In the rapidly evolving world of Web3, DAPPOS stands out as the pioneering Web3 AI Operating System. Designed to intelligently research, plan, and execute crypto-related tasks, DAPPOS bridges the gap between complex blockchain interactions and intuitive user experiences. At its core are two foundational layers: the Intelligence Layer and the Execution Layer, which together create a seamless ecosystem for users ranging from retail traders to enterprise teams.

Let’s start with a quick recap of these key components.The Intelligence Layer is powered by the Multi-Agent Framework (MAF), a scalable orchestration system featuring 300–400 specialized vertical agents and over 200 integrated tools. This setup enables domain-specific reasoning across diverse Web3 scenarios, from quantitative trading strategies to market sentiment analysis. Agents collaborate autonomously through a stateful graph backbone, routing tasks deterministically to subgraphs like Search (for real-time data aggregation), DeFi (for strategy generation and risk validation), and Opportunity (for alpha detection via on-chain and social signals).

Complementing MAF is the Bubble Engine, a continuous reinforcement learning (RL) system tailored for Web3. It ingests live insights from sources like X (formerly Twitter) and Binance Square, using contextual Retrieval-Augmented Generation (RAG) for provenance-first data handling and compound memory to blend durable knowledge with episodic learnings. This ensures adaptive intelligence that evolves with the ecosystem, outperforming generic AIs like ChatGPT or Perplexity in handling Web3 nuances, such as meme coin hype or deceptive practices.

On the other side, the Execution Layer brings these insights to life through the Intent Execution Network — a tested infrastructure with over 5 million users and 12 million transactions. It transforms AI-generated intents into efficient on-chain actions while minimizing risks through off-chain validation and on-chain dispute resolution.

Together, these layers create a foundation upon which all of DAPPOS’s applications are built — including the upcoming DAPPOS Membership, a one-stop subscription that unlocks a full suite of AI-powered Web3 solutions.

Introducing the DAPPOS Membership: All-in-One Solution for Your AI-related Demands in Web3

At the heart of DAPPOS’s business model is our upcoming subscription-based approach, inspired by successful AI platforms but optimized for Web3’s unique demands. The DAPPOS membership serves as a comprehensive subscription package, where a single membership unlocks an expansive suite of AI tools focused on solving a wide array of Web3 challenges through specialized applications.

Here’s a closer look at these Web3-focused applications unlocked with your membership:

• Translation
• Fact Check
• Writing Assistant
• Image Studio
• Video Generator
• Deep Research
• Legal Advisor
• Instant dApp Creator
• Alpha Opportunity Detector
• DApp Interaction Assistant
• Meme Coin Generator
• Marketing Campaign Planner
• …

To illustrate how these AI tools are tailored for Web3, consider our Fact Check application, which goes beyond generic verification by cross-referencing articles, posts, and claims with real-time on-chain data, social signals from platforms like X, and other blockchain-specific sources. This can help users detect hype-driven misinformation in meme coins or DeFi projects, such as verifying token partnerships or spotting bot-manipulated trends. Similarly, the Translation tool is Web3-optimized to handle nuanced blockchain terminology and hyping meme concepts, ensuring users can get the accurate meaning of foreign characters in the Web3 contexts.

Looking Ahead: Expanding Horizons with Partners

As DAPPOS grows, we’re excited to open our ecosystem to external partners, inviting developers, protocols, and enterprises to collaborate on enriching the DAPPOS membership. Through open APIs, partners can contribute custom products — such as specialized oracles for niche data feeds and AI DePIN — accelerating innovation and creating shared value. This collaborative model will position DAPPOS as your one-stop destination for all AI-related needs, where a single platform seamlessly integrates intelligence, execution, and expandable applications to handle everything without ever leaving the ecosystem.

While our core focus remains Web3, the DAPPOS membership will also extend features to Web2 domains for hybrid users. For industries like news, tourism, and health, we will offer customized OS overlays that enhance traditional workflows — such as fact-checking tools for information verification, anti-censorship tools for secure content sharing, or privacy-focused data vaults that resist centralized tracking. These add-ons provide a bridge for mainstream adoption, ensuring users can operate in censored environments with encrypted, AI-optimized experiences.

We’re just getting started at DAPPOS. Whether you’re a curious explorer, a strategic trader, or a visionary builder, the DAPPOS membership invites you to unlock Web3’s full potential.

In the relentless flux of Web3 — where tokens pump on a tweet, protocols pivot overnight, and alpha hides in on-chain whispers — static knowledge isn’t just outdated; it’s obsolete. That’s why, at DAPPOS, we’ve engineered the Bubble Engine as the adaptive core of our Web3 AI Operating System. It’s not another layer of intelligence; it’s the mechanism that keeps the entire system alive, learning, and evolving in real time. Drawing from our experiences building a platform that’s already processed millions of intents, we’ve designed Bubble to ingest the ecosystem’s chaos and turn it into reliable, actionable insights — tackling AI hallucinations head-on through rigorous, consensus-driven fact-checking.

What Makes Bubble Unique: Continuous RL Meets Web3 Realities

At its foundation, the Bubble Engine is a reinforcement learning (RL) powerhouse optimized for Web3’s unique demands. Unlike generic AI models that rely on frozen training data, Bubble continuously refines itself by pulling in live signals from sources like X (formerly Twitter) and Binance Square. Think of it as an ever-hungry learner: it scans for emerging trends, such as a meme coin’s viral collaboration or a DeFi protocol’s subtle upgrade, and integrates them into its decision-making fabric.

