank

4. SoftBank’s Bigger AI Bet: Chips, Data Centers, Energy and Robotics

5. Why Son Calls ‘AI Bubble’ an Insult

6. 6. The 68-Year-Old Who Won’t Retire

7. The 46 th Annual General Meeting of Shareholders Deck

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AI broke the cost of building software. What used to take a team and a sprint, one person now ships in an afternoon.

So everyone is doing it. PMs, designers, founders, all pushing changes that used to wait behind an engineering ticket.

That is the good news. Here is the problem.

When everyone can build, everyone builds their own slice. In parallel. With no one holding the whole picture. The coordination that used to live in managers and meetings does not disappear, it just loses its owner.

Execution has never been faster. Staying in sync has never been harder.

Lightsprint is the YC Spring 2026 startup built on exactly that gap. It lets non-engineers ship real features to a real codebase:

• describe what you want in plain English

• it reads the existing code and lays out the trade-offs and visual options, styled to your actual app

• it spins up a live preview

• it spins up a shared live preview the whole team can open and approve

• it ships a real pull request

The bet underneath it: when everyone becomes a builder, coordination has to move out of managers and meetings and into the software itself.

Inside you will find:

1. The Rise of the High-Impact IC and the Problem Nobody Names

2. Why Coding Agents, Jira and Figma Each Solve Only Half

3. How It Works: One Shared Plan, Parallel Agents, a Preview Everyone Can Approve

4. The Founders Behind It and Why It’s Them

5. The Bet: Software Development Becomes a Team Sport

6. Lightsprint (YC P26) Pitch Deck

Want more? Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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30% growth MoM and 2,000+ customers paying for it.

Everyone agrees cold outbound is dead: reply rates at 2 to 3%, inboxes buried under AI-written emails that all sound the same, deliverability collapsing under the volume. Gojiberry grew fastest into exactly that, because it sells the opposite of volume.

So what is it. You plug in your website and five minutes later (literally) the agent is running: it learns what you sell and who buys it, finds the few people already showing intent, reaches out across email and LinkedIn, handles the replies, and books the demo. And remembers what works.

Inside you will find:

1. Why B2B Outbound Quietly Stopped Working

2. The Market Racing to Replace the SDR and Where Gojiberry Fits

3. How It Works: Plug In Your Website, the Agent Does the Rest

4. Why Every New Customer Makes the Next One Convert Faster

5. $0 to $3.5M ARR and the Customers Who Prove It

6. The Founders Behind It and the Bet on Owning the Whole Pipeline

7. Gojiberry (YC P26) Pitch Deck

Want more? Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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The team is building a place for code and agents to fail before they fail in front of a customer.

An agent is only worth anything because of the software it can operate and that is exactly where it breaks. It calls Stripe wrong, it misfires a Slack message, etc. And the more capable these agents get, the more damage a single wrong call does.

So what does Arga Labs actually do. It spins up a real-world sandbox that mirrors your production every time you open a pull request, with digital twins of the external services your software touches and lets your code and your agents run real workflows against them until you have seen how they behave for real.

Inside you will find:

1. Why Every Technology Wave Builds a Reliability Market Next to It

2. The Reason You’re Still a 1x Tester With a 100x Engineer’s Tools

3. The Product: A Production Twin Agents Can Break Before They Break Yours

4. $0 to $40K MRR in 7 Weeks, and the Customers Who Put Their Own Money In

5. The Founders Behind

6. Arga Labs Pitch Deck

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Want more? Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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Not a founder who uses AI → An AI that is the founder, works for itself and was given one instruction: make money.

Its name is Thomas. Nobody handed him a roadmap, a market or a product. The agent goes onto the open internet, solves a problem somebody will pay for, collects the cash and uses what he learned to decide what to chase next.

The bet was simple. The models are largely ready, but the infrastructure around them is still catching up. Today’s systems can already perform useful work, yet most agents remain constrained by predefined workflows that require human approval at each step. Thomas took a different approach. Instead of building a specialized harness, he gave the model access to the same tools and interfaces a human would use (human harness), allowing it to learn from the results of its actions rather than prompts.

In his first two weeks running that loop on his own, with no human involved, Thomas made $17,000.

