Seed. Early. Growth. We invest across consumer and enterprise and have partnered with thousands of inspiring entrepreneurs over the past two decades.
Menlo Park, CA
Joined January 2010
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Redpoint retweeted
Thrilled to co-lead @fractile_ai's $720M Series C and get to work with @goodwin_ml and the incredible team.
Agents are running longer on bigger models and larger contexts. They’re bottlenecked by memory.
Fractile is the chip-first frontier AI company built to break that, stacking DRAM directly on logic for speed and scale. Over many whiteboards in Bristol, it became clear that Fractile’s full-stack approach is unlike anything else in silicon. You won’t find a more talented and fast-moving team. Couldn’t be more excited for everything ahead!
We’re delighted to announce that Fractile has raised $720M in a Series C led by @thrivecapital @foundersfund @lightspeedvp and @redpoint, with further participation by brilliant new and existing investors.
Redpoint retweeted
"Let them cure cancer" may be the new "let them eat cake": why Jev's creator, @CompleteSkeptic, thinks some AI valuations are miscalibrated:
Why hasn't AI automated more work? What's holding coding agents back? And are the labs' valuations built on the right expectations?
@CompleteSkeptic, co-founder and CEO of @typesafeai, was the perfect person to discuss this and more. Diogo coauthored OpenAI's InstructGPT paper, and a few weeks before we recorded, TypeSafe launched Jev, a "system one" model that returns structured decisions instead of text.
It was a ton of fun to discuss this with Diogo.
The conversation includes:
0:00 Intro
1:14 The Early Bet on RLCD
4:40 Built for Humans vs Computers
6:39 Roadmap & Model Limitations
11:04 Mental Models of Models
16:07 Do LLMs Have a Place in 10 Years?
17:32 New Model Shapes
21:24 Problems Still Unsolved
27:00 The Tyranny of the KV Cache
31:21 Rethinking Coding Agents
34:40 Multimodality
37:52 Images, Games & Computer Use
39:36 Could This Have Been Built 5 Years Ago?
42:01 Benchmarks & Copycat Releases
44:12 Fundraising
45:27 Quickfire
Listen here:
YouTube: youtu.be/ham8dROHCrc
Spotify: bit.ly/4kyeNBQ
Apple: bit.ly/3WppmgK
Redpoint retweeted
How does a corporate card startup become a $60B AI product factory?
In our first on-camera interview a decade in the making, Ramp co-CEO Eric Glyman (@eglyman) answers just that question.
Today, @tryramp is best known for its corporate cards, or maybe its marketing stunts with the likes of Kevin from ‘The Office,’ Tony Hawk and a 70-minute Broadway musical about paying bills.
But Eric says his $60B startup, NYC's most valuable, feels less like a fintech and more like a productivity company driven by one simple question: If a business spends $100 to make $200, how can Ramp improve that ratio?
Nearly 100,000 companies use Ramp today for everything from expenses to managing AI spend. But Eric says that when he zooms out to the millions who still aren't customers, Ramp feels painfully early still.
On The Upstarts Podcast, Eric shares why he’d rather run Ramp like Amazon than Google; why Ramp hires for proof of work, not credentials, from a 14-year-old intern to a 28-year-old CTO; and how being the first customer for Anthropic’s Claude Code and Cognition’s Devin led Ramp to build its own AI tools.
Plus: The real story of Paribus, his first startup with co-founder Karim Atiyeh (@karimatiyeh); what they learned at Capital One; and a warning for Instinct and Muse.
This season is presented by @Atlassian and @chargebee 🫡
CHAPTERS
00:00 Introduction
01:51 What Ramp Actually Does
03:27 From Gym Charges To 1% Of U.S. Corporate Payments
05:13 Glass, Inspect And Building AI Tools For Itself
07:45 An AI Sales Assistant Before ChatGPT
09:45 How Ramp Decides What Products To Ship
11:14 First Customer For Claude Code And Cognition’s Devin
13:09 Why Ramp Wanted To Build Like Amazon, Not Google
15:42 Hiring For Proof Of Work: The 14-Year-Old Intern
18:43 A .300 Batting Average And ‘Growth Without Fear’
21:17 What Ramp’s Founders Learned At Capital One
24:00 The $1,000 Flight Refund Behind Paribus
26:34 Bots, A Cease-And-Desist, And A Lesson For Instinct And Muse
32:00 Marketing 101: Bill Pay The Musical And Kevin In A Glass Cube
36:01 Business Books And Helping People Do Their Life’s Work
39:03 How A 28-Year-Old CTO Catalyzed A Co-CEO Change
43:55 ‘Still So Early’: How Ramp’s Founders Stay Hungry
55:26 John Wooden And Why Ramp Competes Against Itself
Thanks for watching!
