Consensus 2026 concluded its final day with a strong focus on artificial intelligence, tokenization, stablecoin infrastructure, and institutional blockchain adoption, as major crypto, fintech, and infrastructure companies unveiled new products and initiatives shaping the next phase of the digital asset industry.

The final day of the conference featured high-profile appearances, including a surprise live appearance by Changpeng Zhao, alongside keynote discussions involving Donald Trump Jr., Charles Hoskinson, and several executives focused on AI, payments, and tokenized infrastructure.

Crypto.com Expands Into Travel and Rewards Infrastructure

Crypto.com announced the launch of Crypto.com Travel, a new in-app booking platform powered by Bookit that allows eligible users to earn cashback rewards in CRO tokens on travel-related purchases.

The platform provides access to:

• hotels
• flights
• cruises
• car rentals
• entertainment experiences

The initiative represents a continued push toward integrating crypto rewards and digital assets into mainstream consumer services and real-world spending.

Midnight Foundation Introduces “Collateral Warehouse” Concept

Midnight Foundation also revealed plans for a new “Midnight Collateral Warehouse,” an open-source infrastructure model designed to help institutions manage and mobilize collateral across both traditional finance and blockchain networks.

According to the project, the system aims to improve institutional collateral management while maintaining financial privacy and interoperability between multiple financial environments.

The initiative reflects growing institutional interest in tokenized financial infrastructure and programmable settlement systems.

AI and Blockchain Convergence Accelerates

Several announcements throughout the day highlighted the rapidly growing intersection between blockchain infrastructure and artificial intelligence.

BioMatrix introduced what it describes as a “Human Participation Network” designed to connect real users with AI-generated content, tasks, and economic opportunities.

Meanwhile, Inveniam Capital Partners announced the launch of NVNM Chain, a Layer 2 blockchain designed specifically to provide verifiable records and attestation systems for AI agents.

The platform aims to help enterprises and regulators verify:

• source data
• AI decision-making processes
• accountability structures
• compliance records

as AI systems become increasingly integrated into finance and enterprise operations.

Healthcare Infrastructure Tokenization Gains Attention

Healthcare tokenization also emerged as a major topic during the final day of Consensus.

Medimint announced a blockchain platform designed to tokenize healthcare infrastructure assets, including:

• medical equipment
• hospital infrastructure
• diagnostic facilities

The company says the platform could enable fractional ownership and broader access to healthcare infrastructure investment opportunities.

The concept reflects the growing expansion of real-world asset tokenization beyond traditional sectors such as real estate and private credit.

Consensus 2026 Reflects Industry Shift Toward Real-World Infrastructure

Across all three days of Consensus Miami, one of the clearest themes was the industry’s continued shift away from speculative narratives toward infrastructure, payments, enterprise adoption, AI integration, and tokenized real-world systems.

Topics dominating discussions throughout the event included:

• stablecoins
• AI infrastructure
• tokenized assets
• payments
• enterprise blockchain adoption
• institutional settlement systems
• real-world utility

As the conference concluded, many of the announcements reflected a broader effort across the crypto industry to position blockchain technology as foundational infrastructure for finance, commerce, energy, healthcare, and AI-driven systems rather than purely speculative markets.

Key Highlights

• Datadog achieved a historic milestone with over $1 billion in quarterly revenue for Q1 2026, representing revenue expansion exceeding 32% and surpassing analyst projections by more than 500 basis points.
• Shares of DDOG rocketed approximately 30% during premarket hours following the May 7, 2026 earnings announcement.
• Management elevated both second-quarter and full-year projections, highlighting robust operational momentum and accelerating agentic AI adoption.
• The firm secured FedRAMP High authorization, unlocking access to expanded government contracting opportunities.
• Wall Street analysts maintain measured bullishness, with updated price targets positioning DDOG beyond $200, suggesting possible record highs ahead.

