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Privacy and accountability can coexist onchain, say panelists at Consensus Miami

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Privacy and accountability can coexist onchain, say panelists at Consensus Miami

Public blockchains make transactions transparent enough to trace, audit and police, but that visibility can come at the expense of user privacy. Traditional compliance systems often address accountability by identifying people, but that can undermine one of crypto’s original promises: the ability to transact without exposing personal identity by default.

According to panelists at CoinDesk’s Consensus Miami conference earlier this week, those tensions are increasingly solvable through an onchain “intelligence layer” that combines hybrid blockchain architecture with wallet-address-level monitoring.The idea is to split the work across different parts of the system. Private permissioned networks can give institutions the accountability and credibility they need, while public permissionless chains can provide liquidity, and blockchain-forensics tools can help platforms screen transactions at the wallet-address level without automatically tying every user to a real-world identity.

Rajeev Bamra, global head of strategy for digital economy at Moody’s Ratings, said the conventional intelligence layer answers three questions: “Who is it? What are they doing? And can I trust the record?” Those have been addressed in traditional finance by banks, custodians, clearinghouses and credit-rating agencies, he said.

Bamra estimated the institutional digital-finance market at roughly $35 billion today, against more than $200 trillion in annual clearing-house flows in conventional finance, with growth of “over 100 or 150%” in the past 18 months. Blockchain architecture, he predicted, will not be uniformly public or private but a hybrid. “Private permission networks are going to offer the accountability, the credibility aspect,” he said, while “the public permissionless brings the liquidity which the private permissions don’t.”

Pauline Shangett, chief strategy officer at the non-custodial exchange ChangeNOW, firmly sided with the user-side argument. “Bitcoin at its core, at its origin was a semi-anonymous digital cash,” she said.

ChangeNOW, which does not enforce KYC by default, works with AML providers and blockchain forensics firms to monitor flows at the wallet-address level. “All of this blockchain forensics infrastructure allows us to not map people who are passing funds through our system, but instead map their addresses,” Shangett said.

When law-enforcement agencies come to ChangeNOW, Shangett said, the company provides transaction data without doxing the person behind the transaction. She said that compromise allows the platform to provide registration-free swaps while still maintaining internal accounting systems and working with authorities when illegitimate funds move through the service.

On regulation, Bamra said cross-border frameworks like the European Union’s Markets in Crypto-Assets Regulation and the U.S. GENIUS Act ask the same fundamental questions about asset quality, segregation and liability, but diverge sharply at the specifications layer. “We think there is regulatory convergence in intention, but there’s fragmentation in reality or in execution,” he said.

Shangett ended with a regulatory-liability framing, which she suggested cuts to the heart of where responsibility should actually sit.

“The agents who should be held liable for the regulatory frameworks and the adoption thereof are agents who are dealing with emission and not transmission,” she said.

Real Stories: Hair Treatment Results from Users

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Real Stories: Hair Treatment Results from Users

Most people who start a hair treatment don’t talk about the first few weeks. They talk about the end result — thick hair, no more shedding, finally feeling confident again. But the middle part, the waiting and the uncertainty, is where the real story lives. Understanding what genuine hair recovery actually looks like can help you set better expectations and make smarter decisions about your own hair.

What “Results” Actually Mean in Hair Treatment

Hair doesn’t recover the way a wound heals. There’s no clear before-and-after moment you can point to. Hair growth happens in cycles, and when treatment begins, the first job is usually stopping further loss — not growing new hair. That alone can take two to three months.

This is something many users don’t expect. They start treatment hoping to see new growth within weeks, and when they don’t, they assume nothing is working. But stabilization is progress. It’s the foundation everything else builds on.

Real results tend to arrive in stages:

  • Reduced shedding (usually first sign, around weeks 6–10)
  • Scalp improvement — less oiliness, itching, or flaking
  • Fine, thin regrowth along the hairline or parting
  • Gradual improvement in hair texture and density over months

Why Individual Results Vary So Much

Two people can follow the same treatment plan and have completely different outcomes. This isn’t a failure of the treatment — it reflects the complexity of hair loss itself.

