Before diving into the framework it’s useful to briefly articulate why we find DePIN so exciting.
DePIN, the crypto industry vernacular for Decentralized Physical Infrastructure, is an emergent category of networks that promiseS to replatform centralized infrastructure services like Telecom, Wireless and Energy.
DePIN networks employ a highly disruptive business model which simultaneously aims to lower cost and provide superior performance compared to the oligopolies and monopolies which operate these vital services today.
How? The main accelerant is superior risk-capital formation. Any individual or business can acquire and operate nodes with their entrepreneurial risk capital instead of requiring centralized companies to raise large amounts of capital and operate large networks globally.
It’s valuable to note that utilizing new capital formation approaches to disrupt industries isn’t new; a similar disruption trend occurred in the Restaurant industry via the Franchise model.
Owning and scaling restaurants used to be hard. For example, growing from 1 store to 10 required the restaurant owner to raise substantial capital, acquire real estate, obtain local permits, hire staff locally and operate all the locations. The franchise model helped accelerate scaling by enabling entrepreneurs with risk capital and local expertise to make many of these capital and operational decisions under the umbrella of a well known brand. The franchisee purchased a standard set of brand assets & equipment to operate the restaurant and in-return sent a portion of proceeds to the company.
Similarly, DePIN operators (in many cases) purchase and operate nodes and provide services and receive tokens, with a portion being returned to the DePIN network foundation. Even moving beyond the franchise model, participation in these networks requires substantially less capital expenditure (e.g. $100) and is permissionless, ungated by any centralized decision maker.
In sum, DePINs enable infrastructure networks to scale much more efficiently than existing networks. For example, the mapping platform Natix mapped over 1 million kilometers in 11 weeks, orders of magnitude faster than Google.
Evaluating DePINs
Hundreds of DePINs seek funding every year. These are the considerations I use for evaluating them.
The strongest DePIN projects include most or all of the below design considerations:
- Granular geographic importance
The more granular the network deployment, the harder to replicate - Supply Side overlaps with the Demand Side
When Supply Side uses the infrastructure they require less token incentives to operate nodes, preserving incentives for other uses beyond supply-side bootstrapping - Compete on Performance, not Cost
Networks that drive outsized performance not physically possible in centralized form can expect greater premiums over time - Demand scales nonlinearly with Supply
Networks where a single node can scale to many customers can achieve superior profitability compared to networks where incremental demand must precipitate incremental supply
I. Granular Geographic Performance
Networks that require node deployment with high degrees of fidelity to operate engender a larger moat and network effect. The reason for this is clear; incentivizing a network that requires granularity to the scale of meters is much more challenging to create and operate than in a centralized or pseudo-centralized manner.
For example, Compute networks like Render or storage networks like Filecoin tend to gravitate towards the “least granular” end of the spectrum. For many of them, they have the flexibility to build capacity in a range 10s or 100s of miles with marginal effect on performance (latency being the primary). By-and-large, a difference of 10-100 miles does not meaningfully degrade the network offering. It’s therefore easier for a competitor to enter the market and quickly build colocated infrastructure and provide a comparable capability.
On the “most granular” other extreme, a sensor or mapping network that collects data in sub 10 meter increments is incredibly challenging to replicate at-scale. Networks like Helium Mobile operate at this end of the spectrum. Mobile Hotspots have a range of 100-500ft, and so replicating that level of coverage is extremely challenging. This creates a moat for networks, better incentives for operators, and a pathway for geographically dense roll-out plans that can provide quality services in specific regions.
II. Supply Side overlaps with the Demand Side
DePIN networks use tokens to bootstrap the supply side of networks. In many networks, rational actors operate the supply-side only when they foresee a profitable outcome. In the most hyper-economic case, many Bitcoin miners only operate when mining is profitable, therefore turning on/off on a regular basis.
The challenge is, for networks where the primary incentive to operate infrastructure is economic, the network is required to consistently distribute tokens above a breakeven rate for operators to maintain network coverage and performance.
The opposite is where operators are willing and able to operate the infrastructure for free because of a shared ideological mission, or more probably, because they derive utility from the product.