The exceptional Q1 2026 performance from Datadog has effectively challenged the recent bearish narrative that drove shares to extended lows. DDOG had suffered significant pressure as market participants worried artificial intelligence would erode traditional SaaS business models. Thursday morning’s results painted a dramatically different picture.

Datadog, Inc., DDOG

The monitoring and analytics specialist posted revenue expansion exceeding 32%, demolishing Wall Street expectations by over 500 basis points while crossing the billion-dollar quarterly threshold for the first time in company history. Premarket trading showed shares surging approximately 30% following the announcement.

Profitability metrics proved equally impressive. Adjusted operating income climbed 34%, while GAAP net income more than doubled year-over-year. Adjusted earnings crushed consensus forecasts by over 1,750 basis points.

Executives didn’t merely celebrate a strong quarter—they upgraded forward guidance across both the upcoming quarter and full fiscal year, attributing the optimism to sustained business strength and emerging agentic AI deployment trends.

Revenue Growth Catalysts

Expansion across the customer base proved instrumental, with the company’s largest accounts growing by 21%. Enhanced service adoption rates and fresh product introductions—particularly around artificial intelligence and data center monitoring capabilities—provided additional momentum.

Datadog’s core platform enables organizations to observe and evaluate their technology infrastructure with real-time precision. As artificial intelligence workloads expand, this functionality becomes increasingly critical rather than obsolete.

The FedRAMP High certification represents one of the most rigorous security standards for cloud service providers working with federal agencies. This designation positions Datadog to pursue substantially more government business while simultaneously validating its security posture for enterprise clients.

The balance sheet reflects financial strength with $4.8 billion in cash and liquid assets, while shareholder equity stands at nearly twice total liabilities. Leadership indicated this financial positioning could enable capital return programs within several years.

Insider transaction activity has drawn attention, with approximately $109.1 million in stock sales recorded over the previous three months against zero reported purchases. This dynamic remains a consideration for investors weighing the otherwise positive fundamental outlook.

Wall Street’s Response

Financial analysts greeted the quarterly results with tempered enthusiasm. Multiple firms highlighted the exceptional revenue performance and upgraded forecasts as significant positive indicators.

Current consensus price targets place DDOG near the upper boundary of its established trading corridor, though recent revisions are pressing above the $200 threshold—territory that would mark new all-time peaks.

Institutional investors control approximately 80% of outstanding shares and have been net distributors over the trailing twelve months. Following a 30% single-session advance, some portfolio rebalancing appears likely.

The valuation reflects a P/E multiple of 608x, illustrating the substantial future expansion investors are currently pricing into shares. DDOG carries a GF Score of 84 out of 100, featuring a maximum 10/10 growth ranking offset by a 4/10 profitability assessment.

Market observers have suggested that a decisive move to record highs could transform technical resistance into support, potentially establishing a baseline projection around $220 over the coming 12 to 18 months.

Fundamental Background

The structural deficit in the silver market has now persisted for a sixth consecutive year. According to forecasts by the Silver Institute, the gap between supply and demand in 2026 is expected to reach 67 million ounces, forcing the market to rely on accumulated reserves. However, the demand picture remains uneven.

Industrial consumption continues to decline, primarily due to the photovoltaic sector, where solar panel manufacturers are actively reducing the amount of silver used per cell in response to elevated prices. Against this backdrop, investment demand remains resilient: global ETP holdings have reached approximately 1.31 billion ounces, while silver lease rates in London have climbed to record highs amid a growing physical shortage.

Technical Picture

On the daily chart of XAG/USD, a two-phase structure is visible. From 21 November 2025, the instrument formed a strong upward impulse along an ascending trend line, reaching a peak on 29 January 2026. This was followed by a sharp collapse and a break below the trend line, with the low recorded on 6 February near the 64 level. A rebound then followed, and on 2 March a local recovery high was established — this area now corresponds to resistance around 96. A retest of the lows took place on 23 March 2026.