Hair fall has many root causes. Nutritional deficiencies, thyroid imbalances, hormonal shifts, chronic stress, scalp conditions, and genetics can all be involved — sometimes together. A treatment that addresses one cause won’t necessarily fix another. Someone with iron deficiency responding to supplementation will have a different recovery curve than someone dealing with androgenetic alopecia that requires topical and internal intervention simultaneously.

Age, how long the hair loss has been happening, and overall health also shape results. Someone who has been losing hair for two years is working with more damage than someone who caught the problem early.

What Real Users Tend to Report

When people share honest accounts of their hair treatment journeys, a few themes come up consistently. First, most say the process required more patience than they anticipated. Second, many mention that changes in habits — diet, sleep, stress management — were as important as the products they used.

A common pattern in user experiences is noticing something small first: less hair on the pillow, a slightly fuller ponytail, or a dermatologist pointing out new growth during a checkup. These moments matter because they’re often the first signal that the body is responding.

Browsing through Traya hair treatment reviews gives a candid look at this kind of progression — not just the wins, but the slow, uneven nature of how hair recovery actually unfolds for different people.

The Role of Root Cause Identification

One reason many people struggle through multiple treatments without success is that the underlying cause was never properly identified. Treating hair fall generically — with the same shampoo or supplement everyone uses — rarely works if the root issue is something specific like PCOS-related hormonal imbalance or a prolonged nutritional gap.

Some approaches, like Traya’s, focus on diagnosing what’s actually driving the hair loss before recommending treatment. This matters because the same symptom (hair fall) can have very different origins, and the path forward changes depending on what you find.

A blood test, a scalp analysis, or even a detailed health history can reveal things that change the entire treatment strategy.

Managing Expectations Without Losing Hope

Here’s what honest hair treatment stories teach us: recovery is possible for most people, but it’s rarely fast or linear. There will be months that feel like nothing is changing. There will be times when progress seems to stall. That doesn’t mean the process isn’t working.

The users who see the best long-term results tend to be the ones who stayed consistent, got their root cause properly identified, and resisted the urge to switch treatments every few weeks out of impatience.

Final Thoughts

Hair treatment results are real, but they’re not always photogenic. Behind every success story is usually a longer, quieter story of figuring out the actual cause, adjusting the approach, and showing up consistently over months. If you’re somewhere in that middle chapter right now, the most useful thing you can do is make sure you understand why your hair is falling — and treat that, not just the symptom.

Germany Mulls Crypto Tax Overhaul, 1‑Year Exemption at Risk

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Germany Mulls Crypto Tax Overhaul, 1‑Year Exemption at Risk

Germany is preparing to change how it taxes Bitcoin and other cryptocurrencies from 2027, potentially ending one of Europe’s most generous long-term holding exemptions as it seeks to raise additional revenue and tighten tax compliance.

Finance Minister Lars Klingbeil said at an April 29 press conference on the 2027 federal budget that the government wants to “tax cryptocurrencies differently,” and key points include an extra 2 billion euros (about $2.3 billion) in revenue from crypto taxation and measures against financial and tax crime.

Under current rules, private crypto gains in Germany are taxable if the assets are sold within one year of acquisition, but are generally tax-free after that period. The exemption has made Germany one of the more favorable European jurisdictions for long-term Bitcoin and crypto holders.

The finance ministry’s 2022 and 2025 guidance confirmed that this one-year “Haltefrist” also applies to coins used in staking and lending, after an earlier plan for 10 years was dropped. Tax advisory firms such as Blockpit describe the rule as a key advantage for German retail investors, especially long-term holders.

Germany plans to “tax cryptocurrencies differently.” Source: Bundesfinanzministerium

Klingbeil did not explicitly reference the holding period in his April remarks. However, industry groups, including the German Bitcoin Association, say the exemption is the most likely target if the government aims to generate significant revenue from crypto taxation.

Related: Germany‘s central bank president touts stablecoin and CBDC benefits for EU

Bitcoin and crypto tax accountant Robin Thatcher told Cointelegraph that removing the 12-month tax-free disposal would “significantly weaken Germany’s pull as a crypto hub,” and that other jurisdictions “should be copying this policy rather than Germany changing it.”

