Hickory Falls Ventures
Investment Thesis
Big problems. Bold bets. Brilliant outcomes.
Core thesis
Intelligence is crossing from the digital world into the physical one — and the deployment gap is where durable value gets built.
The dominant wave of AI value creation has been digital-native: language models, code generation, software productivity. The next durable wave will not come from purely digital products, but from embedding intelligence into high-friction, real-world systems — manufacturing, supply chains, logistics, defense, space, and physical performance — where barriers to adoption remain high and returns to successful deployment compound over time.
Most attention in AI is focused on models — larger, faster, better benchmarks. In the physical world, that's not where the constraint is. The real problem is translating AI capability into action inside messy, real-world systems. That means translating AI outputs into workflows that humans actually use. Translating unstructured, inconsistent data into something models can learn from. Translating between legacy systems, supplier relationships, and decision-makers who've been doing things a certain way for twenty years.
Deployment in the physical world means changing how a factory schedules production, altering how a buyer selects suppliers, introducing new tools into long-standing human relationships. These are not just technical problems — they are behavioral and organizational ones. The last mile of AI is where the hardest challenges emerge. It is also where the most defensible companies get built. HFV invests at this gap — because wherever the crossing is hardest, the position is most defensible.
Three thesis pillars
01
Deployment over invention
The frontier has been established. The opportunity is in applying AI to the physical world — not building foundation models. The US leads in invention; the alpha is in deployment.
02
Physical world, broadly defined
Manufacturing informs our insight but does not limit our thesis. Any domain where intelligence meets physical constraint — robotics, logistics, defense, space, sports, human sensing — is in scope.
03
Compounding data flywheels
Physical AI deployments generate structured, causal, real-world data as a byproduct of operation — improving underlying models and widening the moat over time. This is the mechanism behind durable value.
Our edge
Operator insight
We run businesses inside the physical world
HFV's managing partners operate businesses inside global manufacturing and supply chains — AAA World-Wide across Taiwan and China. We evaluate physical AI investments with ground truth most investors can only approximate: where AI actually deploys, where it stalls, and what operators need to say yes.
Asian deployment advantage
The physical world economy is largely built here
A disproportionate share of global manufacturing, assembly, and supply chain operation is based in Asia. Our presence inside that ecosystem — as operators, investors, and advisors at SparkLabs Taiwan — gives us earlier deal access and direct visibility into how quickly physical AI reaches production scale, because the factories adopting it are our neighbors and peers.
Infrastructure lens
We evaluate the stack beneath every application-layer bet
Our primary edge lives at the application layer — but we use the physical AI infrastructure stack as a rigorous evaluation lens, asking whether each company has credible access to the primitives it needs to scale. We won't pass on a compelling infrastructure opportunity when access emerges.
Active diligence — SparkLabs Taiwan
Evaluated, not yet invested
Manufacturing robotics & AI operational intelligence
Through our Venture Partner role at SparkLabs Taiwan, HFV actively evaluates seed-stage companies at the frontier of manufacturing robotics and physical AI — sharpening our investment criteria in the categories we expect to be most active in over the next 18–24 months.
The last mile is the hardest one
In software, deploying a new product can be as simple as pushing an update. In the physical world, deployment means changing how a factory schedules production, altering how a buyer selects suppliers, introducing new decision-making tools into long-standing human relationships. These are not just technical problems — they are behavioral, organizational, and trust problems.
What we see from inside our own manufacturing operations isn't AI replacing people — it's reshaping what people do. Buyers become decision-makers supported by intelligence. Operators become supervisors of more adaptive systems. Engineers become integrators of tools, data, and process. The value shifts from execution to coordination, judgment, and speed of decision-making. That transition is slower than in software. It is also far more defensible.
Why now
AI has reached a level of usability where non-technical operators can actually interact with it — not just engineers, but buyers, plant managers, and logistics coordinators. Global supply chains are under sustained pressure, forcing companies to rethink efficiency in ways they've avoided for decades. Labor constraints are pushing organizations to do more with fewer people. And data is finally becoming accessible, even in traditionally analog industries.
These forces are converging — pushing AI out of the digital world and into the real one, one workflow at a time. Many attempts will fail, not because the technology doesn't work, but because it doesn't fit the environment. The companies that get it right will become deeply embedded in how the physical world operates. That embeddedness is the moat.
Portfolio — thesis already expressed
These are not disconnected bets. They are different expressions of the same conviction: intelligence crossing into the physical world, at the deployment layer, across domains where integration is hard and moat is real.
Space & defense infrastructure
Starlab — ISS replacement
Karman+ — asteroid mining
Skydio — autonomous drones
Epirus — directed energy defense
Ursa Major — rocket propulsion
Firehawk — propulsion systems
SpaceX
Voyager Technologies IPO
Physical supply chain & logistics intelligence
Hyperscience — intelligent document & data extraction
Workrise — skilled labor for industrial sectors
Glober AI — AI-native localization for global expansion
Physical performance & human sensing
Paris Musketeers — European League Football
Red Bull Italy SailGP
Levels — metabolic & biometric sensing
Sandbox VR — physical-spatial immersive experience
Limitless — AI wearable & ambient memory acquired
Foundational AI — portfolio enablers
Not core thesis, but foundational to AI at large — and to every company we back.
OpenAI
Databricks
Chalk.AI
Perplexity
You.com
What we avoid
Generic AI SaaS and LLM wrappers with no physical world connection. Horizontal productivity tools competing on features rather than deployment depth. Applications with no data flywheel — where the AI doesn't improve as a result of operating in the world.
Investment philosophy
HFV deploys capital directly and through syndicates, SPVs, and affiliate networks including First Round Angel Track, Gaingels, SparkLabs Taiwan, and Hyphen Capital — with a long time horizon and a preference for early positions in domains before they are obvious.