Let’s consider the RTK DePIN Geodnet as an example. RTK is a technology which provides improved location accuracy – from meters to centimeters – for machines like UAVs and Robotics by calculating and distributing atmospheric correction values from a static ground station to the vehicles. For example, many farms today own or contract RTK nodes for use cases like precision farming, where the RTK equipment helps their robotic tractors more accurately plow fields. These farmers would not require a large token incentive to operate a DePIN RTK node instead of a regular Web2 node because they already require the node for normal business operations. They require less tokens than network types where the supply side isn’t also the demand side, and would likely maintain higher uptime because it’s core to their business success.
Another example is Hivemapper, a dashcam company whose dashcams upload videos and information from drivers. Many regular people already buy dashcams to help in the event of an accident and to protect against insurance fraud. They are therefore willing/able to buy and operate these devices already and require fewer tokens than a network where users specifically needed to perform an action that was outside their normal benefits or behaviors.
Although in both examples many users would operate nodes with no financial return, the tokens are helpful; they help acquire the marginal user, help ensure a user would buy the DePIN equipment vs a different brand/model, and also help with network brand awareness. But networks where the supply-side overlaps with the demand can distribute less than those networks which are primarily driven by operators whose primary motive is profit.
III. Competing on Performance, not Cost
Never compete on cost alone. We should enable capabilities “only possible on DePIN”.
Many DePIN networks today compete primarily on cost with centralized providers. For example, Helium Mobile advertises itself as a product to break-free from traditional Telco at only $20 per month.
Although competing on cost can work for an initial period to bootstrap a network of early customers, and certainly can help win the lower end of the market, networks that compete primarily on cost will struggle to develop pricing power.
DePINs that enable features or performance not possible through centralized alternatives can generate superior performance and therefore pricing premiums.
One clear example of this is Hivemapper. The refresh rate for Google Maps Street View data is 6-12 months, meaning that the images in the street view API are stale. However, once Hivemapper achieves network density, it could update these monthly or even hourly. It’s obvious that for dashcams, a distributed network can enable refresh rates orders of magnitude superior to that of Google operating it’s mapping vehicles. Also because Hivemapper can theoretically capture real-time high resolution video anywhere in the world, these same dashcams can unlock new use cases like Security and Real-time Intelligence which are not possible with lower refresh rates.
Another example is Grass, the decentralized web scraping service. Centralized web-scraping providers are not able to scrape many websites since they are operating out of DataCenter IP addresses and often blocked by providers like Cloudflare. Competitors obviously don’t want their data being scraped, so they block datacenter IPs in bulk.
Grass enables any residential IP to act as a scraper, and therefore be nearly impossible to block. This network has potential to generate real-time data scraping on many more websites than through a centralized approach.
IV. Demand Scales Nonlinearly with Supply
In many networks, supply must meet demand. For example in a compute network, as more demand onboards to the network, more compute units are required to service demand. This isn’t true in other network types, where a single node can scale to many customers.
As an example, consider Dawn Internet, a decentralized internet provider. They enable a single wholesale high-throughput fiberoptic cable to serve internet to hundreds or thousands of customers through distributing internet via a mesh network. In this example, once a wholesale node is setup (e.g. in a residential apartment complex), that same bandwidth can be sold to either 10 local units or 1000, therefore driving very high margins during that period. The internet can also be distributed between buildings to create an event wider mesh network.
Of course over the very long term these most profitable nodes may see other entrants enter and margins be competed down to more reasonable levels (market forces are good), but certain regulatory or real-estate considerations could provide strong protections. Nonetheless networks where an incremental increase in demand doesn’t require an increase in supply can scale much more efficiently and profitably.
Other Considerations
As part of any decision making process there are other considerations which are more bespoke, and therefore omitted here. These include the quality and prior experience of the founders, the scale of regulatory restrictions/hurdles, the distribution model, etc.
Summary
DePIN will disrupt many centralized providers entirely but also serve as a natural network extension to others (Helium Mobile carrier offloading). Networks that depend on the discussed attributes are well positioned to outperform other centralized providers and DePIN companies.