The U.S. economy added 130,000 jobs in January.
Traders grew increasingly doubtful about a rate cut in March.
Gold prices climbed following the jobs report’s release.
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Prediction markets entered the mainstream in 2025, with a fourfold surge in annual trading volume as a handful of venues consolidated control over what is rapidly becoming an institutional-scale product, according to a new report from blockchain security firm CertiK.
The sector’s total volume rose from $15.8 billion in 2024 to $63.5 billion in 2025, the report said, with activity remaining elevated after the US election cycle and extending into January 2026.
That persistence matters because it suggests that election trading behaved less like a one-off spike and more like an acquisition event that drew new users into repeat behavior.
Notably, the week ending Jan. 18 set a record of about $6 billion in notional volume, the report said, reflecting how quickly prediction markets have moved from niche crypto product to a high-turnover trading venue.
However, CertiK’s central argument is that the next phase of growth is colliding with an integrity problem that has less to do with smart contract exploits than with the layers that govern onboarding, the “real” meaning of volume, and the mechanisms that determine who gets paid.
Three platforms now account for more than 95% of global prediction market volume, according to CertiK, and each is pursuing a different path to dominance.
Kalshi, which operates as a regulated venue in the US, is positioned as the compliance-first model. Polymarket has captured the largest share of crypto-native and international participation.
Meanwhile, Opinion is the fast-growing entrant, using ecosystem incentives to scale from effectively zero to roughly 30% market share in months, the report said.
That concentration turns operational issues into systemic ones.
A failure at any major venue is no longer a contained event; it is a market-wide trust shock that can spread across liquidity pools, data feeds, and user balances, particularly as brokers and mainstream distribution begin to treat prediction probabilities like a new class of information product.
CertiK points to a December 2025 incident involving Magic.link, Polymarket’s third-party authentication provider, as a preview of where the sector is most exposed.
Accounts using Web2-style login methods, such as email or social authentication, were compromised, placing funds in affected accounts at risk, while the on-chain settlement layer remained secure.
In CertiK’s framing, it was an identity failure, not a settlement failure, and it highlighted the tradeoff of “Web2.5” onboarding: a smoother user experience in exchange for centralized failure points.
The lesson is uncomfortable for an industry that markets itself on decentralization.
Prediction markets can support fully collateralized on-chain settlement while retaining the same third-party risks that plague conventional fintech, including authentication, account recovery, and platform-level access controls.
The report also draws a line between two concepts that are often conflated in crypto markets: trading volume as a proxy for adoption and probability outputs as a proxy for information.
According to the report, incentive programs can inflate activity without necessarily improving the quality of forecasting signals.
CertiK reported that wash trading remains widespread, citing research estimating that artificial volume reached as high as 60% on some platforms during peak airdrop-farming periods.
Such distortion can mislead outsiders, including prospective institutional users, regarding liquidity depth and organic participation.
Yet CertiK argues the more important question is whether the probabilities remain useful even when the tape is noisy.
In the report’s view, wash trading has inflated volume metrics but has not yet compromised price accuracy, and probability outputs have remained reliable for forecasting.
This creates tension for platforms seeking to graduate to mainstream finance; they may be able to position themselves as information utilities even if their activity metrics are partly fabricated by incentives.
It also raises a harder strategic decision for the market leaders.
If distribution and credibility depend on information quality, platforms may have to become less tolerant of behaviors that boost volume in the short term but undermine the optics and trust required for institutional capital.
Beneath the headline numbers, CertiK describes a structural rotation in how prediction market liquidity is executed.
Polygon retained “legacy dominance” through the November election cycle, the report said, but BNB Chain volume surged beginning in late 2025, correlating with Opinion’s accelerated incentive rollout.
By the week of Jan. 19, CertiK said BNB Chain activity had effectively flipped the historical hierarchy, capturing the plurality of weekly flows and pushing off-chain settlement into a secondary position, even as Kalshi posted record performance during NFL playoff trading.
That shift is more than a scoreboard for blockchain ecosystems. It changes who can participate, how trades are cleared, and which market structures are feasible.
CertiK notes that many on-chain venues are moving from automated market makers to central limit order books deployed directly on high-throughput chains, a design that produces tighter spreads and more familiar mechanics for professional traders.
In practice, it also moves prediction markets closer to an exchange-like microstructure, with the attendant risks of front-running and the MEV-style transaction-ordering disadvantages on public networks.