Cointelegraph reached out to Germany’s Federal Ministry of Finance for comment, but had not received a response by publication.

EU transparency push and policy alignment

The tax debate also comes as Germany prepares for broader crypto reporting under the EU’s DAC8 regime.

Since January, Germany’s implementation of the EU’s DAC8 regime via the Crypto Asset Tax Transparency Act requires crypto asset service providers (CASPs) to report detailed customer transaction data to the Federal Central Tax Office and other EU authorities, dramatically reducing the scope for undeclared crypto trading.

Austria, where Vienna-based crypto broker Bitpanda is headquartered, scrapped its own tax-free holding period for crypto in 2022 and moved to taxing gains as capital income regardless of how long coins are held.

Abolishing Austria’s holding period “extremely stupid idea.” Source: Eric Demuth

Bitpanda co-founder Eric Demuth has since described Austria’s move as “an extremely stupid decision,” arguing in a March 12 X post that it created more bureaucracy and complexity for users and platforms while bringing “hardly any additional benefit” for the state and warning that Germany should not repeat the same mistake.

Related: Bitget taps ex-Bitpanda legal chief Oliver Stauber to build Vienna MiCA hub

Thatcher said the change would put Germany “broadly in line with Austria,” with a 27.5% flat tax, and “not far” from the United Kingdom’s 24% top capital gains tax, causing Germany’s structural competitive edge to “disappear overnight.”

Critics see tax push eroding Germany’s crypto appeal

A spokesperson from Bitpanda told Cointelegraph this is a “critical juncture for Germany’s digital economy.” Any reform should not be “a mere revenue exercise,” they said, especially since the gains to the state would be “negligible” at approximately 0.02% of the federal budget. They added that any new framework “must prioritize market competitiveness and prevent a migration of activity toward unregulated, offshore venues.”

Thatcher said “the packaging matters,” and that the framing shows the motivation is fiscal rather than principled, “sitting inside a 98 billion euro deficit-reduction budget,” alongside cuts to health, pensions and levies on alcohol and tobacco. “Investors and entrepreneurs notice when they are bundled in with so-called sin taxes,” he said, “it shows how the state views the asset class.”

Erald Ghoos, chief executive officer of OKX Europe, told Cointelegraph the plan would hurt Germany’s adoption and competitiveness “in one move,” pushing people toward offshore platforms “without [Markets in Crypto Assets] MiCA obligations.”

He cited Austria as a failed example that created “compliance headaches for minimal revenue gain,” adding that MiCA has “done real work harmonizing regulation,” but that “Europe keeps losing ground” when it comes to taxation.

Magazine: Bitcoin will not hit $1M by 2030, says veteran trader Peter Brandt

Cointelegraph is committed to independent, transparent journalism. This news article is produced in accordance with Cointelegraph’s Editorial Policy and aims to provide accurate and timely information. Readers are encouraged to verify information independently.

Coinbase stock drops 4% after Q1 revenue miss as crypto trading slows

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Coinbase stock drops 4% after Q1 revenue miss as crypto trading slows

Coinbase (COIN) shares fell about 4% in after-hours trading Thursday after the crypto platform reported weaker-than-expected first-quarter results as falling crypto prices weighed on trading activity, one of the company’s main sources of revenue.

The company posted a loss of $1.49 per share, compared with analyst expectations for a 27-cent profit. Revenue came in at $1.41 billion, below estimates of $1.52 billion.

Transaction revenue totaled $755.8 million, missing analyst expectations of $805.2 million. Subscription and services revenue, a segment investors closely watch as Coinbase tries to reduce its reliance on trading fees, totaled $583.5 million, below expectations of $619.3 million.

Crypto markets weakened sharply as bitcoin BTC$79,967.69 and other digital assets fell. Lower prices and reduced volatility typically lead to weaker spot trading volumes across exchanges. Investors had expected a slowdown after the crypto selloff early in the quarter, even though bitcoin rebounded roughly 12% in March.

Coinbase has spent the past several years expanding beyond its core trading business into stablecoins, staking, derivatives and blockchain infrastructure. The company said Wednesday that its global crypto trading volume market share rose to 8.6%, a record high, driven partly by growth in derivatives trading.

