Is DePIN a Viable Business Model for Startups?

At some point, infrastructure stopped being an advantage and gradually became a liability. For many startups, capacity was built long before demand could reliably appear. Idle servers and hardware still had to be paid for even when usage stayed low. This is where DePIN models began to gain traction, as infrastructure could generate returns only when real demand was present.

Startups are adopting this model because existing or distributed resources can generate usage-based revenue rather than sit idle. This approach may lower upfront capital pressure and reduce long-term operational risk.

We’ve built many DePIN-focused solutions over the years, powered by cryptographic verification systems and incentive orchestration frameworks. Thanks to this expertise, we’re sharing this blog to discuss why DePIN is a viable business model for startups. Let’s start!

Key Market Takeaways for DePIN Platforms

According to Grand View Research, the blockchain market is entering a hypergrowth phase, moving from a valuation of roughly USD 31 billion in 2024 toward a projected multi-trillion-dollar scale by the end of the decade. This expansion matters for DePIN because decentralized infrastructure is among the earliest blockchain use cases, directly replacing real-world systems for compute, storage, and connectivity.

Source: Grand View Research

Momentum around DePIN has accelerated as real usage replaced speculation. In 2025 alone, DePIN networks attracted over a billion dollars in funding while already generating meaningful on-chain revenue. 

Millions of active devices now contribute resources at the network edge, driven by demand for low-latency compute and resilient systems that remain functional even during broader market volatility.

On the execution side, platforms like Render Network demonstrate how decentralized compute can serve real production workloads, supplying GPU power for AI training and high-end rendering across a global node network. 

In the IoT domain, IoTeX enables secure machine connectivity at scale, with tens of thousands of devices feeding verified data into DePIN applications.

What Is DePIN?

DePIN stands for Decentralized Physical Infrastructure Networks and refers to a system in which real-world infrastructure is owned and operated by multiple independent participants rather than by a single company. Blockchain-based verification and incentives coordinate these contributors so services remain reliable while ownership and costs stay distributed.

How Do DePIN Systems Work?

DePIN systems work by letting real people run physical hardware that provides services such as connectivity, compute, or storage, while software coordinates everything in the background. The network must verify that real work was performed using cryptographic proofs, and it can then automatically reward providers through smart contracts.

1. The Physical Layer 

This is the P in DePIN. It refers to actual physical devices deployed in the real world.

• Wireless hotspots such as Helium 5G nodes
• Dashcams and sensors, such as Hivemapper mapping devices
• GPU and CPU servers, such as Render compute nodes
• Energy batteries such as PowerLedger storage units
• Storage drives, such as Filecoin storage providers

These devices are not owned by a central corporation. They are owned by individuals and businesses called providers who invest in hardware to participate in the network.

2. The Verification Layer

This is the most critical technical challenge in DePIN. The network must reliably prove that real-world work actually occurred.

DePIN platforms achieve this using Proof-of-Physical-Work mechanisms.

• Cryptographic challenges that prove location or activity
• Multi-witness consensus where nearby devices validate each other
• Trusted Execution Environments that ensure computations were not altered
• Oracle networks that verify external conditions, such as weather or energy output

For example, when a Hivemapper dashcam captures road data, it does not simply upload video. It generates cryptographic proof of time and location, preventing recycled or manipulated data from entering the network.

3. The Economic Layer

This layer coordinates the entire network without a central authority. It runs on blockchain infrastructure and governs incentives.

A. The Token Rewards System

When a provider’s hardware performs verified work such as providing connectivity or storing data, the protocol automatically distributes native tokens. This is executed through smart contracts with no manual control.

B. The Burn and Mint Equilibrium Model

Most mature DePIN platforms rely on this model to maintain long-term sustainability.

• The customer pays for the service. A developer purchases $100 worth of storage
• Protocol burns tokens. $100 worth of native tokens are destroyed
• New tokens minted for providers. Providers receive freshly issued rewards

This creates a self-reinforcing economic loop. More usage leads to more tokens burned. Scarcity increases as demand grows, aligning network growth with provider incentives.

The Complete Workflow

Below is a real example of decentralized cloud storage in action.