If there is a single tail risk that unifies the sector’s growth story, it is resolution, the step that converts probabilities into cash.
CertiK characterizes oracle manipulation as the primary technical attack vector because market-resolution mechanisms directly control fund distribution.
It also says ambiguous market definitions have already caused disputes across all major platforms throughout 2025, especially where political outcomes or contested official results create gray areas.
The report maps the main resolution models across the dominant platforms.
Polymarket is described as using UMA’s optimistic oracle, in which outcomes resolve automatically unless disputed within a challenge window, with disputes escalating to UMA token-holder votes.
Kalshi is framed as using centralized arbitration, with human arbiters resolving outcomes based on authoritative sources.
Opinion is described as relying on consensus oracles, where designated parties must agree on an outcome.
Each model carries a different trust assumption. Optimistic oracles can be fast for unambiguous outcomes but create edge-case vulnerability, including the risk that large token holders may influence votes in low-liquidity disputes.
Centralized arbitration is predictable but requires trusting the platform operator. Consensus oracles distribute authority but still depend on the incentives and integrity of the designated resolvers.
As prediction markets scale, those tradeoffs become harder to ignore.
The sector can tolerate occasional edge-case controversy when it is a crypto curiosity. However, becomes a governance crisis when market probabilities begin to appear in mainstream distribution channels or are used by institutions as inputs to risk decisions.
PHILADELPHIA, PA / ACCESS Newswire / February 11, 2026 / Datavault AI Inc. (NASDAQ:DVLT) (“Datavault AI” or the “Company”), a leader in data monetization, credentialing, digital engagement and real-world asset (RWA) tokenization technologies, announced that on Tuesday evening, Chief Executive Officer Nate Bradley hosted a private, invitation-only dinner at Mar-a-Lago for a select group of institutional investors, high-net-worth individuals, and senior government officials.
The private dinner followed successful, similar engagements earlier in the day at Mar-a-Lago, where Bradley met with a separate group of high-net-worth strategic investors. The strong reception from those discussions generated interest in a second, Datavault-hosted gathering, culminating in the private evening dinner.
Discussions during the engagements centered on Datavault AI’s execution roadmap, platform capabilities, and long-term positioning across data infrastructure, digital engagement, and monetization markets. The meetings reflected growing interest in the Company’s approach to verified data, tokenization frameworks, and scalable engagement technologies that bridge physical and digital environments.
The Mar-a-Lago engagements followed a period of elevated visibility and operational execution for Datavault AI. Earlier this month, the Company highlighted its high-impact activations during Super Bowl LX weekend, where its proprietary technologies were deployed in live environments to demonstrate authenticated audience engagement, immersive digital experiences, and real-world tokenization use cases. Those activations served as a real-world validation of the Company’s platforms and their ability to operate at scale.
In addition, Datavault AI recently issued a letter to stockholders outlining its 2025 accomplishments and outlook for 2026. In that update, the Company reported signing $49 million in tokenization and technology licensing agreements during the fourth quarter of 2025, contributing to record-setting revenue performance in fiscal 2025, with additional revenue impact extending into fiscal 2026. Datavault AI also reiterated expectations for at least $30 million in revenue for fiscal 2025, representing year-over-year growth of more than 1,000% compared to fiscal 2024. The Company expects to publish its fourth-quarter results on February 15, 2026.
“The level of engagement we experienced throughout the day, and the interest that carried into the evening, reflects a growing understanding of what Datavault AI has built and where we are headed,” said Nate Bradley, Chief Executive Officer of Datavault AI. “We are focused on execution and on delivering platforms that enable verifiable data, scalable engagement, and monetization in real-world environments. We appreciate the opportunity to engage directly with strategic investors and senior leaders as we continue advancing that mission.”
Datavault AI remains focused on expanding commercial deployments of its technologies, strengthening strategic partnerships, and advancing infrastructure that supports secure data processing, digital engagement, and real-world asset tokenization across multiple sectors.
