Kindred Ventures

Supporting world-changing startups and kindred spirits who create them. Started in 2014 by @stevejang, joined by @km in ‘18, and focused on the earliest stages.

[Kindred Ventures @KindredVentures]

News! We are proud to share our latest $355M set of funds, combining early stage and early growth.

[Kindred Ventures @KindredVentures]

@stevejang 👏👏👏

[steve jang @stevejang]

https://t.co/XjAdkIGxy9

[Kindred Ventures @KindredVentures]

Architect Labs is developing AI to accelerate the co-design of custom chips - democratizing the capabilities to innovate on the hardware level of the incredible intelligence era ahead of us.

So, we’re thrilled today to share that @KindredVentures led a $24M seed round for @architectlabs, joined by @TQVentures @RaceCapital @togetherfund, as well as a storied group of operators/researchers including @snsf, @lukaszkaiser, @AravSrinivas, @tlbtlbtlb, @alexwg, and et al from @NVIDIA, @GoogleDeepMind, @OpenAI, and @perplexity_ai.

For decades, the contract between hardware and progress was simple: transistors got smaller, everything got faster, and the industry planned around the rhythm. That rhythm has slowed because of Moore’s Law stalling, and the new performance gains are coming from somewhere else entirely, architectural decisions about how memory and compute are arranged, how silicon is shaped around the workloads it serves, and how hardware and software are designed to evolve together instead of drifting apart.

AI is no longer confined to the data center. It’s running in robots, at the edge, on satellites, in every device with ambition. Each of those environments has its own physics around power, latency, and cost, and none of them are well-served by the same general-purpose GPU. The frontier labs building tomorrow's models are still optimizing upward to fit chips they didn't design, instead of designing chips downward to fit the models they imagine.

The reason that hasn't changed is not just physics, it’s also inertia. Chip design cycles remain long, manual, capital-intensive, and gated by a small population of specialists. Custom silicon has remained an inheritance of a few incumbents rather than a tool available to the new guard who need it.

Architect Labs is rebuilding that process from first principles, an AI-native, self-improving system that co-designs silicon, compilers, runtimes, and system software as a single loop, so the cadence of chip development can finally start to look like the cadence of software. It's the unlock that lets the companies shaping intelligence actually own the hardware that runs it.

The founders, @axi_master and @aadityasubedi_ understand exactly how to diagnose this problem. They have little patience for the status quo. Ebrahim started college at 15, found his way onto Apple's silicon teams, and then onto Tesla's AI5 (the custom chip behind FSD and Optimus) where he watched a piece of silicon become outdated by the models it was meant to serve before it even shipped. Aaditya was researching AI for code verification at Harvard before he and Ebrahim met at Stanford and started working on AI for chip design together, a collaboration that later became the company. Alongside them now is a stellar team, researchers and systems engineers from @Anthropic, @Google, @intel, @Meta, @Samsung and @xai, with 80+ production tape-outs and core contributions at nearly every frontier lab between them.

To the Architect Labs team, we’re honored to join you on this incredible mission! 🚀🚀🚀

[ComputeSDK @computesdk]

🎉🎉🎉

Huge congrats to @northflank for successfully completing the 2026 100k Scale invitational!

See the full results below🧵

[Architect Labs @architectlabs]

Grateful to have @stevejang from @KindredVentures lead our seed. We are excited to build alongside investors who understand the full computing stack, believe deeply in the mission, and are able to look at long time horizons on where the industry is headed.

[Kindred Ventures @KindredVentures]

For more details, please read here:

https://t.co/lKoGVDkf1Z

[Kindred Ventures @KindredVentures]

Architect Labs is developing AI to accelerate the co-design of custom chips - democratizing the capabilities to innovate on the hardware level of the incredible intelligence era ahead of us.

So, we’re thrilled today to share that @KindredVentures led a $24M seed round for @architectlabs, joined by @TQVentures @RaceCapital @togetherfund, as well as a storied group of operators/researchers including @snsf, @lukaszkaiser, @AravSrinivas, @tlbtlbtlb, @alexwg, and et al from @NVIDIA, @GoogleDeepMind, @OpenAI, and @perplexity_ai.

For decades, the contract between hardware and progress was simple: transistors got smaller, everything got faster, and the industry planned around the rhythm. That rhythm has slowed because of Moore’s Law stalling, and the new performance gains are coming from somewhere else entirely, architectural decisions about how memory and compute are arranged, how silicon is shaped around the workloads it serves, and how hardware and software are designed to evolve together instead of drifting apart.

AI is no longer confined to the data center. It’s running in robots, at the edge, on satellites, in every device with ambition. Each of those environments has its own physics around power, latency, and cost, and none of them are well-served by the same general-purpose GPU. The frontier labs building tomorrow's models are still optimizing upward to fit chips they didn't design, instead of designing chips downward to fit the models they imagine.

The reason that hasn't changed is not just physics, it’s also inertia. Chip design cycles remain long, manual, capital-intensive, and gated by a small population of specialists. Custom silicon has remained an inheritance of a few incumbents rather than a tool available to the new guard who need it.