Redpoint retweeted
Starting today, every engineer who joins Serval begins with a weeklong, $10,000 paid vacation. We’re building the next generational company. We need generational talent to see it through.
Our mission has always been to empower people across every team to turn their understanding of a problem into working, trustworthy automations. Making that function inside the largest enterprises takes world-class engineering.
That’s what you’d be joining us to do. There are foundational decisions still to make, and the engineers making them will shape the future of how big we can build this company.
We want you to arrive rested and ready to do the best work of your life. So your first week is a chance to get away.
And if a @getserval employee refers you, both you and that employee receive $30,000, on top of the vacation.
Come build with us: serval.com/careers
Redpoint retweeted
Why hasn't AI automated more work? What's holding coding agents back? And are the labs' valuations built on the right expectations?
@CompleteSkeptic, co-founder and CEO of @typesafeai, was the perfect person to discuss this and more. Diogo coauthored OpenAI's InstructGPT paper, and a few weeks before we recorded, TypeSafe launched Jev, a "system one" model that returns structured decisions instead of text.
It was a ton of fun to discuss this with Diogo.
The conversation includes:
0:00 Intro
1:14 The Early Bet on RLCD
4:40 Built for Humans vs Computers
6:39 Roadmap & Model Limitations
11:04 Mental Models of Models
16:07 Do LLMs Have a Place in 10 Years?
17:32 New Model Shapes
21:24 Problems Still Unsolved
27:00 The Tyranny of the KV Cache
31:21 Rethinking Coding Agents
34:40 Multimodality
37:52 Images, Games & Computer Use
39:36 Could This Have Been Built 5 Years Ago?
42:01 Benchmarks & Copycat Releases
44:12 Fundraising
45:27 Quickfire
Listen here:
YouTube: youtu.be/ham8dROHCrc
Spotify: bit.ly/4kyeNBQ
Apple: bit.ly/3WppmgK
Redpoint retweeted
Danila Shtan is the CTO of @nebiusai, the AI cloud racing AWS, Google and Microsoft.
Danila has been with the company since the beginning. On November 1, 2023, Nebius launched its first public cloud with about 1,600 H100s. That same day, Danila told the engineering team to throw the entire stack away and start from scratch.
Today, Nebius is a Nasdaq-listed AI cloud with a $17.4 billion deal with Microsoft, a Meta agreement worth up to $27 billion, and a $2 billion investment from NVIDIA.
Danila is betting Nebius can grow fast enough to fight the hyperscalers as equals before they turn their full attention to AI cloud. He thinks the market is barely scratching the surface.
0:00 Intro
1:25 What Differentiates AI Clouds
6:16 Nebius’ Origin Story
10:15 Bringing New Nvidia Chips Online
14:55 What Different Customers Want
19:58 Latency vs. Cost
21:53 Disaggregated Prefill & Decode
24:59 Inference’s Low-Hanging Fruit
28:31 What Nebius Should Productize
30:11 The Tavily Acquisition
31:56 How Data Centers Differ
34:29 Bottlenecks in the AI Buildout
37:03 How New Workloads Shape Clusters
39:17 Why Hyperscalers Didn’t Win This Market
43:39 The Future of Neoclouds
45:42 What Gets Absorbed by AI Hyperscalers
49:43 OpenAI x Baseten
52:07 Quickfire
Listen here:
YouTube: youtu.be/qJkcjURcAe8
Spotify: bit.ly/47OFCKJ
Apple: bit.ly/4f6hwPk
Redpoint retweeted
Great to be back on Unsupervised Learning with @jacobeffron and @patrickachase!
We talked about the day-to-day knife fighting of getting GPUs, why we contribute a lot to open source, and how our most experienced engineers are the biggest agent-maxxers.
Is the compute market still the Wild West? What will happen to GPU prices over the next few years? And how will the inference market evolve?
@bernhardsson, co-founder and CEO of @Redpoint portfolio company @modal, was the perfect person to discuss this and more. Modal has crossed a $1B revenue run rate and recently raised $750M at a $15.75B valuation.