About Datavault AIDatavault AI™ (NASDAQ:DVLT) is leading the way in AI driven data experiences, valuation and monetization of assets in the Web 3.0 environment. The Company’s cloud-based platform provides comprehensive solutions with a collaborative focus in its Acoustic Science and Data Science Divisions. Datavault AI’s Acoustic Science Division features WiSA®, ADIO® and Sumerian ® patented technologies and industry-first foundational spatial and multichannel wireless HD sound transmission technologies with IP covering audio timing, synchronization and multi-channel interference cancellation. The Data Science Division leverages the power of Web 3.0 and high-performance computing to provide solutions for experiential data perception, valuation and secure monetization. Datavault AI’s cloud-based platform provides comprehensive solutions serving multiple industries, including HPC software licensing for sports & entertainment, events & venues, biotech, education, fintech, real estate, healthcare, energy and more. The Information Data Exchange ® (IDE) enables Digital Twins, licensing of name, image and likeness (NIL) by securely attaching physical real-world objects to immutable metadata objects, fostering responsible AI with integrity. Datavault AI’s technology suite is completely customizable and offers AI and Machine Learning (ML) automation, third-party integration, detailed analytics and data, marketing automation and advertising monitoring. The Company is headquartered in Philadelphia, PA. Learn more about Datavault AI at http://www.dvlt.ai.
Forward-Looking StatementsThis press release contains “forward-looking statements” (within the meaning of the Private Securities Litigation Reform Act of 1995, as amended, and other securities laws) about Datavault AI Inc. (“Datavault AI,” the “Company,” “us,” “our,” or “we”) and our industry that involve risks and uncertainties. In some cases, you can identify forward-looking statements because they contain words, such as “may,” “might,” “will,” “shall,” “should,” “expects,” “plans,” “anticipates,” “could,” “intends,” “target,” “projects,” “contemplates,” “believes,” “estimates,” “predicts,” “potential,” “goal,” “objective,” “seeks,” “likely” or “continue” or the negative of these words or other similar terms or expressions that concern our expectations, strategy, plans or intentions. The absence of these words does not mean that a statement is not forward-looking. Such forward-looking statements, including, but not limited to, statements regarding future events, the timing, scope and expected benefits of Datavault AI’s audience engagement activities and outreach, and the anticipated benefits of Datavault AI’s commercial partnerships and/or collaborations, including, without limitation, with Sports Illustrated, are necessarily based upon estimates and assumptions that, while considered reasonable by the Company and its management, are inherently uncertain. Readers are cautioned not to place undue reliance on these and other forward-looking statements contained herein.
Actual results may differ materially from those indicated by these forward-looking statements as a result of various risks and uncertainties including, but not limited to, the following: risks related to the ability of Datavault AI to successfully implement its commercial partnerships, collaborations and/or strategies; changes in market demand for Datavault AI’s services and products; changes in economic, market, or regulatory conditions; risks relating to evolving regulatory frameworks applicable to tokenized assets; risks associated with technological development and integration; and other risks and uncertainties as more fully described in Datavault AI’s filings with the SEC, including its Annual Report on Form 10-K for the year ended December 31, 2024 and other filings that Datavault AI makes from time to time with the SEC, which are available on the SEC’s website at http://www.sec.gov, and could cause actual results to vary from expectations.
The forward-looking statements made in this press release relate only to events as of the date on which the statements are made. Datavault AI undertakes no obligation to update any forward-looking statements made in this press release to reflect events or circumstances after the date of this press release or to reflect new information or the occurrence of unanticipated events, except as required by law. Datavault AI may not actually achieve the plans, intentions or expectations disclosed in its forward-looking statements, and you should not place undue reliance on such forward-looking statements. Datavault AI’s forward-looking statements do not reflect the potential impact of any future acquisitions, mergers, dispositions, joint ventures or investments it may make.
Trademarks, Trade Names, Service Marks and CopyrightsWe own or have rights to use various trademarks, tradenames, service marks and copyrights, which are protected under applicable intellectual property laws. This press release also contains trademarks, tradenames, service marks and copyrights of other companies, which are, to our knowledge, the property of their respective owners. Solely for convenience, certain trademarks, tradenames, service marks and copyrights referred to in this press release may appear without the © , ® , and symbols, but such references are not intended to indicate, in any way, that we will not assert, to the fullest extent under applicable law, our rights or the rights of the applicable licensors to these trademarks, tradenames, service marks and copyrights. We do not intend our use or display of other parties’ trademarks, tradenames, service marks or copyrights to imply, and such use or display should not be construed to imply a relationship with, or endorsement or sponsorship of us by, these other parties.
Media Contact:[email protected]
SOURCE: Datavault AI Inc
Lawyers say unjust-enrichment law favours Bithumb, but outcomes may hinge on whether users knew, or should have known, the payouts were a mistake.