Trailing 12-month derivatives trading volume increased 169% year over year, while retail derivatives revenue surpassed an annualized run rate of $200 million for the first time, Coinbase said.

The company also pointed to growth in prediction markets and stablecoin activity. Coinbase said its prediction markets business surpassed $100 million in annualized revenue within its first two full months following its U.S. launch.

Meanwhile, Coinbase said its Base blockchain processed 62% of global onchain stablecoin transaction volume during the quarter.

Earlier this week, Coinbase said it would cut about 700 jobs, or roughly 14% of its workforce, as part of an AI-driven restructuring effort. The company also cited the broader crypto downturn as a factor behind the layoffs.

Investors are increasingly focused on whether Coinbase’s subscription and infrastructure businesses can offset the cyclical swings of crypto trading revenue during weaker markets.

CZ floats Binance.US revival to give U.S. users access to global crypto liquidity

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CZ floats Binance.US revival to give U.S. users access to global crypto liquidity

Miami — Binance founder Changpeng “CZ” Zhao said a revived Binance.US is one possible path for giving American crypto traders access to better prices.

Binance wants to help restore U.S. users’ access to global crypto liquidity, CZ said, naming a possible Binance.US revival as one route after years of limited engagement in the American market.

“The best liquidity in crypto is outside of the U.S.,” CZ said during Consensus Miami 2026. “Crypto is one of the very few markets that U.S. don’t have access to the best prices.”

“I think in our ecosystem, Binance has the best liquidity in this market,” he continued. “We would love to be able to provide that in some way, either revitalize Binance.US or somehow provide U.S. the best liquidity in the world and the best prices for the consumers.”

The comments come two years after CZ resigned as Binance CEO and pleaded guilty to numerous U.S. charges. Zhao was later sentenced to four months in prison, released in 2024, and pardoned by President Donald Trump last year.

Binance.US has been plotting a comeback under CEO Stephen Gregory, with plans to expand beyond spot crypto trading into derivatives and prediction markets.

CZ said U.S. policy toward crypto had “changed in the last year and a half or so,” pushing him to spend more time with U.S. builders, regulators and policymakers. He said the U.S. is now “leading in the world in terms of crypto policies,” citing market structure legislation, including the CLARITY Act.

The U.S. still lacks access to the deepest liquidity, he said, even as developers and crypto firms return after years of regulatory pressure.

“Many of the U.S. people left,” Zhao said. “They went to Abu Dhabi, they went to Hong Kong, Singapore. Many of the developers left, and then they’re now coming back.”

Zhao also framed BNB Chain as underexposed in the U.S. after years of limited domestic activity. He said the network now has a builder house in New York, a small San Francisco presence and more U.S. investment activity through YZi Labs.

YZi Labs, formerly Binance Labs, rebranded last year with Zhao taking a more active investment role. The firm later introduced a $1 billion fund for BNB Chain projects.

“BNB in particular has not had a lot of exposure in the U.S., … Other layer 1 blockchains have done much more marketing, community building, builder houses, etc., in the U.S.”

Zhao said U.S. institutions had limited access to BNB until recently, leaving the token behind other major cryptocurrencies in exchange-traded products and institutional distribution.

“The lack of access for institutions to BNB is actually an opportunity for BNB investors,” Zhao said. “When the institutions come in, that’s generally better for the token.”

Zhao also said AI agents will need crypto rails to transact with each other, arguing that blockchains are better suited than credit cards or bank rails for automated cross-border payments.

“Credit cards don’t have an API,” Zhao said. “The most native thing for the agent to use is obviously a blockchain.”

He added that BNB Chain should position itself as payments infrastructure for AI agents, though he said the market is still in its earliest stage. “BNB Chain should just be the money for agents,” he said.

XRP May Soar to $12 as Price Holds Cycle Bottom Zone for Months

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XRP May Soar to $12 as Price Holds Cycle Bottom Zone for Months

XRP (XRP) is testing a key long-term support level that has historically preceded major rebounds, according to a monthly chart shared by analyst MikybullCrypto.

Key takeaways:

  • XRP has jumped by roughly 30% from its February lows.
  • Multiple fractals suggest the price is bottoming out, supported by strong XRP ETF inflows.