A few takeaways from my conversation with Erik, alongside @patrickachase:
▪️ Why compute won’t become a commodity
GPU capacity varies in disk, networking, location, and especially reliability. That variation makes a true exchange hard to build, so much of the market still runs on late-night WhatsApp groups and hallway deals at events like GTC. Erik expects it to get somewhat more efficient over time, but to stay structurally messy.
▪️ NeoClouds, NeoLabs, and the cost of capital
Erik disagrees with the idea that NeoClouds are going to die, and he sees them as sound businesses built on leasing hard assets against locked-in contracts. Their real disadvantage is cost of capital, which is why the successful hyperscalers all sit inside cash-rich public companies. NeoLabs carry a different risk. GPU deals often require only about 30% upfront, so a lab that raises $1B can commit to far more compute than it can pay for today. If funding tightens, Erik expects some NeoLabs to resell capacity and start to look more like NeoClouds.
▪️ Where durable advantage lives in inference
Erik sees pure token serving as a race to the bottom, with routers already commoditizing the underlying providers. Better kernels and smarter KV caching still matter, but those techniques spread quickly. He believes the more durable edge comes from offering a cluster of adjacent building blocks.
▪️ Who is actually adopting coding agents
Erik expected junior engineers to adopt agents first, but he has seen the opposite. For senior engineers, agents are like having 10 interns. Give one a full POSIX test suite and it can write a new file system in three days. He also sees training data creating a new kind of incumbency in software, with developers defaulting to frameworks like React because agents already know them well.
▪️ Why GPU prices may go up
Erik changed his mind on this 48 hours before we recorded. After reading Anthropic’s S1, he concluded that the largest buyers of compute are financially strong enough to keep acquiring capacity, which points to higher prices over the next 12 months.
Full Unsupervised Learning Episode 👇
0:00 Intro
1:26 The Compute Market Today
5:16 Modal’s Path to LLM Inference
10:02 Building the Hard Infrastructure
12:32 Unsolved Problems in Inference
16:07 Chips & Model Sizes
21:21 What Wins in Inference
24:56 Prioritizing a Multi-Product Roadmap
30:20 Agents as Modal’s Users
33:19 The Next Big Bet After Sandboxes
38:58 Robotics & Multimodal Inference
41:04 Scaling From $2M to $1B
42:51 NeoClouds & NeoLabs
48:15 RL as a Service
51:40 Quickfire
YouTube: youtu.be/HJDekXH-h5c
Spotify: bit.ly/4dZ0O4e
Apple: bit.ly/4inZJnE
Redpoint retweeted
Is the compute market still the Wild West? What will happen to GPU prices over the next few years? And how will the inference market evolve?
@bernhardsson, co-founder and CEO of @Redpoint portfolio company @modal, was the perfect person to discuss this and more. Modal has crossed a $1B revenue run rate and recently raised $750M at a $15.75B valuation.
A few takeaways from my conversation with Erik, alongside @patrickachase:
▪️ Why compute won’t become a commodity
GPU capacity varies in disk, networking, location, and especially reliability. That variation makes a true exchange hard to build, so much of the market still runs on late-night WhatsApp groups and hallway deals at events like GTC. Erik expects it to get somewhat more efficient over time, but to stay structurally messy.
▪️ NeoClouds, NeoLabs, and the cost of capital
Erik disagrees with the idea that NeoClouds are going to die, and he sees them as sound businesses built on leasing hard assets against locked-in contracts. Their real disadvantage is cost of capital, which is why the successful hyperscalers all sit inside cash-rich public companies. NeoLabs carry a different risk. GPU deals often require only about 30% upfront, so a lab that raises $1B can commit to far more compute than it can pay for today. If funding tightens, Erik expects some NeoLabs to resell capacity and start to look more like NeoClouds.
▪️ Where durable advantage lives in inference
Erik sees pure token serving as a race to the bottom, with routers already commoditizing the underlying providers. Better kernels and smarter KV caching still matter, but those techniques spread quickly. He believes the more durable edge comes from offering a cluster of adjacent building blocks.
▪️ Who is actually adopting coding agents
Erik expected junior engineers to adopt agents first, but he has seen the opposite. For senior engineers, agents are like having 10 interns. Give one a full POSIX test suite and it can write a new file system in three days. He also sees training data creating a new kind of incumbency in software, with developers defaulting to frameworks like React because agents already know them well.