Prosecutors are expected to tread carefully, as the incident stemmed from an internal error rather than hacking or fraud.
The episode is intensifying scrutiny of Korean crypto exchanges’ internal controls, with regulators signaling tighter ownership and oversight rules ahead.
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IntellaStore® IV, APCON’s new network security appliance, offers the on‑box APCON Intelligent Processor (AIp) to run the user’s choice of security applications including APCON’s own ThreatGuard
WILSONVILLE, OREGON / ACCESS Newswire / February 10, 2026 / Deploying the IntellaStore® IV Network Security Appliance from APCON means easy installation, dedicated network packet capture, and a seamless workflow from traffic of interest to security and compliance tools. The release of APCON’s IntellaStore IV empowers network security engineers, business owners, office managers, and others to conveniently address network visibility (filtering, port tagging, etc.) as well as their vital security needs. With the APCON Intelligent Processor (AIp) running the server-side software, users are free to upload their own security and compliance tools, or enjoy the simplicity of ThreatGuard, APCON’s new network intrusion detection system.
The IntellaStore IV supports all the necessary functions to reveal network traffic characteristics for further processing. Some of these capabilities include:
Network VisibilityThe IntellaStore IV enables direct ingestion of high-throughput packet streams with onboard filtering and preprocessing before handoff to security and monitoring tools. Traffic filtering and aggregation ensure only relevant packets are recorded or forwarded, reducing downstream tool load. Analysts can produce precise, investigation-ready packet captures, cut through the noise, and eliminate tool overload while accelerating security and network insights.
Packet CaptureUsers can activate the recording of specific traffic to help identify the patterns and sources of regular content, and identify potential anomalies that need a closer look, using only the relevant data. Create filters, define custom criteria, and create event‑based triggers to initiate targeted packet captures.
On-Box StorageStore up to 32TB of data or additional tools directly on the IntellaStore IV security appliance. For more memory storage, offload capabilities (iSCSI) allow forwarding of filtered captures to other tools or external repositories when needed.
ThreatGuard is APCON’s world class network intrusion detection system software that can run on the AIp to provide deep packet inspection (DPI), rule-based detection, dashboards, and investigation workflows alongside packet capture. Each IntellaStore IV includes a 60-day free trial of ThreatGuard so teams can evaluate on their own network traffic.
The Value of a Network Security Appliance
Enterprises are grappling with the combined complexity of distributed environments, encrypted traffic, and restrictive budgets. Many organizations own a capable IDS (Intrusion Detection System) or SIEM (Security Information and Event Management) tool, but struggle to feed it clean, relevant traffic at scale; others can capture packets, but lack consistent workflows for analysis, storage, and sharing. IntellaStore IV combines these processes on one platform.
Built for real teams, real networks
IntellaStore IV is engineered to fit seamlessly into existing processes without the need to replace existing systems. Security teams can onboard quickly with pre‑bundled IDS rules, start with default dashboards, and incrementally add custom scripts and filters. NetOps teams can use traffic optimization features to deliver clean data streams to legacy tools. Incident responders can rely on consistent packet capture to maintain chain‑of‑custody and investigative integrity.
Faster investigations, measurable outcomes
With packet capture, detection, and analysis co‑located on the same hardware, analysts eliminate context switching across systems and minimize blind spots introduced by incomplete or delayed captures. The platform’s traffic optimization eliminates unnecessary processing in downstream tools for better performance.
Customer‑centric by design
The product design reflects three customer priorities:
Time to value: Deploy in hours, not weeks with usable defaults out of the box
Tool cost control: Filter traffic upstream of expensive security tools so they process only the flows that matter
Scalability: Run multiple software tools directly on the platform, turning the IntellaStore IV into an expandable, consolidated appliance.
Built for today, ready for tomorrow
As traffic volumes grow and architectures shift, teams need systems that scale without complexity. IntellaStore IV’s port density, storage capacity, and filtering options make it future‑ready, while its software ensures new rules, analytics, and dashboards can be added using the same platform. Whether organizations are modernizing a security strategy, supporting industrial networks, or improving branch visibility, the appliance adapts to the mission without imposing a new learning curve.
Availability and ordering
IntellaStore IV is available for order today from APCON and authorized partners. Sample SKUs include:
ACI‑4235‑IS4‑2: Appliance without ThreatGuard (comes with a 60-day trial of ThreatGuard)
ACI‑4235‑IS4‑2‑1: Appliance with ThreatGuard
ACI‑4235‑E24‑2: Blade only
ACI‑9510‑001: ThreatGuard security software
Please contact APCON or your preferred channel partner for pricing and configuration guidance.