Step-by-Step Flow

• User action – Developer uploads a file to DeCloud Storage
• Smart contract trigger – The contract automatically splits the file into encrypted fragments
• Geographic distribution – Fragments are routed to multiple storage nodes worldwide
• Proof of storage – Each node cryptographically proves it is storing the fragment correctly
• Automatic payments – Tokens flow from the developer to storage providers through smart contracts
• Verifiable dashboard – All transactions are visible on a public blockchain explorer

Is DePIN a Viable Business Model for Startups?

Yes, DePIN can be a viable business model for startups when designed carefully around real service delivery. It can gradually reduce upfront capital needs by shifting infrastructure ownership to the network while software coordinates trust and incentives.

But it should work only if performance can be verified technically and incentives stay aligned over time.

1. The Economic Viability

Traditional infrastructure startups face a brutal paradox. They must build capacity before proving demand, locking in millions of dollars in hardware that may sit idle. DePIN flips this model on its head.

The Capital Efficiency Breakthrough

Expense Category	Traditional Startup	DePIN Startup
Initial Hardware (CAPEX)	$5M – $50M (raised from VCs)	$0 (crowdsourced from community)
Time to 1,000 Nodes	24–36 months (procurement, permits)	3–6 months (viral hardware adoption)
Customer Acquisition Cost (CAC)	$300 – $500 per B2B customer	Negative CAC (hardware buyers become evangelists)
Geographic Flexibility	Locked into licensed or planned regions	Global from Day 1 (organic, demand-driven growth)

Why this matters for a startup

It extends your runway 5 to 10 times. Instead of spending 18 months raising a Series B to buy more servers, you spend those months scaling your software and community while your network grows organically.

Evidence in Action

• Helium’s 5G Network: Scaled to 400,000+ hotspots with less than $100M in total raised capital. A traditional telecom would require $2 to $3B for equivalent coverage.
• Render Network: Provided $12M+ monthly in GPU compute in 2025 without owning a single data center.

2. The Execution Viability

Viability is not just about the idea. It is about execution. Most DePIN failures stem from three core mistakes.

A. The Ghost Network Problem

If you cannot prove physical work, you are paying for fiction.

Solution: Hybrid Verification Systems

• Cryptographic Proofs: GPS signatures, trusted execution environments (TEEs).
• Multi-Witness Consensus: Nearby nodes validate service provision.
• Oracles and Audits: Third-party verification for enterprise SLAs.

Example: Hivemapper uses AI validation and GPS proofs to ensure dashcam imagery is unique and recent, preventing Google Maps scraping.

B. The Tokenomics Death Spiral

What happens when the token price drops 80 percent and providers shut off hardware?

Solution: Burn and Mint Equilibrium (BME) plus Fiat On Ramps

Customers can pay in stablecoins to reduce exposure to price swings and keep costs predictable. The protocol may buy and burn tokens using real revenue which can steadily support demand. Providers should earn tokens tied to delivered service value so rewards reflect usage rather than speculation.

Example: Aethir’s enterprise GPU network maintains 99%+ uptime despite token volatility by pegging service prices to USD and using treasury-hedging strategies.

C. The Enterprise Trust Gap

No Fortune 500 will bet its operations on community goodwill.

Solution: Curated Enterprise Layers

Tiered SLAs can separate community-grade services from enterprise-grade offerings with clear guarantees. Insurance-backed uptime commitments may add confidence for critical workloads. Compliance-ready nodes can support HIPAA, GDPR and similar regulatory requirements while enabling enterprise adoption.

3. The Market Viability: Is There Real Demand?

The most elegant tokenomics fail without customers. Demand drivers in 2026 make DePIN uniquely timed.

Market Force	Why It Favors DePIN	Startup Opportunity
AI Compute Crunch	Centralized GPU shortages and edge inference needs	Decentralized GPU networks growing at 200 percent YoY
IoT Data Explosion	50B+ devices by 2030 need cheap connectivity	Wireless DePIN at 60 percent lower cost
Data Sovereignty Laws	GDPR and Schrems II require local processing	Distributed networks are inherently compliant
Cloud Cost Rebellion	AWS and Azure bills crushing startups	DePIN storage offers up to 70 percent savings

Quantitative Validation

• DePIN sector revenue crossed $15B annualized in Q4 2025.
• Enterprise adoption grew over 300 percent in 2025 (Messari DePIN Report 2026).
• 45 percent of Fortune 500 companies are piloting at least one DePIN solution.