▪️ Why GPU prices may go up
Erik changed his mind on this 48 hours before we recorded. After reading Anthropic’s S1, he concluded that the largest buyers of compute are financially strong enough to keep acquiring capacity, which points to higher prices over the next 12 months.
Full Unsupervised Learning Episode 👇
0:00 Intro
1:26 The Compute Market Today
5:16 Modal’s Path to LLM Inference
10:02 Building the Hard Infrastructure
12:32 Unsolved Problems in Inference
16:07 Chips & Model Sizes
21:21 What Wins in Inference
24:56 Prioritizing a Multi-Product Roadmap
30:20 Agents as Modal’s Users
33:19 The Next Big Bet After Sandboxes
38:58 Robotics & Multimodal Inference
41:04 Scaling From $2M to $1B
42:51 NeoClouds & NeoLabs
48:15 RL as a Service
51:40 Quickfire
YouTube: youtu.be/HJDekXH-h5c
Spotify: bit.ly/4dZ0O4e
Apple: bit.ly/4inZJnE
Redpoint retweeted
Over the past 2.5 years, the Legora team has constantly redefined my bar for moving at AI speed and building exceptional AI products. Spend any time with them and their customers and it’s clear that Legora is a truly special company with an insanely exciting future ahead. A huge congrats to the team on this milestone!
We have raised a $550M Series E at an $8.8B valuation, led by Atreides.
Every major existing investor is back in, and we’re welcoming Baron Capital, Capital Group, Fidelity, Glade Brook and J.P. Morgan. We picked investors who think in decades. Several of them work with law firms and legal teams every day, so they can see where the work is heading.
Lawyers are moving from AI assistants to agents that do multi-step work. The money goes there. We’re growing our teams across North America, Europe, Latin America and Asia-Pacific, and going deeper on the Legora aOS.
Thank you to the 1,000+ people at Legora, and to the 140,000 legal professionals who use what we build.
I say this a lot because I believe it: it’s the best time in history to be a lawyer. We're thankful to be a part of it.
Full story: legora.com/blog/series-e
Redpoint retweeted
Meet Mistral Large 4, aka Le Chonk.
• 1T parameters, natively multimodal. 49B active.
It is the best open weights model from US or Europe on aggregated benchmarks.
• State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding.
• Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure.
• Available to all via API today. Working with cybersecurity partners privately.
Open weights release end of October.
🤖 Made with AI
Redpoint retweeted
When is harness optimization enough? When does post-training make sense? What will determine who becomes the new AI hyperscaler?
@ypatil125, co-founder of @appliedcompute, was the perfect person to discuss this and more.
Yash worked on Codex at OpenAI before leaving to co-found Applied Compute with fellow OpenAI researchers Rhythm Garg and Linden Li. Sixteen months in, the company is a unicorn, and is serving enterprises including DoorDash and Cognition.
We cover:
0:00 Intro
1:42 The Case for Owning Your Intelligence
4:35 OpenAI x Baseten and the Multi-Model Future
7:19 Can Post-Training Beat Frontier Models?
9:03 What Data Stays Out of Distribution
11:51 Data Efficiency and Continual Learning
14:31 When Updating Model Weights Makes Sense
16:01 Online Training in Practice
18:16 Lowering the Cost of Post-Training
19:48 Does Every Company Need Its Own Model?
24:06 RL in Non-Verifiable Domains
26:59 How Applied Compute Picks Customers
28:46 Building an Inference Business
34:43 The Case for a New AI Hyperscaler
38:21 Building RL Environments
41:33 Quickfire
YouTube: youtu.be/QeiYSLBCwD4
Spotify: bit.ly/4y6EJrz
Apple: bit.ly/4j1okRj
Redpoint retweeted
Three years ago, we started Restate because we felt that building reliable distributed applications was just too hard. We were solving the same problems around failures, recovery, and consistency again and again.
Today, I'm excited to share that we've raised a $20M Series A led by Singular with participation from Redpoint Ventures and Capital One Ventures.
The need for solutions like Durable Execution has only grown since we started. Today, the majority of new Restate use cases are AI agents: long-running processes, coordinating across many tools and APIs, that need to keep working correctly through all sorts of failures and interruptions, coordinate sub-agents, or schedule work.
At the same time, our customers have pushed Restate into places that expanded our own view of what Durable Execution could become. Replit moved the execution of Replit Agent onto Restate. DOSS runs high volumes of enterprise workflows on Restate and Fortune 500 institutions are using Restate for complex transactional workflows.