Inside you will find:

1. How the Agent Finds Its Own Way to Make Money

2. How an AI Made $17K Without a Human in the Loop

3. The Loop Where Every Dollar Rewrites the Next Move

4. How V2 Removed the Last Human From the Loop

5. Why the Long-Term Ceiling Is GDP Itself

6. The Real Thomas

7. Thomas YC Pitch Deck

Want more? Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates

↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks

↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library

↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools

↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

Get 7-Day Free Trial

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It did it in June. Peak season, World Cup on, property managers buried in turnovers and telling every vendor who calls to circle back in October, because nobody re-platforms the system during their highest-revenue weeks.

Trellis grew 15% week over week anyway, with 100% trial conversion, the fastest climb from zero in its entire YC batch.

So what is it. Trellis sells property managers an agent that runs their short-term rental operation end to end: messaging guests, dispatching cleaners and maintenance, handling the back office. It replaces the stack of five separate tools and it goes after a slice of the market no software has ever really owned.

Inside you will find:

1. Trellis YC P26 Pitch Deck

2. Why $42B of a $105B Market Has Never Had a Real Owner

3. The Traction That Isn’t Supposed to Happen in June

4. The Agent That Builds a Different Product for Every Operator

5. The People Building It, and Why It’s Them

6. The Bet on Owning the Stay, and the Math to $100M

Want more? Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

Get 7-Day Free Trial

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Some pitch decks raise money. This one built a $12B MONSTER 🔥

In 2019, Brex used this deck to raise $57M in Series B funding, and it became one of the most legendary fintech rounds of the decade.

The founders, Henrique Dubugras and Pedro Franceschi, had already built and sold a company as teenagers.

But Brex was different.

They were attacking one of the most broken parts of the startup ecosystem: corporate credit cards for fast-growing startups.

Instead of relying on personal guarantees and slow underwriting, Brex built a software-driven financial platform designed specifically for startups.

Investors immediately understood the scale.

This deck was backed by some of the most powerful names in Silicon Valley:

• Peter Thiel
• Max Levchin
• Yuri Milner
• Y Combinator

And the trajectory after that round was insane.

Brex scaled from a startup credit card into a full financial operating system for companies, expanding into spend management, banking, global payments, and treasury products.

Within a few years, the company had reached a valuation of $12B and became one of the fastest-growing fintech companies of the decade.

And it all started with this deck.

Just a brutally clear story about a massive problem, a product that solved it, and a market big enough to build a generational company.

This is one of the best fundraising decks you’ll ever see.

Because it shows exactly how to raise venture capital when everything matters:

• how to frame a massive opportunity

• how to explain a new fintech category

• how to make investors feel the inevitability of the company

  ---

  

  Apply to The Pitch by Deel now

  ---

In this breakdown we’re sharing:

1. The ORIGINAL 2019 Brex Series B deck used to raise $57M
2. A second version of the deck that has circulated online and been reconstructed from public sources

So you can see how one of the most iconic fintech companies in the last decade convinced investors to bet big.

Here you go 🔥

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Before reusable rockets.
Before Starlink.
Before SpaceX became the most important private company in aerospace.

There was just a pitch deck.

And one idea that sounded insane at the time:

Rockets shouldn’t be disposable.

For decades the space industry worked like this:

Build a rocket for hundreds of millions → launch it once → watch it burn in the ocean.

Every launch destroyed the vehicle.

Imagine throwing away a Boeing 747 after every flight.

That was the norm.

SpaceX’s thesis was simple and revolutionary:

1. Make rockets reusable.
2. Drop launch costs by 10x.
3. Unlock the entire space economy.

Today that idea powers:

• Starlink, the fastest-growing satellite internet network in history 🔥
• The majority of global satellite launches
• NASA missions and national security launches
• The foundation of the new commercial space industry

And the market is starting to price it in.

Private investors already value SpaceX at $1.5T+, making it one of the most valuable private companies on Earth.

But the bigger story is what happens if SpaceX ever goes public.

Several analysts believe that if SpaceX ever goes public, it could become one of the most important IPOs of the decade, driven by:

• Starlink becoming a global telecom giant
• Dominance in launch infrastructure
• Future space logistics and transportation

In other words:

SpaceX isn’t just a rocket company.
It’s becoming the infrastructure layer of space.

Apply to The Pitch by Deel now

The Legendary SpaceX Pitch Deck 🚀

Before all of this…

Before the rockets landing themselves…

Before the $350B valuation…

There was a pitch deck that explained why the economics of space were about to change forever.

Below is the original SpaceX deck that helped start the private space race.