Architect Labs is rebuilding that process from first principles, an AI-native, self-improving system that co-designs silicon, compilers, runtimes, and system software as a single loop, so the cadence of chip development can finally start to look like the cadence of software. It's the unlock that lets the companies shaping intelligence actually own the hardware that runs it.

The founders, @axi_master and @aadityasubedi_ understand exactly how to diagnose this problem. They have little patience for the status quo. Ebrahim started college at 15, found his way onto Apple's silicon teams, and then onto Tesla's AI5 (the custom chip behind FSD and Optimus) where he watched a piece of silicon become outdated by the models it was meant to serve before it even shipped. Aaditya was researching AI for code verification at Harvard before he and Ebrahim met at Stanford and started working on AI for chip design together, a collaboration that later became the company. Alongside them now is a stellar team, researchers and systems engineers from @Anthropic, @Google, @intel, @Meta, @Samsung and @xai, with 80+ production tape-outs and core contributions at nearly every frontier lab between them.

To the Architect Labs team, we’re honored to join you on this incredible mission! 🚀🚀🚀

[Aaron Ginn @aginnt]

Today, @get_hydrahost announced a $100 million Series A led by @KindredVentures , with participation from @nvidia , @ARKInvest, @ComcastVentures, SPLY, Magnetar, @Denver_Ventures, Flume Ventures, @scottmcnealy, and @foundersfund .

It’s a major milestone for our company, but more importantly, it’s validation of a belief we’ve held since day one: the future of AI infrastructure will not be owned by a handful of companies. It will be distributed worldwide.

When we started Hydra, most people saw GPUs as hardware. We saw an asset with a global market.

Just as the internet needed cloud platforms, AI needs an operating layer that can coordinate compute resources wherever they exist.

That’s what we’ve spent the last several years building.

Today, Hydra powers AI infrastructure across more than 60 data centers in almost two dozen countries. Four of the five largest inference platforms run on our network. We’ve booked over $2 B+ in compute contracts and helped deploy some of the first sovereign AI infrastructure projects in the world.

What’s unique about Hydra is that we don’t own the GPUs. We don’t need to.

Our job is to make every GPU, every megawatt, and every AI factory more productive and easier to bring to customers. We built the de facto software and data center automation operating system that connects global supply with global demand, like SWIFT or Stripe.

The result is simple: data centers earn more, AI companies scale faster, and governments can build sovereign AI capability without relying exclusively on a handful of hyperscalers or expensive long-term contracts.

This funding isn’t about buying hardware but about accelerating the adoption of our data center OS for global AI infrastructure.

We’ll use these resources to expand our network, deepen our presence across key markets globally, launch new AI factories with our partners, and continue building the software layer that powers the next generation of compute.

The last decade was about centralizing compute; the next decade will be about distributing it.

AI is becoming a global utility. The winners won’t just build the models. They’ll build the infrastructure that makes intelligence available everywhere.

That’s the future we’re building toward at Hydra.

To our customers, partners, employees, and investors: thank you for believing in this vision before it was obvious.

HWPO

You can read more here: https://t.co/kWBceyO6a6

https://t.co/QefRgyjt5f

[Kindred Ventures @KindredVentures]

From @Perplexity’s computer-use agents to @Roblox’s huge engineering workflows, agents and agent harnesses have forever changed the way teams build products.

Tomorrow in SF we're hosting @randomjohnnyh, cofounder of @perplexity_ai, @andrewswerdlow, VP of engineering at @roblox, and our own @stevejang of @KindredVentures to go deep on this new era.

Apply to join us https://t.co/E3GSIrEasa

[steve jang @stevejang]

stealth hardware co, super interesting co, super fun early team roles.

[Kindred Ventures @KindredVentures]

@damienhe @fdotinc @HustleFundVC @BoostVC @outlandervc @actionscapital @rightsidecap 👋🏽👋🏽

[Kindred Ventures @KindredVentures]

We’re thrilled to share our seed investment in @fearn_ai - a research and agent lab developing an AI agent and harness which speeds up the creation, filing, and enforceability of patents at the highest of fidelities - alongside @speedrun @designerfund and @EssenceVenture.

The founders, @hanhanhan_kim and angela gao, are a duo of Caltech research scientist and ex-big law researcher, and have been in stealth until today but already working with many deep tech, biotech, and hardware systems. Read more about them 👇🏽

https://t.co/iJHsek2Zmc

[Kindred Ventures @KindredVentures]

@km @MarcoDeMeireles @stevejang x posts do no reflect the opinions of my employer, kanyi.

[Kindred Ventures @KindredVentures]

News! We are proud to share our latest $355M set of funds, combining early stage and early growth.

[Kindred Ventures @KindredVentures]

@MarcoDeMeireles @km @stevejang knicks in 5 👾

[Kindred Ventures @KindredVentures]

@iScienceLuvr @stevejang @km @SophontAI 🫶🏽

[Kindred Ventures @KindredVentures]

@DevaBuilds @stevejang it’s novel. new ideas, new discovery, new creation - extending human capabilities. not a re-sampling of past data.

[Kindred Ventures @KindredVentures]

@thattallguy @nico_laqua ☺️

[Kindred Ventures @KindredVentures]

@thogge @nico_laqua 🥶

[Kindred Ventures @KindredVentures]

@jcfiaschetti 🫡