About APCON, Inc. (APCON®)
APCON is a leading provider of network visibility and security solutions that help enterprises capture, optimize, and act on the data that matters. From high‑performance hardware to intuitive software, APCON technologies power troubleshooting, security operations, and compliance across complex environments. For more information, visit APCON’s Network Security Appliance page.
Media Contact
Email: [email protected]
Trademarks
APCON and IntellaStore are registered trademarks of APCON. All other trademarks are the property of their respective owners.
SOURCE: APCON, Inc.
Crypto majors flat on the day, BTC at $68,600
Tempo hires Farcaster cofounders, adds to their deep talent bench
Mr. Beast acquires teen-focused banking app Step
Jump Trading to earn equity stakes in Polymarket & Kalshi
MegaETH launches its mainnet, debuts “The Rabbit Hole” hub
📌 What Happened
🗣️ What They’re Saying
🧠 Why It Matters
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Crypto majors are mostly flat; BTC -1% at $68.6K; ETH -1% at $2,010; SOL even at $84; XRP even at ~$1.40
STABLE (+20%), H (+7%) and ASTER (+5%) led top movers
ZRO briefly jumped 20% before selling off, amidst speculation of launching its own chain
Farcaster co-founders Dan Romero and Varun Srinivasan joined Stripe’s Tempo, calling stablecoins a “generational opportunity”
Tether invested $150M in Gold.com for a ~12% stake; Tether’s gold stash now tops $23B (148+ tonnes), making it a top-30 global gold holder per Jefferies
MrBeast’s Beast Industries acquired Step, a teen-focused banking app backed by Stephen Curry and Justin Timberlake
Logan Paul faked a $1 million Polymarket bet during the Super Bowl
Polymarket sued Massachusetts in federal court, arguing only the CFTC has jurisdiction over prediction markets; meanwhile Kalshi sports markets face a 30-day geofence deadline
It’s a big week ahead for macro: Delayed nonfarm payrolls Wednesday, Coinbase earnings Thursday, Robinhood earnings Friday, and CPI on Friday
Corporate Treasuries & ETFs
The BTC ETFs saw another $145M in net inflows on Monday while the ETH ETFs saw $57M
Strategy bought 1,142 BTC for $90M at avg $78,815 per coin; total holdings now 714,644 BTC (~3.4% of supply) at a $76,056 avg cost basis
BitMine (BMNR) continued loading up on ETH during the crash, adding another
Meme Coin Tracker
Meme majors were mostly flat; DOGE -1%, SHIB -1%, PEPE -1%, TRUMP -1%, FARTCOIN +1%
BNKR rallied another 30% after deploying its new launchpad with better fees for agents and more revenue streams for the protocol
GIRAFFES was the runner of the night on Solana, jumping 96x to $4M; MOLTEN was the top mover on Base, up 17x to $3.5M
Jump Trading will earn equity stakes in both Polymarket and Kalshi in exchange for providing market-making liquidity
MegaETH launched its mainnet and ecosystem hub “The Rabbit Hole”
BackPack Exchange is reportedly raising $50M at a $1B valuation ahead of its expected TGE
ENS Labs scrapped its Namechain L2, will deploy ENSv2 exclusively on Ethereum mainnet
Kinetiq announced the launch of perps dot fun, allowing anyone to launch a perps market
NFT leaders were mostly red; Punks even at 29.9 ETH, Pudgy -3% at 4.4 ETH, BAYC -3% at 6.2 ETH; Hypurr’s -3% at 445 HYPE
Cyberkongz (+10%) and Kodas (+10%) led notable movers
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XRP supply in 2026 hinges on how much escrowed XRP Ripple chooses to distribute after monthly unlocks.
The process is capped by the ledger, while market impact still depends on net flows and demand.
According to the XRP Ledger, total supply is fixed at 100 billion XRP, while Ripple’s on-ledger escrow system sets an upper bound of 1 billion XRP that can become available each month.
Unused amounts can be re-escrowed. For background, see XRPL’s “What is XRP?”, the total supply FAQ, and the XRPL escrow explainer.