The horizontal volume profile spans the 68.300–89.000 range, with the point of control (POC) concentrated between 79.100 and 81.000. The price is currently trading below the lower boundary of this zone and remains under selling pressure. The nearest support lies at 68.300, followed by stronger support at 61.000, corresponding to the February crash low.

The RSI + MAs indicator shows readings of 55, 47 and 47. RSI remains above both moving averages; however, all indicators are within neutral territory, with no strong directional momentum currently visible.

Key Takeaways

The silver market continues to be influenced by two opposing fundamental forces: a structural supply deficit supported by investment demand, and weakening industrial consumption from the photovoltaic sector. The resolution of this imbalance is likely to determine the future direction and character of the market.

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This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.

Cloudflare shares fell sharply in after-hours trading on Thursday after the cloud infrastructure company announced major layoffs tied to its push into artificial intelligence.

According to recent reports, the stock dropped about 18% even after Cloudflare reported first-quarter earnings and revenue that topped Wall Street expectations.

The company posted revenue of $640 million for the quarter, up 34% from a year earlier and above analyst estimates of $622 million. Adjusted earnings came in at $0.25 per share, also ahead of expectations. However, investors focused instead on Cloudflare’s decision to cut more than 1,100 jobs globally, or roughly 20% of its workforce, as part of what it called an “agentic AI-first operating model.”

Chief executive Matthew Prince said Cloudflare’s internal AI usage has jumped more than 600% over the past three months. According to the company, thousands of AI agent workflows are now being integrated into daily operations. Management described the restructuring as a long-term operational shift rather than a traditional cost-cutting exercise.

The market reaction suggested investors remain cautious about aggressive AI-driven restructuring, especially as Cloudflare also issued softer-than-expected revenue guidance for the current quarter. The company forecast second-quarter revenue between $664 million and $665 million, slightly below analyst projections.

The layoffs add to a growing trend across the technology industry as companies reorganize around AI tools and automation. Amazon has continued trimming roles across cloud computing, devices, and media divisions while increasing spending on generative AI infrastructure. Microsoft has also cut jobs in several business units over the past year as it redirected billions of dollars toward AI data centers and products tied to OpenAI technology.

Meta and Coinbase have also announced workforce reductions in recent months while emphasizing efficiency and AI-focused restructuring. Industry tracking data shows more than 93,000 technology jobs have been cut globally so far in 2026, with automation and AI adoption increasingly influencing hiring decisions.

Despite the sell-off, Cloudflare maintained its full-year outlook. The company reaffirmed projected 2026 revenue between $2.805 billion and $2.813 billion and forecast earnings per share of $1.19 to $1.20. Management said expanding AI integration across operations should improve efficiency and help the company deliver new products faster.

Stablecoin-based cards could soon account for double-digit percentages of all cards in some Latin American markets, John Timoney, head of strategic partnerships at Rain, a payments infrastructure platform, said.

Retail stablecoin card spend grew about 105% to 106% over the past year, Timoney said during a panel at Consensus Miami 2026. Cards are physical or virtual, allowing users to spend stablecoins such as tether USDT$0.9997 and USD Coin (USDC) directly from a digital wallet for daily purchases.

Rain provides stablecoin infrastructure for card issuers and recently became a Mastercard Principal Member, allowing it to offer credit and prepaid cards on the Mastercard network. Rain and Mastercard are also exploring on-chain settlement for some card program flows using regulated stablecoins.

The company is not trying to replace card networks, Timoney said. It is trying to make stablecoin balances usable through existing networks that already reach merchants globally.

“The card networks over decades have rolled up hundreds of millions of merchants,” Timoney said. “Rain explicitly did not want to reinvent the wheel.”

Spend patterns are also becoming harder to distinguish from ordinary card activity, he said. Stablecoin card users are spending across typical merchant categories, including large global merchants and everyday purchases.