The Viability Checklist: Is DePIN Right for Your Startup?

Score your idea against these seven questions. Four or more Yes answers indicates strong fit.

• Is your hardware commoditized & user-installable
• Is demand geographically distributed?
• Can service be cryptographically verified?
• Do unit economics close?
• Is there incumbent frustration?
• Can you design “earning” simplicity?
• Is there a regulatory pathway?

The Verdict

DePIN is viable for startups when:

• You are building in a capital-intensive sector where bypassing CAPEX is a 10x advantage.
• You adopt the orchestrator mindset rather than ownership. The product is a coordination software.
• You design for real utility first and tokens second. Tokens are a mechanism, not the product.
• You are prepared to manage operational complexity across the verification, legal, and community layers.

DePIN is likely not viable when:

• You require military-grade reliability from day one.
• Your market demands instant, ubiquitous coverage at launch.
• You are uncomfortable with transparent on chain economics.
• You expect traditional SaaS margins immediately. Early DePINs reinvest heavily in growth incentives.

How Startups Can Use the DePIN Model to Generate Revenue?

Startups can generate revenue with DePIN by charging small transaction fees for real-world services such as compute storage or connectivity. As usage grows, the protocol can gradually capture value through burn-based token mechanics that may directly link demand to scarcity.

1. The Transaction Fee Layer

The most direct revenue stream comes from taking a small percentage of every transaction executed on the network. This works similarly to an app store fee but is applied to physical infrastructure services such as compute, storage, and connectivity.

Example Case Study. Render Network GPU Compute

• Service. Decentralized GPU rendering for 3D animation, AI training, and visual effects
• Pricing Model. $2.50 to $4.50 per GPU hour, compared to $3.50 to $6.00 on AWS or Azure
• Revenue Generation: 5 percent protocol fee on every transaction.

By Q4 2025, the network was processing over $12M in monthly transactions, resulting in approximately $600,000 in recurring protocol fees.

2. The Token Economics Layer

The Burn and Mint Equilibrium BME model has become the dominant sustainable token design. Instead of relying on inflation, value is captured through controlled token scarcity tied directly to real usage.

How It Works in Practice

• Customer Action: An AI startup pays $10,000 for GPU compute
• Token Mechanics: The protocol automatically buys $10,000 worth of native tokens
• Value Capture: Tokens are burned and permanently removed from circulation
• Revenue Impact: Reduced supply increases token value, benefiting the protocol treasury and long-term stakeholders

Example Case Study: Helium Network Wireless Connectivity

• Service. Decentralized 5G and IoT wireless coverage
• Pricing Model. $20 per month for unlimited 5G compared to $60 plus from traditional carriers
• BME Impact. $25M in monthly service revenue results in approximately $1.25M in monthly token burns
• Network Effect. Every 1 percent increase in usage drives around a 0.7 percent increase in token value

The network now operates at scale with over 400,000 active nodes processing more than 2.5 billion data transfers every month.

3. The Enterprise Licensing Layer

While the base network remains decentralized, startups unlock higher margin revenue by offering enterprise-grade services on top of it. These include compliance controls, curated infrastructure, and service level guarantees.

Example Case Study: Aethir Enterprise GPU Cloud

• Core Network. Community-owned decentralized GPU marketplace
• Enterprise Layer. Curated and compliance-ready GPU clusters with 99.9 percent SLA guarantees
• Pricing Premium. 40 to 60 percent higher than open marketplace rates
• Numerical Reality. $160M plus in annual recurring revenue achieved in late 2025

Revenue is balanced across models, with about 60 percent from enterprise contracts and the remaining 40 percent from the decentralized marketplace.

4. The Data and API Monetization Layer

DePIN networks produce high-quality real-world data as a byproduct of infrastructure usage. When aggregated and anonymized, this data becomes a powerful monetizable asset.