🔥 Access the SpaceX Pitch Deck Below

Get access to the original SpaceX deck plus the pitch decks from some of the most iconic companies ever built:

• OpenAI
• Anthropic
• Figma
• Revolut
• ElevenLabs
• And many more

👇 Unlock the full archive below.

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🚨 Letter AI just closed one of the cleanest, strongest Series B rounds of 2026.

$40M Series B… four months after its last raise.

What is Letter AI?

Letter AI is building the AI-native operating system for revenue teams.

And this feels generational 🔥

They’re collapsing the entire bloated GTM stack into one unified system that does content, training, coaching, deal rooms, revenue intelligence, and real-time guidance: all inside the workflow, all powered by AI.

No more digging through Notion.
No more outdated decks and fragmented CRMs.

Letter is becoming the command center that tells reps what to send, how to respond, what to say, and how to close in real time.

This isn’t “AI for sales.” This is AI replacing the stack.

And when a 25-person team is already winning global enterprises and raising $40M led by Battery Ventures just months after their last round…

That’s not a feature company. That’s infrastructure in the making 🚀

📢 CALLING ALL FOUNDERS 📢

Deel is launching The Pitch: a global startup pitch competition, presented by J.P. Morgan.

Up for grabs…

• 💰 Up to 100 regional winners receive $50,000 in investment

• 🌍 Up to 10 global champions win $1M in investment

• 🤝 Plus access to exclusive startup perks and a global founder community

If you’re building something bold, this is your moment.

Apply Now 👇

Why did Battery Ventures go so all into Letter?

Because this isn’t incremental software, it’s a full-stack replacement of a broken category:

Old enablement made teams manage PDFs. Letter rebuilt it AI-first and became the single source of GTM truth.

When customers rip out multiple tools for one platform (and reps say they’d riot if it disappeared) that’s infrastructure.

Where Letter Is Now:

• 25 employees

• Customers in 30+ countries.

• Global brands like Adobe, Lenovo, Novo Nordisk, and Plaid.

• $40M Series B led by Battery Ventures (4 months after Series A).

Small team. Enterprise logos. Fast follow-on capital.

Anyways, so what did I do?

I went straight to Ali Akhtar and convinced him to share their Series B deck, solely so I could break it down and share it with you guys.

And I’m not exaggerating: this is one of the tightest, hardest Series B decks I’ve seen at this stage. Especially in GTM.

It’s sharp. Ruthless. Every slide moves the narrative forward.

In essence: they’re cracked.

If you’re raising right now, you should be studying this.
This is how you pitch infrastructure, not a feature.

Below is the full, unfiltered Letter AI Series B deck 🔥EXCLUSIVE: The $40M Letter AI 8-Slide Pitch Deck 🔥

🔥 Access now

Access Letter AI’s Pitch Deck now with the free trial (no strings attached), or jump straight into premium if you’re ready for the full scoop of resources of PMF (stay up to date with the most successful startups’ pitch decks, growth resources and more)👇

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Perplexity isn’t “another chatbot.”

It’s one of the few AI startups with a credible shot at owning the default interface for search: ask a question, get a synthesized answer, and see the sources.

And the market has been funding that thesis aggressively.

• In 2023, Perplexity raised a $25.6M Series A led by NEA, with participation from Databricks Ventures and a stacked group of top-tier angels.

• In January 2024, it raised $73.6M led by IVP, with participation from Nvidia and Jeff Bezos.

• By mid-2024, it raised roughly $250M at a ~$3B valuation, including SoftBank Vision Fund 2.

• In December 2024, it reportedly closed a $500M round valuing the company at around $9B.

• As of 2025, total capital raised has been reported at roughly $1.5B.

• Recent fundraising discussions in 2025 suggested the company was at just under $100M ARR.

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Trending right now: The 10 Excel Templates Every SaaS & AI Founder Needs to Build, Survive, and Scale 🔥, The Family Office List of Lists💰 (2026), 🚨 The Ultimate AI Fundraising Copilot (Built With Claude)

This isn’t just hype. It’s one of the fastest-scaling consumer AI products in the world, going directly after Google’s core behavior: search.

This issue opens up the hood of Perplexity’s December 2023 pitch deck.

I compiled the deck and included:

1. How Perplexity got valued this high (the real investor logic

2. The fundraising strategy that unlocked tier-1 VCs (and the playbook behind it)

3. The early deck + the key slides worth stealing

Check out the Perplexity deck with the free trial (no strings attached), or jump straight into premium!