XRP’s maximum supply is capped at 100 billion XRP, and 100 billion XRP existed at creation.Ripple locked 55 billion XRP into on-ledger escrows, designed to add supply predictability.The escrow design releases up to 1 billion XRP per month as an upper limit, and leftovers can be re-escrowed into later months.XRPL transaction fees are burned, with a minimum fee of 10 drops (0.00001 XRP) that can rise under load.“Unlock” is not the same as “distribution,” and partial whale-tracker samples are not enough to compute a monthly net.
Full-month unlock and re-lock totals before estimating net new supply (avoid partial samples).Fee regime changes during congestion since fees are burned and can escalate.Escrow share versus circulating share from primary explorers or APIs at publish time (see XRPSCAN facts endpoints).Changes in market structure that alter who holds XRP and how exposure is hedged (see Ripple’s Q1 2025 XRP Markets Report).
XRP’s supply constraints start with a hard cap.
The XRP Ledger documentation describes XRP as capped at 100 billion, and the ledger began with 100 billion XRP created at inception.
The moving variable is not issuance; it is location and availability.
XRP can sit in escrow, in circulating balances, or in concentrated holdings that may trade infrequently.
“Circulating supply” is a headline number.
“Effective float” can be modeled as the portion that is practically available to trade at the margin (an editorial construct, not an XRPL-defined metric).
Forward-looking frame: In a month where the escrow ceiling is 1 billion XRP, the market outcome still depends on what fraction is distributed and where it lands, such as exchanges, market makers, or longer-term holders.
The escrow design itself notes that the amount of XRP actually released into circulation will likely be much less than the monthly maximum.
Ripple locked 55 billion XRP into a series of on-ledger escrows.
The structure was described as adding predictability to supply in Ripple’s 2017 escrow announcement.
The ledger-side mechanics matter for forward estimates.
The escrow design releases a total of 1 billion XRP per month across independent escrows.
It is explicitly described as an upper limit on how much XRP can become available from escrow in a given month.
Any unused XRP can be placed into a new escrow to be released later, preserving the ceiling while shifting timing.
Early February 2026 provided examples of these mechanics in public whale-tracking logs.
Whale Alert recorded 400 million XRP and 100 million XRP “unlocked at Ripple” on Feb. 1, 2026.
It then recorded 300 million XRP and 400 million XRP “locked at Ripple” on Feb. 2.
Escrow unlocks define availability.
Distribution defines impact.
Ripple’s escrow announcement also described the mechanism as creating “certainty of XRP supply” and explained that unused XRP can be returned to escrow at the back of the schedule.
For a forward-looking model, the relevant quantity is net potential market supply addition.
Let U be monthly unlocked (bounded by U ≤ 1B).Let R be re-escrowed that month.Net potential addition ≈ U − R, before considering whether distributed XRP lands on exchanges or in longer-horizon holdings (editorial model).
A scenario range can be used as a watch framework rather than a forecast:
0–200M XRP net in a conservative distribution month (modeled).200M–600M XRP net in a mid distribution month (modeled).600M–1B XRP net in a high distribution month (modeled).
Macro plumbing can matter more than the ceiling.
Ripple’s Q1 2025 report describes market structure themes such as ETPs and futures participation, which can change how exposure is held and hedged even when the escrow rules stay constant.
Related CryptoSlate context: XRP ETFs and flow plumbing.
XRP burn exists, but it is tied to network operation rather than discretionary monetary policy.
According to XRPL’s transaction cost documentation, each transaction destroys a small amount of XRP as a fee, and the fee is “irrevocably destroyed” and not paid to any party.
The current minimum transaction cost is 0.00001 XRP (10 drops).
The documentation also notes the fee can increase during periods of higher load.
A practical burn estimator for monitoring is:
Burned XRP over a period ≈ validated transaction count × average fee (in XRP) (editorial math based on XRPL fee rules).
A stress test belongs in the dashboard.
Fee escalation can raise burn temporarily during load events, because the fee mechanism also serves as spam and DoS protection.
Related CryptoSlate context: XRPL activity tracking.
XRP’s cap and escrow ceiling do not remove liquidity concentration risk.
A trading-focused “effective float” lens can treat balances that rarely move, escrowed holdings, and operational treasuries as less available than exchange-linked inventory.
Keep clear that “effective float” is an editorial model rather than an XRPL statistic.
For readers modeling quarter-ahead volatility, the relevant question becomes how often large balances move relative to exchange depth.
Whale-tracker samples can help spot events, while month-level conclusions still require complete enumerations and primary ledger verification.