Example Case Study: Hivemapper Decentralized Mapping

Core Service. Continuously updated street-level imagery

Data Products. Traffic analysis, change detection, and commercial intelligence

Pricing Structure

• Base API access at $500 per month
• Historical image queries are priced between $0.10 and $2.00 per image
• Enterprise analytics packages range from $10,000 to $50,000 per month

Enterprise offerings are generating over $5M in recurring monthly revenue, demonstrating that DePIN data and infrastructure can sustain commercial demand at scale.

How DePIN Startups Prevent Early Oversupply?

DePIN startups prevent early oversupply by releasing hardware only where real demand already exists, thereby reducing idle-capacity risk. They may actively link rewards to verified usage so tokens flow only when infrastructure is actually used.

The Oversupply Problem

Every hardware unit deployed represents a future claim on the token treasury. If 10,000 sensors are deployed but only 1,000 generate usage, the protocol incurs costs for 9,000 idle assets that may never generate revenue.

Take, for example, Helium’s early growing pains from 2019 to 2021. The network grew rapidly to more than 900,000 hotspots, but nearly 65 percent were concentrated in residential areas with minimal commercial demand. 

Early providers earned tokens for simply being online, regardless of whether anyone used their coverage. 

This created a $ 1.2 billion token liability for coverage that generated less than $ 5 million in actual data transfer revenue at its peak. The result was a dangerous 240-to-1 imbalance between token rewards and real-world utility.

The prevention framework focuses on controlling deployment through demand signals, so infrastructure scales only when real usage is proven.

1. Geospatial Targeting

Instead of paying equal rewards across all locations, modern DePINs use dynamic, location-aware incentive models.

Case Study: Hivemapper’s Intelligence-Driven Bounty System

Hivemapper faced the classic mapping dilemma. Dashcams were deployed everywhere, but maps were updated only where people actually drove. Their solution was a demand-weighted bounty algorithm.

How it works

The world is divided into dynamic tiles. Each tile has a commercial value score based on:

• Business density, where office districts score ten times higher than residential areas
• Road infrastructure changes, where construction zones receive premium weighting
• Explicit enterprise requests, where logistics companies pay for specific routes

For example, a dashcam driving through San Francisco’s Financial District earns 8.50 dollars per kilometer in HONEY tokens. The same device in a rural Nebraska neighborhood earns 0.85 dollars per kilometer. This creates a 10x differential based solely on commercial utility.

2. Dynamic Token Emission

Leading DePINs have moved beyond fixed issuance schedules to algorithmically adjust emissions based on real-time supply-and-demand balances.

Case Study: Render Network’s GPU Orchestration Model

Render does not just connect GPU providers with users. It actively manages supply to match the fluctuating demands of the AI rendering market.

Real-time utilization dashboard

Every six hours, the protocol calculates:

• Total available GPU hours at 15.4 million monthly
• Booked GPU hours at 11.2 million monthly, representing 72.7 percent utilization
• Regional imbalances, with Asia at 89 percent utilization and Europe at 68 percent

Adaptive response

When Asian utilization hit 89 percent in the fourth quarter of 2025, Render’s algorithm automatically:

• Increased token rewards for new Asian GPU providers by 22 percent
• Reduced European emissions by 15 percent where utilization was lower
• Created a priority bonus of 40 percent additional tokens for specific GPU types, such as A100 and H100, in high-demand regions

3. The Staged Launch Framework

The staged launch framework limits deployment to regions with verified demand so infrastructure is added only when it can be used. This approach may gradually scale networks while protecting the treasury from early oversupply.

Case Study: WeatherXM’s Agricultural Forecasting Model

Instead of deploying weather stations globally, WeatherXM implemented a predictive, staged deployment strategy tied to agricultural cycles.

Phase 1 Pilot, 6 months

Deployment focused only on California’s Central Valley during the almond bloom season to align supply with immediate agricultural demand. The target was 500 stations across 300 square miles, supported by pre-sold data contracts valued at $750,000 annually. This approach could steadily ensure high utilization from day one.

Phase 2 Expansion, 12 months

Expansion occurred across five additional agricultural regions, guided by crop value per acre, with vineyards ranking higher than wheat fields. 

Regions with higher weather volatility, such as hurricane-prone areas, were prioritized, while locations underserved by NOAA were selected. This approach could gradually expand coverage without creating excess idle infrastructure.