We think this is just the beginning and excited to build what we believe will be a fundamental pillar of all infrastructure in the future.
Read more here: restate.dev/blog/announcing-…
Redpoint retweeted
Simulation has the potential to be transformative, but only if it's accurate. Today, we're sharing results of a comprehensive evaluation across 2,993 questions, with an industry-leading mean TVD of 7.62% and an MAE of 3.53%.
More below, including the full post on our site.
Redpoint retweeted
Meet Ande.
Ande is the AI-native network for corporate entertainment, connecting the enterprises that book with the vendors that serve them.
$400M of dinners, suites, and gifting already runs through it, across 93,000 vendors in 90+ cities.
One network. Both sides win.
Redpoint retweeted
I first came to San Francisco when I was 15, with my dad. He is a programmer. To a teenager from a small island outside of Stockholm, this was the place where the future was being built.
We walked into Salesforce East and stood there watching the enormous digital display of moving water. Outside, Salesforce Tower was starting to rise.
I remember looking up and thinking it would be pretty sweet to have a tower someday. We are not there yet.
What I could not have known is that I would be back years later, having dinner with @Benioff and welcoming @salesforce as a @WeAreLegora customer.
Salesforce's Legal and Corporate Affairs organization will now use Legora across North America, EMEA and APAC. Their lawyers keep the judgment calls. We take care of the work around them. We have run on Slack since day one and became Salesforce customers when our sales team outgrew its first CRM, so it is good to have it run in the other direction too.
Welcome to Legora, Salesforce.
Dad, this one feels special.
Redpoint retweeted
We’re announcing that Forus has raised a $150M Series C at a $3B valuation to build the AI network for medicine.
Medicine will remain one of the world’s most important industries until humanity achieves immortality, and we are only at the beginning of a new era in what it can do. GLP-1s are changing obesity and cardiometabolic disease. Gene therapies can treat diseases at their genetic source. New cancer treatments are turning diagnoses that were once fatal into diseases people can live with. AI is enabling us to discover of new drugs even faster.
But discovery is only the beginning. It still takes more than a decade and billions of dollars to turn a new molecule into an approved medicine, and once it reaches market, more than a third of patients prescribed specialty treatments never receive their first dose.
Forus is creating the AI network to accelerate the entire medicine pipeline, from development and launch through prescription and treatment. We connect the companies creating medicines with the doctors who prescribe them and the patients who need them.
Today, Forus supports millions of people across all 50 states and is already used by providers to treat patients in 85% of U.S. residential ZIP codes. 9 of the top 15 global biopharma companies work with us, alongside many fast-growing biotechs. Our goal is to put Forus in every doctor’s office in the country and unlock an order of magnitude more medicine for society.
There is a generational opportunity to rethink how new medicine reaches people. Forus is becoming how medicine moves from discovery to treatment in America, and as we scale, we’ll become the most important company in life sciences.
Forus is not constrained by capital or customer demand; we are constrained by the talent and capacity of our team. To take on the opportunity in front of us, we need exceptional engineers and operators in New York who want to move fast and help us make something that matters. Come build with us.
Our Series C was led by Bain Capital Ventures, with Thrive Capital, General Catalyst, Accel, Redpoint, BoxGroup, Pear VC, Vast Ventures, and SV Angel investing alongside them.
Redpoint retweeted
Today we're announcing Coder Agent Relay: a new way to give Cursor Cloud Agents self-hosted execution environments on your infrastructure.
Launching with @spacexai for regulated enterprises where code can't leave the network.
🔗 cdr.co/agentrelayx
Redpoint retweeted
Just one day after setting up Revel, an intern at @OrbitalOps_ was already using it to independently run 40 hot-fires.
Orbital Operations is developing a high-delta-V, high-thrust rocket vehicle around a first-of-its-kind cryogenic propellant management system to unlock rapid mobility across LEO, GEO, and beyond.
Fresh out of @ycombinator Combinator W25, their small team—half of them interns—needed test software that could move as fast as they did.
Before Revel, Orbital Ops had never run a test. They had no data recording, no automated sequencing, and no software team to build either.
With Revel, they now:
• Run dozens of tests in a day
• Give interns ownership of entire engine subsystems
• Operate five-plus test cells daily, up from a single test cart
All without a single software hire.
Thanks to @BenSchleuniger, Ross Doherty, @nicosuave9, Dane Patten, @stefan_salaices, and the rest of the Orbital Ops team for the partnership.
Link to the full case study in the replies.