XRP chart hints at rebound toward $12

Milkybull’s chart shows XRP trading inside a rising channel that has guided price action since 2014. XRP is now near the channel’s lower trendline around $1.30–$1.40, a zone that previously acted as a launchpad for large upside moves.

XRP/USD monthly chart. Source: TradingView/MilkybullCrypto

The analyst says XRP is “probably going to $12,” a level that roughly aligns with the channel’s midpoint.

Momentum indicators support the rebound thesis. XRP’s monthly relative strength index (RSI) has cooled toward a historical support area near 40–45, similar to levels that appeared before past rallies.

In a Thursday post, analyst JD pointed to the same RSI support zone as a potential “cycle bottom” signal for XRP.

His two-week chart shows XRP breaking out of a multi-year symmetrical triangle, then pulling back toward the breakout area.

XRP/USD two-week chart. Source: TradingView/JD

The chart’s projected green target zone aligns with the $8–$14 range, implying strong upside if XRP holds the retest zone.

The bullish outlooks follow XRP’s sharp rebound in recent weeks, up by about 30% from its February lows at around $1.11.

Related: XRP price copies 2025 chart fractal that last time sparked 66% gains

In the period, XRP has largely benefited from renewed risk sentiment led by the US–Iran ceasefire, as well as market-specific fundamentals.

These include Rakuten Wallet’s XRP integration, which expanded the token’s reach in Japan, and $81.6 million in April inflows into US spot XRP ETFs, their strongest monthly total of 2026.

In the first week of May, XRP ETFs have attracted $28.17 million in inflows already.

US XRP ETF net flows. Source: SoSoValue

XRP still risks 2022-style bear market repeat

However, the bullish XRP setup is not guaranteed. The bears will try to pull the price down below the channel support. This would invalidate the bullish structure and put XRP at risk of deeper losses.

XRP/USD monthly chart. Source: TradingView

The support overlaps closely with XRP’s 50-month exponential moving average (50-month EMA, the red line) near $1.33.

Losing this support cluster shifts focus toward the 100-month EMA (the purple line) near $0.93, implying a roughly 30% drop from current levels. A similar plunge occurred during the 2022 bear market.

This article is produced in accordance with Cointelegraph’s Editorial Policy and is intended for informational purposes only. It does not constitute investment advice or recommendations. All investments and trades carry risk; readers are encouraged to conduct independent research.

HSBC Rolls Out Privé World Legend Mastercard to Hong Kong Clients – Finsight.news

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HSBC Rolls Out Privé World Legend Mastercard to Hong Kong Clients – Finsight.news

HSBC Hong Kong has introduced the HSBC Privé World Legend Mastercard, which Mastercard says is the first World Legend Mastercard launched in Asia Pacific. The invitation-only card is aimed at HSBC Private Bank clients and will give HSBC Privé cardholders access to Mastercard’s most premium consumer credit tier.

The card combines HSBC Privé lifestyle benefits with The Mastercard Collection, a global suite of dining, entertainment and travel privileges. Existing HSBC Privé World Elite Mastercard cardholders will be upgraded to the World Legend Mastercard, unlocking additional benefits under the new programme.

HSBC said the product reflects rising demand among affluent consumers for experience-based rewards rather than traditional points or possessions. Mastercard cited research showing that 59% of higher-income consumers globally, including in Hong Kong, value experiences over possessions, while 40% of consumers in Hong Kong list overseas travel as a top personal goal.

Cardholders will receive travel, dining and entertainment privileges, including complimentary hotel-night programmes at more than 800 properties worldwide, companion travel benefits, airport lounge access, limousine service and travel insurance. Dining benefits include complimentary experiences at Michelin-starred and other acclaimed restaurants, along with priority reservations at selected restaurants in mainland China.

The card also offers access to HSBC-sponsored concerts and shows, priority ticket bookings for selected Live Nation events, and entry to selected private clubs and lounges, including Hong Kong Golf and Tennis Academy, HKGTA Town Club and Carlyle & Co.

Mastercard also plans to launch an exclusive dining club at Hong Kong International Airport later this year. HSBC Privé primary and supplementary cardholders will receive unlimited complimentary access per visit with up to three guests, with more such clubs planned at major airports globally.