Related CryptoSlate context: exchange inventory framing.
Historical supply snapshots can anchor context, but “current” values should be refreshed from primary sources at publish time.
XRPSCAN in September 2025 listed 14,202,427 XRP burned, 35,308,793,467 XRP in escrow, and 64,662,801,679 XRP circulating.
MetricHow to compute or sourceWhy it matters this quarterSourceMax supplyFixed cap at 100BConstrains long-run dilution narrativesXRPL Learning PortalMonthly escrow availability ceilingUp to 1B XRP per month unlockable from escrowSets upper bound for potential distributionXRPL.org escrow explainerMonthly net potential supply addition (modeled)U − R, after enumerating all unlock and re-lock eventsTracks marginal supply pressure more directly than unlock headlinesXRPL.org escrow explainerBurned XRP via feesTx count × average fee (fees are destroyed)Separates fee spikes from structural tokenomics claimsXRPL.org transaction costEscrow, circulating, burned snapshotsQuery primary explorers or XRPSCAN facts endpoint at publish time; September 2025 snapshot is secondaryPrevents stale “current supply” statementsXRPSCAN API docs; Times Tabloid relay
Claims that XRP was “minted” during an escrow unlock, since total supply is capped at 100 billion and unlocks change availability, not issuance.Month “net distribution” numbers derived from a few whale alerts without full-month transaction enumeration.“Deflationary XRP” claims that omit fee levels and transaction counts, since burn is tied to fees and can vary under load.“Circulating supply equals tradable supply” assumptions that ignore custody concentration and escrow constraints (modeling risk).
Weekly: compile escrow unlock and re-lock transactions for the full period before estimating U, R, and (U−R).Weekly: track average fees and fee spikes, since fees are burned and can escalate during load.Monthly: refresh escrow, circulating, and burned totals from a primary explorer or XRPSCAN facts endpoints before publishing “current” figures.Quarterly: review market structure notes that affect how XRP exposure is held and hedged, since these factors can alter flow behavior without changing escrow mechanics.
XRP’s supply ceiling is defined on-ledger.
The next quarter’s tradable supply depends on measured net escrow flows, fee conditions, and where distributed balances settle.
Related CryptoSlate context: XRPL DEX liquidity and XRPL RWA growth.
For price context alongside supply mechanics, track CryptoSlate’s XRP page.
IT Asset Management (ITAM) Software Market
Emerging trends, investment hotspots, and strategic intelligence poised to reshape the global IT Asset Management (ITAM) Software Market through 2033
Our flagship IT Asset Management (ITAM) Software Market research report delivers authoritative, data-driven insights for 2026-2033, featuring in-depth analyses of market trends, segment performance, competitive positioning, and strategic growth pathways. The study provides actionable intelligence on shifting industry dynamics, emerging investment prospects, competitive developments, and the key segments likely to shape the market’s future.
Key Highlights:
• Detailed coverage across market drivers, restraints and investment hotspots to support strategic decision-making.• Full segmentation by type and application and regional market breakdown – enabling readers to identify high-opportunity segments and adapt strategies accordingly.
Designed for industry executives, investors, policymakers and new market entrants, this report equips stakeholders to gauge market size, forecast revenue, analyse production and consumption trends, evaluate pricing and profit margins, and benchmark competitive performance. Built on rigorous primary and secondary research, the study features company profiling, pricing dynamics, production cost analysis, SWOT and Porter’s Five Forces review, and robust forecasting to help users make informed business decisions.
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Top Companies Covered:
• Altaro Software• Atlassian• BMC Software Inc.• Cherwell Software• Deloitte• Flexera Software LLC• Hewlett Packard Enterprise Development LP• IBM Corporation• JustSAMIt• Microsoft Corporation• Oracle Corp.• Samanage• Scalable Software• ServiceNow Inc.• Snow Software
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Market Segmentation –
This report has explored the key segments: The lucrativeness and growth potential have been looked into by the industry experts in this report. This report also provides revenue forecast data by type and by application segments based on value for the period 2026-2033.