“There’s nothing too remarkable about that,” Timoney said. “And I think that is what is remarkable.”

Despite their growth, stablecoin cards account for less than 1% of global card spend, senior vice president of business development at Consensys Ray Hernandez said during the same panel.

Crypto card adoption

Latin America has become one of the clearest markets for adoption, Timoney added. Stablecoin cards are being used across custodial and non-custodial wallets, crypto exchanges and products that abstract the stablecoin experience from users.

The merchant still receives fiat in many of those transactions. That separates card-based stablecoin spending from direct crypto push payments, where merchants may have to manage crypto settlement, volatility and transaction risk more directly.

The bigger change may be behind the scenes. Rain says stablecoin settlement lets card programs settle on weekends and holidays, reducing trapped capital by more than 40% in some cases.

Traditional card programs often need to pre-fund network obligations or borrow from networks when banking rails are closed. Stablecoins can move outside bank cut-off times.

That can make rewards and card economics more flexible, Timoney said. Capital that would otherwise sit idle can be used elsewhere in the business.

Mastercard has been moving deeper into stablecoin payments. Earlier this year Binance, PayPal and Ripple joined Mastercard’s broader blockchain payments push. That push saw the payments giant agree to buy stablecoin infrastructure firm BVNK for up to $1.8 billion.

Christian Rau, Mastercard’s senior vice president of digital assets and blockchain, said mainstream adoption will depend on making the technology invisible to consumers.

“Other than the people in this room, nobody says ‘oh, I just did an onchain payment’,” Rau said. “The normal benchmark these days is you have a card sitting on your iPhone or on an Android. You tap it, the money is gone.”

The consumer-facing pitch is not an onchain payment, he added. It is the ability to spend any asset in real time, with the network protections users already expect.

Hernandez said the next stage depends on easier on-ramps, abstracted network fees and more local payment infrastructure. Today’s crypto card users are still mostly crypto-native consumers who already hold assets on-chain.

MetaMask is expanding its card strategy around self-custody, Hernandez said. The MetaMask Card, developed with Mastercard and Baanx, lets users spend from a self-custodial wallet while assets are converted into fiat at the time of purchase.

“If all we’re doing is replicating the Apple Pay experience, I think it’s going to be okay, but I don’t think we’re going to overtake,” Hernandez said.

Paying in crypto

That view drew a challenge from GoMining CEO Mark Zalan, who argued that stablecoins and card infrastructure add unnecessary intermediaries to crypto payments.

Zalan said users want to hold bitcoin in self-custody and spend it without converting into stablecoins or relying on off-ramps. He described conversion layers and payment intermediaries as “little helpers” taking small fees from each transaction.

“Protection is another word for rent-seeking,” Zalan said, referring to the consumer protections embedded in card transactions.

Timoney pushed back, saying payments are not only money movement. Card networks also handle chargebacks, merchant risk and other protections consumers and merchants expect.

Rau made a similar point. Most consumers were “socialized with deposit insurance” and chargeback protection, he said.

“Payment is more than moving money from A to B,” Rau said. “From a consumer perspective, the experience of payment is interoperability, safety and security.”

The Coming Collision Between AI Agents and DeFi

For years, decentralized finance has been built around one assumption: humans remain the primary participants in the market. Traders execute swaps, governance participants vote manually, liquidity providers rebalance positions, and treasury managers react to changing conditions based on human judgment.

That assumption may not survive the next decade.

A new wave of AI agents is beginning to merge with decentralized finance infrastructure, creating a future where autonomous systems—not humans—become the dominant users of financial protocols. This shift could fundamentally transform how liquidity moves, how markets behave, and how value is managed across blockchain ecosystems.

The collision between AI and DeFi is no longer theoretical. It is already beginning.

The Rise of AI-Native Financial Participants

Most discussions around artificial intelligence focus on productivity tools, chatbots, or content generation. But within crypto, the more disruptive evolution may be autonomous financial agents.