Sunny Chow, HSBC Hong Kong’s head of cards and unsecured lending for retail banking and wealth, said the launch reflects a shift in premium banking toward more portable and personalised lifestyle benefits. Helena Chen, Mastercard’s senior vice president and general manager for Hong Kong and Macau, said the product responds to demand from affluent consumers for access, relevance and service.

The announcement did not specify annual fees or detailed eligibility requirements beyond the card being invitation-only for HSBC Private Bank clients.

DeFi is not dead, it’s going mainstream with AI agents, crypto executives agree

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DeFi is not dead, it’s going mainstream with AI agents, crypto executives agree

Miami — Decentralized Finance (DeFi) is not dying but instead moving deeper into the financial mainstream alongside the rise of AI agents, crypto executives participating in the Securing the Next Decade of Decentralized Finance panel Thursday at Consensus Miami 2026.

“Crypto is absolutely hurtling into the mainstream,” said Hunger Horsley, co-founder and CEO of Bitwise Asset Management. “Stablecoins, tokenized assets and DeFi are part of that.”

The panel came weeks after a series of DeFi North Korean hacker exploits, including Drift Protocol and Kelp DAO, which resulted in roughly $600 million in losses, drawing criticism over the sector’s security.

DeFi is “an inevitable future,” said Yoni Assia, co-founder and CEO of eToro, dismissing claims that DeFi is fading, much less dead. The technology underpinning lending protocols and smart contracts is already proving itself at scale, he argued.

“There’s $100 billion on lending markets or more,” Assia said. “The technology stack is mind-blowing, and it’s being battle-tested all the time.”

AI agents are speeding up interest

Much of the discussion focused on how AI agents are accelerating interest in crypto-native financial infrastructure.

Guy Wuollet, general partner at a16z Crypto, argued that autonomous AI systems will ultimately require financial rails that look “either literally DeFi or a lot like DeFi.”

“If we believe AI agents are going to be economically important actors, we need a financial system built for them,” Wuollet said.

Assia described experimenting with AI agents capable of independently opening wallets, bridging assets, researching trades and executing transactions across prediction markets and DeFi protocols. “DeFi and AI are both native to each other,” he added.

Horsley compared DeFi’s role for AI agents to the rise of APIs and open-source software in traditional internet infrastructure. “You could think of DeFi as enabling a lot of financial services for AI agents,” he said.

The executives also agreed that institutional attitudes toward crypto and DeFi are changing quickly.

Horsley said Bitwise, which manages roughly $15 billion in assets, is now receiving requests from regulated fintech firms and neobanks looking for compliant ways to offer DeFi-related products to customers.

“The institutions and corporates are arriving,” Horsley said. “They finally feel able to interact with the space.”

Wuollet said many large financial firms are initially approaching blockchain infrastructure less for crypto speculation and more for operational efficiency.

“Finance is going through a digital transformation,” he said. “Institutions want to replace their backend and core ledger with a blockchain.”

The panelists said the convergence between traditional finance, tokenized assets, DeFi and AI agents is likely to accelerate over the coming years as institutions become more comfortable operating onchain.

ETH may lose its biggest buyer as Bitmine mulls slowing down purchases

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ETH may lose its biggest buyer as Bitmine mulls slowing down purchases

Miami — Bitmine (BMNR), the largest Ethereum treasury firm, may slow the pace of its ether (ETH) accumulation as the firm is inching closer to reaching its accumulation goal, Chairman Tom Lee said Thursday at Consensus 2026 in Miami.

The company, which holds over 5.1 million ETH worth around $11.9 billion at current prices, originally expected it would take five years to accumulate 5% of the ETH supply, Lee said. Instead, the company held 4.29% as of this week, less than a year after launching its strategy.

“At our current buying pace of 100,000 ETH a week, we’re going to be there [at 5%] in like six weeks,” Lee said during a keynote presentation. “I think we’re deciding perhaps we want to accumulate at a somewhat slower pace.”