• By Type: Hardware and Software• By Deployment Type: Cloud and On-premise• By End-use Industry: IT and Telecom, BFSI, Healthcare, Retail, Manufacturing, Government, and Others
Geographical Landscape of the Market:
The global IT Asset Management (ITAM) Software Market research report offers thorough regional and country-level analysis, spotlighting market share, demand variation, regulatory differences, emerging profit pockets and growth drivers across:
• North America (USA, Canada, Mexico)• Europe (Germany, UK, France, Italy, Russia, Spain, Rest of Europe)• Asia-Pacific (China, India, Japan, Singapore, Australia, NZ, Rest of APAC)• South America (Brazil, Argentina, Rest of SA)• Middle East & Africa (Turkey, Saudi Arabia, Iran, UAE, Africa, Rest of MEA)
Why Purchase This Report:
➥ Gain strategic insight into key competitors and sharpen your sales & marketing tactics.➥ Identify emerging players and market entrants with breakthrough products.➥ Recognise potential clients or partners in your target market to boost outreach.➥ Develop informed tactical plans based on what top companies are prioritising.➥ Support M&A decisions with in-depth market intelligence and player performance data.➥ Explore licensing and partnership opportunities with precision and confidence.➥ Enhance internal presentations and client deliverables with high-quality validated data and insights.
Exclusive Offer: Buy the full report now at a special launch discount (UP TO 40% OFF)- Visit: https://www.coherentmarketinsights.com/offernew/buy-now/3768
➤ FAQ’s
Q.1 What are the main factors influencing the IT Asset Management (ITAM) Software Market?Q.2 Which companies are the major sources in this industry?Q.3 What are the market’s opportunities, risks, and general structure?Q.4 Which of the top companies compare in terms of sales, revenue, and prices?Q.5 How are market types and applications and deals, revenue, and value explored?Q.6 What does a business area’s assessment of agreements, income, and value implicate?
Author of this marketing PR:
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Research published on the Harvard Business Review found that AI is accelerating work, not reducing it.
Productivity gains are morphing into burnout and workload creep.
The real shift isn’t job loss—it’s work intensification and reorganization.
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Lucid Engines introduced AI and GEO Visibility platforms to help optimize the visibility of digital-first brands for AI search enginesLucid Engine recently launched its AI and GEO (Generative Engine Optimization) platform to help digital-first companies get noticed by AI engines. The present era is evolving at a fast rate, and the majority of people rely on generative AI to get answers to their queries, with ChatGPT being the most preferred choice. This makes it essential for all digital companies and brands to work on their visibility to get cited by the AI for recommendations.
Traditional search engines have dominated the internet for the longest time to show websites and companies whenever a user asks for a recommendation, but generative AI has taken over it, and its way of explaining how a particular brand works for the user has been a revolution. To help digital brands get cited and seen by the generative AI, Lucid Engine is helping them by working and focusing on how AI sees them, improving their presence, and making them get included in AI recommendations, summaries, and AI answers.
The services offered by Lucid Engine go far beyond helping with being included by the AI in their responses and recommendations, and they also offer companies the ability to audit, measure, and optimize their visibility score in all leading AI responses like ChatGPT, Gemini, and Perplexity. The AI visibility platform [https://lucidengine.tech/] helps brands understand how these generative AI engines work at the core, the factors on which they choose a website to display in their recommendation, discover which sources and pages are being cited by them, and how their competitors are perceived.
The platform educates on how generative AI engines work, shows recommendations based on web experience, and not keywords. If AI picks your brand, it helps you discover which words are being shown for your brand and what is causing you to be blocked for them to view you. The platform introduced by Lucid Engines is suitable for Saas companies, e-commerce brands, and companies that rely on online visibility for their growth and success.
With the launch of the platform, a spokesperson from Lucid Engine said, “We intend to help every single of the digital-first companies to break the code of generative AI and GEO optimization platform [https://lucidengine.tech/]. As the majority of the population is shifting to them to get even the smallest of their queries answered, we are helping brands to get optimized and become visible by these generative AI search engines.”
Though many brands have already adapted to the rising trend of AI, the majority are still unaware of how it has started dominating the digital space. This sudden shift has created a gap for companies that are still relying heavily on traditional SEO for their visibility. Lucid Engine launched its service to address this very gap while creating an awareness about generative AI and GEO and helping these companies understand how everything works and ways to become visible in the responses generated by AI.Media ContactCompany Name: Lucid EngineContact Person: Marine DepoorterEmail: Send Email [http://www.universalpressrelease.com/?pr=lucid-engine-launches-ai-and-geo-visibility-platform-to-empower-digitalfirst-brands]Address:7 Av. des Monts ClairsCity: 92700 ColombesCountry: FranceWebsite: https://lucidengine.tech
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