Unlike traditional trading bots that follow fixed instructions, AI agents are capable of adapting to changing market conditions, learning from data, and executing strategies independently. Combined with permissionless blockchain infrastructure, these systems can operate continuously without centralized oversight.

An AI agent connected to a crypto wallet can already:

• Analyze on-chain market conditions
• Execute trades automatically
• Move liquidity between protocols
• Optimize yield positions
• Hedge exposure in real time
• Participate in governance systems
• Monitor treasury risk
• React faster than any human trader

The result is the emergence of machine-operated finance operating at blockchain speed.

AI Trading Agents and the End of Human Reaction Time

One of the earliest impacts of AI in DeFi is likely to appear in trading markets.

Crypto markets already operate 24/7, creating an environment where human traders struggle to maintain consistent performance. AI agents remove this limitation entirely. They can monitor thousands of data points simultaneously while executing decisions in milliseconds.

These systems are evolving beyond simple algorithmic trading.

Future AI trading agents may combine:

• On-chain analytics
• Social sentiment analysis
• Governance proposal tracking
• Liquidity flow monitoring
• Cross-chain arbitrage detection
• Macro-economic data interpretation
• Real-time volatility modeling

This creates a market environment where human reaction speed becomes increasingly irrelevant.

In traditional finance, high-frequency trading firms already dominate market microstructure. DeFi may push this even further because blockchains are globally accessible, composable, and programmable by default.

When autonomous agents begin competing directly against one another, DeFi markets could evolve into machine-speed ecosystems where most activity occurs faster than human cognition can reasonably follow.

Autonomous Treasury Management

Treasury management is another area poised for transformation.

Today, DAOs and DeFi protocols often rely on human governance committees to allocate capital, manage reserves, or rebalance assets. These processes are slow, politically fragmented, and vulnerable to emotional decision-making.

AI systems could radically change this structure.

An autonomous treasury agent may eventually:

• Diversify treasury holdings dynamically
• Move idle capital into productive yield strategies
• Reduce exposure during volatility spikes
• Hedge against stablecoin depegging risks
• Allocate liquidity across chains automatically
• Simulate stress scenarios continuously
• Optimize revenue generation in real time

Instead of waiting for governance votes that take days or weeks, protocols may deploy AI-managed treasury layers capable of adapting instantly to market conditions.

This introduces a profound shift in governance philosophy. Human communities may increasingly define broad strategic objectives, while AI systems handle operational execution autonomously.

In other words, governance may evolve from direct management toward supervisory oversight.

AI-Generated Liquidity Strategies

Liquidity provision in DeFi has become increasingly complex.

Modern liquidity providers must understand impermanent loss, concentrated liquidity ranges, volatility exposure, fee generation, incentive emissions, and cross-protocol yield opportunities. For most retail participants, the ecosystem is already too sophisticated to manage efficiently.

AI agents are uniquely positioned to solve this complexity problem.

An advanced liquidity management agent could:

• Predict volatility changes
• Reposition liquidity ranges dynamically
• Optimize fee capture
• Exit unstable pools before liquidity collapses
• Rotate capital between protocols automatically
• Detect unsustainable yield incentives
• Balance risk-adjusted returns across chains

This could produce a major efficiency leap for DeFi markets.

However, it also creates a dangerous possibility: liquidity itself may become increasingly automated and hyper-reactive.

If thousands of AI agents identify the same risk signals simultaneously, liquidity could disappear from protocols at machine speed during periods of stress. This introduces the possibility of accelerated market cascades far more violent than previous DeFi crashes.

The same intelligence that improves efficiency may also amplify systemic fragility.

Wallet-Operating AI and Autonomous Economic Identity

Perhaps the most transformative development is the emergence of wallet-operating AI.

Today, crypto wallets are controlled directly by humans. But in the future, wallets themselves may become autonomous economic actors.