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🖼️ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors in 2025

🔥 How to Get Into YC: The Spring 26’ FULL GUIDE

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Throxy raised $6.2M, led by Base10 Partners with participation from Y Combinator and a stacked group of operators, investors and angels (including myself!) who understand sales infrastructure at scale.

This is the deck they used. And it’s exactly how early-stage decks should look.

This isn’t another “AI SDR” company.

Throxy is building a fully-managed outbound system for B2B companies selling into manufacturing, logistics, and supply chain.

No SaaS, no internal SDRs.

They combine AI agents for prospecting and research with human operators for messaging and optimization, and deliver meetings directly into customers’ calendars.

And it’s already working:

• $🤫million ARR

• $60K ACV

• 2-month CAC payback

• 16-day sales cycle

• Profitable

• Six-figure pipelines generated for 40+ companies in legacy sectors

Outbound has been broken for decades:
Buy data → blast emails → burn the market → repeat.

Throxy flipped the model.

They don’t sell software. They sell pipeline.

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📚 Table of Contents

• Slide 1: Throxy

• Slide 2: Founding Team

• Slide 3: Problem - The $770B Labor Inefficiency

• Slide 4: Why AI SDRs Fail

• Slide 5: Focus - The Vertical Wedge Strategy

• Slide 6: Market - Replacing Headcount, Not Adding SaaS

• Slide 7: Traction & Unit Economics

• Slide 8: Vision

Below is the full slide-by-slide breakdown of how this deck sells a new category in outbound and why it resonated (and why I backed them after seeing their deck).

Access the full breakdown below 👇

EXCLUSIVE: Throxy’s 8-Slide Pitch Deck Breakdown 🔥

Slide 1/8: Throxy - ‘Sales need outcomes, not software’

Simple & direct. Instantly clear.

This opening line reframes the entire category in one sentence.

They’re not selling an AI tool. They’re selling revenue outcomes.

That distinction matters. Most AI SDR startups compete on features. Throxy competes on results. When you shift from “software buyer” to “revenue owner,” pricing power and urgency increase immediately.

Steal this: If your market is crowded, redefine what you’re selling in one sentence.

Slide 2/8: Founding Team

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At just 17 years old, Arlan Rakhmetzhanov dropped out of high school, got into Y Combinator, built Nozomio and raised a $6.2M seed round from some of the best investors in the world:

From CRV, BoxGroup, and LocalGlobe, with participation from Y Combinator and 20VC Product, plus an absurd operator + angel lineup: Paul Graham (YC), Gustav Söderström (Spotify CTO), Thomas Wolf (Hugging Face), Tomer Cohen (LinkedIn CPO), Jack Brody (Suno CPO), Geoff Charles (Ramp CPO) and operators from OpenAI, Google DeepMind, Databricks, Airbnb, and Microsoft (and yes, me too).

LocalGlobe is one of the most efficient seed investors in the world at producing unicorns: they’ve consistently ranked at the very top of “unicorn backer / unicorn hunter” lists (Dealroom rankings), basically making a business out of spotting $1B outcomes before they look obvious.

And the most important part:

The deck shows real ARR growth — the kind that turns “interesting idea” into “we’re already winning.”

So how did a 17-year-old make that round happen?

That’s the core of the story:

• $6.2M raised

• from investors who rarely miss at seed (LocalGlobe + top-tier syndicate)

• with ARR growth already moving in the right direction (in the deck)

So how did a 17-year-old convince that group (including me) to write the check?

He did it with a cracked 9-slide deck: one deeply correct insight about where agents actually break, plus enough traction to make it undeniable.

Below is the slide-by-slide breakdown and you can access the full Nozomio deck now via the free trial.

🔥 Access now

Access Nozomio’s Pitch Deck now with the free trial (no strings attached), or jump straight into premium if you’re ready for the full scoop of resources of PMF (stay up to date with the most successful startups’ pitch decks, growth resources and more)👇

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EXCLUSIVE: NOZOMIO 9 Slide Pitch Deck Breakdown 🔥

Slide 1: Nozomio

Slide 2: Team - Arlan

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FLORA just closed a massive $42M Series A, led by Redpoint Ventures and with participation from Guillermo Rauch (Vercel), Emery Wells (Frame.io), and the founders of fal.

This brings total capital raised to $52M, alongside existing investors including Mike Volpi at Hanabi Capital, Amy Wu Martin at Menlo Ventures, a16z speedrun, Long Journey, Company Ventures, Alumni Ventures, Justin Kan (founder of Twitch), Cyan Banister, Matthew Hartman at Factorial Capital, Gabe Whaley (founder of MSCHF), and more.