Is Token Appreciation Required for the DePIN Model to Succeed?

This question strikes at the heart of DePIN’s fundamental viability. For years, critics argued that DePINs were merely token Ponzi schemes that required perpetual price appreciation to survive. The 2024 to 2026 market evolution has delivered a definitive answer through economic stress tests, bear markets, and actual enterprise adoption data.

The Short Answer: No, But…

Token appreciation is not required for DePIN operational success, but it is essential for long-term network security and provider incentive sustainability.

Let’s unpack this critical distinction with data from market leaders that have survived both bull and bear cycles.

The Operational Viability

Case Study 1: Filecoin’s Price Resilient Storage Network

FIL token price declined by 82 percent between the 2021 market peak and the 2023 cycle low. This period tested whether real network usage could survive without token price support.

The Result

• Storage Capacity increased from 14 EiB to 22 EiB, which is a 57 percent rise
• Storage Utilization grew from 2 million dollars to 8 million dollars in monthly revenue which is a 300 percent increase
• Provider Retention stayed strong with 85 percent of storage providers remaining operational
• Network Security improved as the network became more distributed and less concentrated

Why It Worked

Filecoin providers earn through two distinct revenue streams. Block rewards from token issuance remain price sensitive, while storage fees paid in FIL or stablecoins stay largely price independent.

During the bear market, storage fees represented 25 to 40 percent of provider income. This was enough to cover operational costs even with depressed token prices. The network continued functioning because real utility created real revenue.

Case Study 2: Helium’s Migration to Solana

HNT token declined by 95 percent from its all time high during the network’s blockchain migration. This phase tested whether network adoption could continue amid extreme price pressure and infrastructure change.

The Result

• Network Coverage continued growing at 15 percent monthly
• Data Transfer increased from 60 TB to 250 TB monthly
• Mobile Subscribers grew from 5,000 to more than 250,000 despite the token price decline

The Critical Innovation

Helium introduced Data Credits which are non-tradable units pegged to USD and purchased by burning HNT. This created the following outcomes.

• Stable service pricing for customers at 0.50 dollars per GB, regardless of HNT price
• Constant burn pressure on the HNT supply is driven by real utility
• Greater provider payment stability through hybrid reward structures

The Economic Architecture: Separating Utility from Speculation

Layer 1: The Service Economy (Price Agnostic)

This layer must function regardless of token price:

Component	Price Sensitivity	2026 Solution
Customer Pricing	Zero	Stablecoin or USD pegging
Service Delivery	Zero	Cryptographic proofs work at any price
Basic Rewards	Low	Multi-currency payouts: 50 percent token and 50 percent stable
Network Security	Medium	Staking requirements dynamically adjust with the token price

Layer 2: The Speculation Economy (Price Sensitive)

This layer benefits from appreciation but doesn’t require it:

Component	Price Sensitivity	Purpose
Early Provider ROI	High	Initial network bootstrap
Protocol Treasury	High	Long-term development funding
Governance Value	Medium	Voting power valuation
Secondary Markets	High	Liquidity and exit options

Conclusion

DePIN can be a viable business model when it is built as real infrastructure rather than a token story. It works best when verification is strong, incentives are aligned, and the product feels usable from day one. Enterprises can clearly gain cost efficiency, resilience, and the ability to scale without heavy upfront ownership. Startups that solve these pieces early may steadily build trust and long-term defensibility. With the right strategy and a capable technical partner, DePIN can become a sustainable revenue engine rather than an experiment.

Looking to Build a DePIN Platform?

IdeaUsher can help you design a DePIN platform that aligns incentives with real network usage and long-term sustainability. Our team can model token economics, verification layers, and node coordination to ensure the system scales reliably over time.

Backed by 500,000-plus engineering hours and ex-MAANG and FAANG talent, we go beyond smart contracts to engineer infrastructure that holds up in the real world.

Why Build with Us?

• Beyond Tokens: We architect for Proof of Physical Work, ZK attestations, and anti-Sybil mechanics.
• Solve the Hard Problems: From hardware oracle risks to geographic cold starts, we have built the solutions.
• Full Stack Build: Tokenomics, firmware integration, node software, and dashboards.

Explore our work to understand the depth and reliability behind our builds.

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