Imagine an AI agent with authority to:

• Pay for digital services
• Manage subscriptions
• Execute payroll
• Purchase compute resources
• Invest idle capital
• Borrow against assets
• Repay loans automatically
• Interact with smart contracts independently

This turns AI from a software tool into an active economic participant.

In this model, millions of autonomous agents could interact with blockchain infrastructure continuously without direct human input. Some may represent individuals, while others may operate on behalf of businesses, protocols, or entirely AI-native organizations.

The implications are enormous.

DeFi was originally designed as decentralized finance for humans. It may ultimately become the financial layer for autonomous machines.

Machine-Speed Markets and the Future of Volatility

As AI participation grows, markets may become structurally different.

Human traders are constrained by psychology, fatigue, limited attention, and delayed execution. AI agents are constrained primarily by compute power, data access, and protocol rules.

This changes market behavior dramatically.

Potential outcomes include:

Greater Efficiency

AI agents may eliminate many pricing inefficiencies, reducing arbitrage gaps and improving capital allocation across ecosystems.

Faster Liquidity Migration

Capital could move between protocols almost instantly as AI systems chase optimal returns.

Increased Market Reflexivity

AI agents trained on similar datasets may react identically during stress events, amplifying volatility.

Reduced Human Influence

Retail traders may struggle to compete against autonomous systems operating continuously with superior analytical capabilities.

Hyper-Competitive Yield Environments

As AI agents optimize returns aggressively, sustainable yields may compress significantly across DeFi markets.

The long-term result may resemble an autonomous financial battlefield where algorithms compete against algorithms in real time.

The Governance Problem No One Is Ready For

The rise of AI agents also introduces governance risks that DeFi has barely begun to address.

Key questions remain unresolved:

• Should AI agents be allowed to vote in DAO governance?
• Who is responsible if autonomous systems exploit protocols unexpectedly?
• Can malicious AI manipulate governance sentiment at scale?
• How do protocols defend against coordinated AI-driven liquidity attacks?
• What happens when AI agents discover profitable behaviors humans consider unethical?

These concerns move beyond technology into economic philosophy and legal theory.

DeFi governance was designed around human participation. But machine participants may soon outnumber human users across major protocols.

When that happens, governance itself may require redesign.

The Emergence of AI-to-AI Economies

The most radical possibility is that humans eventually become secondary participants within certain segments of DeFi.

AI agents could negotiate trades, provide liquidity, lend capital, hedge risk, and purchase services from one another autonomously. Entire financial ecosystems may emerge where most transactions occur between machines.

In such a world:

• Smart contracts become machine coordination layers
• Stablecoins become native settlement assets for AI systems
• DeFi protocols become infrastructure for autonomous economies
• Humans transition into supervisors rather than active operators

This would represent one of the largest structural transformations in financial history.

Not because finance becomes decentralized—but because finance becomes autonomous.

Conclusion

The convergence of AI and DeFi is creating a new category of market participant: autonomous financial intelligence.

What began as simple trading automation is rapidly evolving into wallet-operating AI capable of managing capital, executing strategy, and interacting with decentralized infrastructure independently.

This transformation could make DeFi markets faster, more efficient, and more adaptive than ever before. But it could also introduce unprecedented volatility, governance challenges, and systemic risks.

The core question is no longer whether AI will participate in DeFi.

It is whether humans will remain the dominant participants once it does.

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As global energy systems become increasingly decentralized, connected, and data-driven, a growing number of companies are exploring how blockchain infrastructure could modernize the way electricity markets operate.

One of the projects positioning itself at the center of this transformation is OpenVPP, a platform focused on bringing real-time programmable settlement and tokenized infrastructure into the energy sector.

The company describes its long-term vision as building the “Internet of Energy,” where electric vehicles, batteries, utilities, solar systems, and distributed energy resources can interact through automated, blockchain-powered financial infrastructure.