The comments mark a shift in tone for Bitmine, which has remained one of the few large digital asset treasuries still actively buying crypto while many rivals paused accumulation during the market downturn. Strategy (MSTR), the largest corporate bitcoin holder and another consistent crypto buyer over the past months, indicated this week it may sell bitcoin to cover dividend obligations, per Executive Chairman Michael Saylor’s suggestion.

Lee said Bitmine remains profitable through staking income and cash generation, reducing pressure to liquidate crypto holdings during volatile markets. About 85% of Bitmine’s ETH holdings are staked, generating annualized staking revenue exceeding $300 million, or roughly $1 million per day.

The firm is also evaluating other uses for capital, including a recently announced $4 billion share repurchase program and further expansion of MAVAN, its institutional staking platform launched in March. The service is currently staking about $14 billion in digital assets, including ETH, Solana (SOL), and Canton (CC), according to Lee.

Beyond Ethereum, Lee highlighted Bitmine’s investments tied to AI and consumer platforms, including Eightco Holdings (ORBS) and MrBeast’s Beast Industries. He described Eightco as one of the few publicly traded companies offering indirect exposure to OpenAI and Sam Altman’s World project.

Throughout his keynote, Lee reiterated his view that Ethereum stands to benefit from two major trends: the tokenization of financial assets and the rise of AI systems relying on public blockchains for payments and verification.

Read more: Bitcoin ending May above $76,000 would confirm new bull market, Tom Lee says

Why Bolt-On AI Is Not the Same as AI-Native Platforms

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Why Bolt-On AI Is Not the Same as AI-Native Platforms

By the time a deal surfaces in a banker-run auction, every competitor has already seen it. Finding targets before the process starts requires a platform built to understand business context, and that starts with architecture.

AI-native platforms are built with AI as a foundational component of the workflow engine. Bolt-on AI layers intelligence on top of systems designed before modern AI existed, operating on different assumptions about how data moves and how quickly a search needs to return results.

Grata, the leading private market intelligence platform, is one of the few examples where that architecture has been stress-tested at scale, and the broader research on enterprise AI explains why that distinction is valuable.

Most Enterprise AI is Still Not Producing Results

Enterprise AI research published in the past 18 months consistently points to the same structural issue: bolt-on implementations underperform AI-native ones, often by a significant margin. 

Boston Consulting Group surveyed 1,000 CxOs and senior executives across 59 countries in October 2024 and found 74% of companies still can’t show tangible value from their use of AI. Only 4% had developed what BCG called cutting-edge AI capabilities across functions. Companies in that cohort achieved 1.5 times higher revenue growth, 1.6 times greater shareholder returns, and 1.4 times higher returns on invested capital over three years compared to other companies.

BCG’s framework places 70% of the weight of AI success on people and processes, 20% on technology and data infrastructure, and only 10% on the AI algorithms themselves, meaning algorithmic sophistication alone rarely determines outcomes.

In June 2025, Gartner reached a similar conclusion and predicted that more than 40% of agentic AI projects would be canceled by the end of 2027. The main causes they cited were escalating costs, unclear business value, and inadequate risk controls. 

Gartner’s analysis pointed specifically to the technical complexity of integrating agents into legacy systems, which typically disrupts existing workflows and requires costly modifications that add up over time. The recommendation was to design workflows around agentic AI from the ground up rather than forcing new capabilities into existing infrastructure. 

Bolt-On AI Compounds the Debt It Sits On 

Legacy systems were built for predictable, batch-oriented data processing where a report runs overnight, and a platform query returns results in seconds. That architecture works well when data moves slowly and decisions have long lead times. AI workloads operate differently: generative and agentic systems need to process requests instantly and handle multiple tasks simultaneously.

Collecting data from nearly 5,000 technology professionals globally in 2025, Google Cloud’s DORA Report on the state of AI-assisted software development found AI amplifies whatever is already in the system. This means that a brittle architecture with bolt-on AI becomes more brittle over time, not less.

When AI is added to a system that was never designed to handle these demands, friction accumulates. Latency bottlenecks emerge at every handoff between the legacy layer and the AI service, API designs built for request-response patterns struggle with streaming AI workloads, and batch processing generates stale data that makes recommendations outdated by the time they surface.