What attracted all these investors to FLORA?

Something simple: FLORA is trying to kill model-hopping forever.

And their pitch deck is a blueprint for how to sell a new category.

Because it doesn’t pitch “AI that makes art.”

It pitches workflow control at scale:

• persistent brand assets

• repeatable style across thousands of outputs

• collaboration in real time

• and a pricing model designed to spread inside teams

I met Weber Wong last year in a16z Speedrun and he was kind of sharing his deck with Product Market Fit. So I’ll let you be the judge of it!

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I invested in MITO AI.

This week, they announced a $4.5M pre-seed led by Lightspeed (early investor in companies like Snap Inc., Affirm, and Stripe), with participation from Kibo, Kfund, Sequoia and a16z scouts, LifeX, and a group of operators you want on the cap table (unicorn founders, USV, Roblox, GitHub execs).

On paper, it’s “another AI video startup.”

In reality, the pitch deck tells a much more interesting story.

This isn’t about generating clips faster.
It’s about owning the creative workflow layer of the next Hollywood.

The macro MITO is betting on (and why it’s right)

Video is becoming the dominant interface of the internet.

But the way we make video is still broken:

• Fragmented tools
• Linear workflows in a non-linear world
• AI bolted on as features, not as the system
• Collaboration that feels like emailing ZIP files in 2026

MITO’s core insight is simple but powerful:

AI won’t replace creators.
It will replace the friction between them.

And that’s exactly what the deck is built around.

The shift you are missing

AI video quality is no longer the constraint.

Runway, Veo, Kling, and others have crossed a real threshold. The models work. The outputs are good enough (sometimes shockingly so).

What’s broken is everything around them. Professional video creation today is:

• Across dozens of tools

• Slow to iterate

• Extremely hard to collaborate on

• Almost impossible to manage at scale

MITO starts from a different premise:

If video is becoming software, then video creation needs a real operating system.

Not another generator. Not another plugin. All-round infrastructure.

What MITO is actually building

This deck does a great job avoiding hype language and focusing on structure.

MITO AI is not positioning itself as a “better AI video generator.”

It’s building a browser-based, multiplayer, infinite canvas where the entire AI video workflow lives end-to-end.

Think less “Runway competitor”. More Figma × Notion × AI video orchestration

MITO treats video creation as a coordinated system, not a sequence of isolated tools. Inside one environment, teams can:

• Moodboard & set visual references
• Break ideas into storyboards and shots
• Script & plan production
• Experiment with image, video, and audio models
• Collaborate and iterate in real time
• Produce multi-format outputs
• Keep creative control and consistency

All while directing an AI copilot that executes specific actions, not vague prompts.

How this actually works in practice (short walkthrough of MITO)

This is where I stop feeling like this is a cool demo and start feeling that this is genuinely wild.

Everything just… stays together. Ideas, shots, assets, iterations, theyre all in one place, with the team, in real time.

Could be just me, but after watching this it’s hard not to think:
”oh sh*t, this is how video is going to be made.”

The Insane Deck MITO Used to Raise $4.5M 🔥

MITO just raised a $4.5M pre-seed led by Lightspeed, four months after founding.

If you’re building in AI, creative tools, or infra, this is as good as it gets, and its definitely worth reading closely.

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This one tried to convince you the company deserved to exist.

And in hindsight, it’s one of the cleanest examples of “positioning as strategy” in modern tech.

If you’re building in AI (or investing in it), this deck is a masterclass in how to:

• win trust before you win distribution

• turn “safety” into a product moat

• raise institutional capital for a research-heavy business

• sell inevitability without hype

Why this deck matters now (the $350B hindsight layer)

In January 2026, reports emerged that Anthropic doubled its fundraising target from $10B to $20B, with an implied valuation of ~$350B.

That number sounds absurd until you reread the deck.

Then it starts to feel… consistent.

This isn’t a company that “accidentally” became valuable.

This is a company that designed itself early to absorb massive institutional capital.

The deck explains why the market is even willing to write checks of this size.(Deck referenced throughout: Feb 2023 Anthropic pitch deck.)