In this interview with Crypto Breaking News, OpenVPP Co-Founder and CEO Parth Kapadia discusses the future of tokenized energy infrastructure, real-world blockchain adoption, and how machine-to-machine payments could reshape the global utility sector.

“Energy Assets Need the Same Coordination the Internet Brought to Information”

According to Kapadia, the traditional utility sector still relies heavily on outdated financial systems that struggle to support increasingly decentralized energy networks.

“At its simplest, the Internet of Energy means giving energy assets the same level of connectivity, intelligence, and financial coordination that the internet brought to information,” Kapadia explained.

“EVs, batteries, solar systems, data centers, and distributed energy resources are all becoming active participants in the grid, but the systems used to track, reward, and settle their activity are still outdated.”

He believes the transition toward decentralized energy production, combined with growing global electricity demand, is creating the ideal environment for programmable settlement systems powered by blockchain infrastructure.

Bringing Real-Time Settlement to Energy Markets

One of OpenVPP’s primary goals is reducing the long settlement cycles that still dominate traditional energy markets.

“The infrastructure enables real-time settlement based on what actually happens at the device or asset level,” Kapadia said.

“If an EV, battery, or distributed asset contributes value to the grid, that activity can be measured, recorded, and settled automatically.”

The company says this approach can reduce administrative complexity while improving transparency and allowing consumers, businesses, and utilities to participate more efficiently in next-generation energy programs.

Building Consumer and Enterprise Infrastructure Simultaneously

OpenVPP operates through a dual-layer architecture composed of:

• Base, its consumer-focused layer
• Arc, its enterprise and utility-focused infrastructure layer

Kapadia says the structure was necessary because consumer energy participation and utility-grade infrastructure have fundamentally different operational requirements.

“Base allows us to create a more accessible consumer-facing layer where users, devices, and smaller assets can participate in energy programs and receive value from their activity,” he explained.

“Arc is built for utilities, enterprises, and larger-scale energy operations that require reliability, compliance, and integration with existing infrastructure.”

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Real-World Adoption Already Emerging

While many blockchain projects continue searching for practical use cases, OpenVPP says it is already tracking live energy activity through connected devices.

Kapadia revealed that the platform has already brought:

• more than 400 EVs onchain
• over 500 MWh of energy activity onchain

through integrations using connected vehicle data.

“The key driver is that we started with real energy problems, not just a token or a Web3 narrative,” he said.

“The grid needs more flexibility, consumers need better incentives, and enterprises need better settlement infrastructure.”

The company believes the same infrastructure can eventually support batteries, solar systems, chargers, data centers, and distributed energy resources operating across increasingly digitized power grids.

Tokenization Could Reshape Utility Markets

Looking ahead, Kapadia sees tokenization and blockchain infrastructure becoming increasingly important for the modernization of utility markets worldwide.

“Over the next decade, tokenization will help energy markets become more liquid, transparent, and automated,” he said.

“Blockchain infrastructure can turn verified energy activity into a programmable asset, making it easier to track value, distribute payments, and build new market structures around flexibility.”

He argues that energy may ultimately become one of the most important real-world asset categories connected to blockchain infrastructure due to its role across transportation, AI infrastructure, industrial systems, and data centers.

Focus Shifts Toward Infrastructure and Enterprise Partnerships

According to Kapadia, OpenVPP’s next phase will focus heavily on scaling both its technology stack and institutional partnerships.

The company is currently targeting:

• utilities
• EV platforms
• enterprise energy providers
• data center operators
• distributed energy infrastructure

as it expands real-time settlement systems and tokenized metering capabilities.

“Our goal is to move OpenVPP from proof of concept into critical infrastructure for the next generation of energy markets,” Kapadia concluded.

The interview reflects a broader trend emerging across the blockchain sector, where infrastructure projects tied to real-world industries such as energy, payments, AI, and logistics are increasingly attracting attention as markets mature beyond purely speculative use cases.