The Data Problem That Bolt-On Can’t Fix

Data integration is one of the most persistent structural problems with bolt-on implementations. The 2025 MuleSoft Connectivity Benchmark Report found 95% of organizations face challenges integrating AI into existing processes, with 80% identifying data integration as the primary obstacle. The report also revealed the average enterprise manages 897 applications, and only 29% of those applications connect to each other. 

For dealmakers, the consequences are concrete. Private market intelligence requires pulling from dozens of sources. A bolt-on AI system sitting on top of a fragmented dataset can surface what’s in the connected tables, but synthesizing across unstructured data—the kind of reasoning that makes intelligence actionable—requires a system architected for that complexity from the outset.

What Changes When AI Isn’t an Afterthought

An AI-native platform is one where intelligence is embedded in every step of the process, not called on as a separate service. 

Nevin Raj, General Manager at Grata, describes two failure modes that private equity firms encounter when evaluating platforms. “You get two flavors of AI that can be problematic in today’s world,” Raj said. “AI-wannabes: think legacy databases that inject a chatbot layer on top of their data. It actually makes the UI less user-friendly and doesn’t add much value as a result, but the company thinks it tricks users into believing they are AI-native. LLM wrappers (often marketed as AI-native): these companies take ChatGPT, Claude, etc. and create unsupervised content that is AI slop. The quality is low but seems plausible at first glance.” 

What distinguishes a genuinely AI-native platform, Raj adds, is being “built on a scalable foundation of AI annotated by humans and quality-controlled to provide information that is accurate and trustworthy,” with features that “actually automate verticalized workflows without adding another chatbot that is rarely used.” 

A dealmaker on a genuinely AI-native platform doesn’t prompt the system separately or toggle between modules. The platform understands the professional context of the query and processes it through AI reasoning instead of keyword matching. Search results reflect business similarity, and screening narrows by attributes. The reasoning is embedded in the product’s core architecture.

Gartner estimated that in 2024, fewer than 1% of enterprise software applications included genuinely agentic AI capabilities. By 2028, analysts project this figure will reach 33%. 

Architecture Determines What AI Can Actually Do

The broader lesson that can be learned from the BCG, Gartner and MuleSoft research is consistent: a platform’s architecture determines how far AI can take it. Bolt-on implementations hit the ceiling of the systems they sit on. AI-native platforms are bounded by data quality and model sophistication, both of which improve over time.

BCG’s survey also found that the 4% of companies generating consistent value from AI treated it as an architectural decision they made early. The 74% still waiting for results are running AI on infrastructure never designed for it. For dealmakers competing on speed, that architectural distinction carries more weight as AI capabilities advance and the cost of retrofitting grows. 

FAQ

Q: How do the machine learning capabilities compare across platforms?

Answer: Algorithmic sophistication matters less than buyers typically expect. A platform’s data infrastructure, or how it’s structured, how frequently it updates, and how well sources are integrated, drives the quality of AI outputs far more than the model itself. A sophisticated algorithm operating on fragmented or siloed data will consistently underperform a simpler one built on a clean, unified foundation.

Q: How do the search capabilities differ between AI-powered and traditional platforms?

Answer: Traditional platforms match keywords against indexed fields, so results depend on how well a query maps to existing terminology. AI-powered platforms interpret queries as business intent, returning contextually relevant results even when the language doesn’t align precisely. For dealmakers, this means surfacing companies by what they actually do and not just how they describe themselves.

Q: How do modern deal sourcing platforms compare to traditional research methods?

Answer: AI-native platforms process thousands of companies simultaneously using business context such as sector fit, ownership structure, and leadership signals, replacing the manual filtering and analyst time that defined earlier approaches. Earlier-stage discovery is the practical result: deal teams reach conviction on targets before a formal process narrows the field and compresses timelines.

Q: Evaluating different options for private market intelligence—what should I consider?

Answer: Start with data infrastructure before evaluating features. How a platform structures, updates, and integrates its data determines what AI can actually deliver. Bolt-on AI built on fragmented systems exacerbates existing limitations rather than resolving them. Evaluate whether AI is embedded in core workflows or added as a separate layer. That distinction shows up in speed, accuracy, and daily usability.

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