Slide-by-slide: what Anthropic is really selling

Slide 1: “Anthropic, PBC” and named leadership

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The Big 5 of AI & their $70B+ Funding Pitch Decks

If you want to understand where AI is actually going, don’t start with benchmarks or launch blogs. Start with how the builders explain their own work, in their own words and how they raised BILLIONS of $$$.

Get full access to the Original Pitch Decks from:

• OpenAI

• DeepMind

• Anthropic

• Perplexity

• Mistral

Together, these companies have raised ~$70B+ in capital and represent five fundamentally different bets on how AI should be built.

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What you’ll get in this issue 🔒

• Full access to the original Pitch Decks from OpenAI, DeepMind, Anthropic, Perplexity and Mistral.

• A clear breakdown of what each deck is actually arguing, and why it mattered at the time

• A side-by-side comparison of the competing AI worldviews (scale, science, safety, product, infrastructure)

• A deep dive on the contrarian view of Yann LeCun and why he believes all of these approaches may hit a wall

Everything included with a subscription

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🖼️ +50 Pitch Decks of World’s Most Sucessful Startups

🖼️ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors in 2025

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OpenAI was built with a clear purpose: “Build safe AGI”.

Since 2017, the company has experienced growth like nothing before, changing the world and with one breakthrough after another one.

Revenue followed the same curve growing 3X year over year, or 10X from 2023 to 2025: $2B ARR in 2023, $6B in 2024, and $20B+ in 2025.

This is never-before-seen growth at such scale.

In today’s newsletter, we curated something indedited:

From 2017 to 2020, the decks internal decks of OpenAI

• 2017
  AI is fragile and dangerous by default. Alignment is the bottleneck.

• Early 2018
  Reinforcement learning and scale start to work in complex environments.

• September 2018
  OpenAI locks its mission: build safe AGI and distribute the benefits.

• 2019
  Systems outperform humans in games and simulated worlds.

• 2020
  Large generative models + large-scale RL unlock general capability.

These decks show:

• How AI thinking shifted from narrow tasks to general systems

• Why scale became inevitable, not optional

• When language models stopped being experiments and became foundations

• Why safety, alignment, and deployment were treated as first-order problems

• How OpenAI’s scope expanded from a small research lab to a platform shaping an entire industry

This growth wasn’t accidental. It tracks almost perfectly with the ideas in the decks: the shift to scale, the focus on general systems, the bet on language models, and the long-term AGI mission locked in years earlier.

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Here you go, enjoy 🔥

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Today we’re going back to 2015.

Before Revolut was Europe’s most valuable fintech.
Before $75B secondaries.
Before 40M users, $500M+ in profits, and billions sitting on the balance sheet.

Back when it was 4,800 users, a handful of slides, and a £1.5M seed round.

This is a teardown of Revolut’s original seed pitch deck, the one that convinced Balderton Capital and Seedcamp to back two founders solving what looked like a very “small” problem: hidden FX fees.

Read the investor’s perspective at:

👉 The Revolut Investors Who Won Big: Balderton’s Billions, Crowdcube’s Millionaires, and the Secret Angel List

And why this deck matters more than almost any other in European startup history.

Revolut at Seed Stage: Context That Changes Everything

Let’s anchor the moment.

• Year: 2015

• Product: FX-friendly prepaid card for travelers

• Users: ~4,800

• Revenue: basically nothing

• Founder capital: £300k of Nik Storonsky’s own savings

• Round: £1.5M seed

• Valuation: ~£8M

Investors:

• Balderton Capital (lead)

• Seedcamp

• Giano Capital

• AMK Investment Office

What’s wild is not just how early this was.
It’s how un-flashy the deck actually is.

No grand AI narrative.
No “super app of finance” vision yet.
No massive TAM gymnastics.

Just a brutally clear wedge.

What the Revolut Seed Deck Actually Did (And Didn’t Do)

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Last month, Yann LeCun publicly announced he’s leaving Meta to launch a new AI startup focused on world models.

According to reporting by the Financial Times and Sifted, the company (AMI Labs) is in talks to raise €500M at around a €3B valuation, with a global research footprint and a clear mission: build AI systems that understand the physical world, not just language.

That part is public.

What’s less public is how LeCun and his team are thinking about why the current AI paradigm won’t get us there — and what they believe replaces it.

The fundraising deck for this round has been circulating privately. It’s clearly confidential, so I won’t publish it or quote from it directly.

But I’ve reviewed how the thesis is framed, and it’s one of the clearest explanations I’ve seen of how top AI researchers see the next phase of AI unfolding.

Here’s what you need to know.

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