But raw ingestion isn’t enough in a space rife with noise — and where AI hallucinations can lead to costly errors, like misreading market signals or fabricating protocol risks. Bubble employs Contextual Retrieval-Augmented Generation (RAG) to aggregate data with provenance in mind — prioritizing traceable, verifiable sources. This hybrid system blends semantic search for conceptual matches with keyword precision for exact hits, then deduplicates and reranks results using cross-encoders. For every output, it locks in citations, ensuring users can trace back to the origin. If evidence is thin, it falls back gracefully, flagging uncertainties rather than fabricating confidence.

To illustrate, consider a user querying a potential arbitrage opportunity across chains. Bubble doesn’t just recall static APY tables; it fetches real-time KOL strategies and on-chain metrics, cross-verifies against multiple APIs (like those from Dune Analytics or Chainlink oracles), and simulates outcomes. This fact-checking loop — built into the RL process — rewards accurate predictions by weighting verified data higher in future iterations, much like how a trader hones intuition through market feedback. Here, complex queries are decomposed into atomic claims (e.g., “Is this liquidity pool solvent?” or “Does this signal match historical patterns?”), then routed through a multi-source consensus mechanism to detect and mitigate hallucinations — ensuring outputs are not just plausible, but provably grounded.

Compound Memory: Blending Timeless Truths with Fresh Alpha

One of Bubble’s standout innovations is Compound Memory, which fuses durable Web3 fundamentals — like core blockchain mechanics or DeFi primitives — with episodic learnings from recent events. This isn’t passive storage; it’s an active evolution. Verified facts (e.g., a protocol’s audited smart contract details) form the bedrock, while transient insights (e.g., a token’s liquidity spike tied to a celebrity endorsement) layer on top, decaying or amplifying based on ongoing validation.

In practice, this means Bubble adapts without forgetting. For instance, when analyzing a new NFT project’s viability, it draws on historical patterns from collections like Bored Apes or Pudgy Penguins — fact-checked against immutable on-chain records — while incorporating fresh sentiment from X threads. If a signal smells off, like bot-inflated engagement, Bubble’s misinformation filters kick in: cross-referencing wallet clusters via tools like Nansen or Etherscan, and community flags to weed out pumps.

To enhance reliability, Bubble employs consensus among its specialized agents — running parallel validations across RL-tuned models to flag hallucinations, where a single model’s fabricated claim (e.g., a nonexistent partnership) gets overridden by collective evidence, reducing error rates in high-stakes Web3 advice.

User-Powered Evolution: The Bubble Task Platform

What truly sets Bubble apart is its collaborative edge. Through the Bubble task platform, users aren’t just consumers — they’re contributors. Post a tweet with a novel insight (say, a hidden exchange listing leak), and if it passes verification, it will be fed into the engine. This Web3 incentive model rewards high-quality submissions, accelerating adaptation.

This mirrors how open-source communities debug code: collective input, rigorous checks. Bubble’s RL loop treats each verified bubble as a training signal, fine-tuning weights to prioritize Web3-native cues over generic noise. The result? A system that outperforms tools like Perplexity in contextual depth, as it doesn’t just search — it evolves with the ecosystem’s pulse, using claim decomposition to break down user inputs into verifiable statements before integration, preventing hallucinated knowledge from polluting the memory pool.

Building Trust Through Verification

Developing Bubble wasn’t without hurdles. Early iterations grappled with Web3’s deception density — fake airdrops, rug-pull signals disguised as partnerships. We learned that unfiltered RL could amplify biases, so we embedded fact-check logic at every stage: mandatory cross-verification against on-chain ground truth, anomaly detection for suspicious patterns (e.g., unnatural volume surges), and episodic memory purges for debunked info.

A key principle emerged: treat misinformation not as an edge case, but as the default — particularly in high-stakes scenarios (e.g., financial or legal advice) where hallucinations can occur in 30–50% of outputs. By design, Bubble queries multiple stakeholders — exchanges, DAOs, independent analysts — and assigns adaptive scores. For example, a bullish signal from a single X account gets downweighted until corroborated by transaction data or diverse sources. This rigor involves decomposing outputs into discrete claims, routing them through a verifier network for consensus (leveraging RL rewards for accurate validators), and generating provenance certificates for transparency. In our tests, this has slashed hallucination risks, turning potential pitfalls into strengths — ensuring Bubble delivers institutional-grade trust without relying on centralized oversight or model retraining.

A Decentralized Intelligence Horizon

Bubble Engine is already transforming how DAPPOS users navigate Web3, from crafting trading strategies to spotting opportunities in real time. But we’re just scratching the surface. Future enhancements include multimodal RAG for ingesting images, videos, and audio (think analyzing NFT art trends or protocol demo clips), and graph-based extensions to map entity relationships across chains — potentially integrating deeper, decentralized fact-checking.

As we move forward, Bubble will deepen its role in the Multi-Agent Framework, enabling even more composable autonomy. Imagine users bubbling custom subgraphs for niche workflows, or the engine predicting market shifts via RL simulations backed by multi-model consensus. Ultimately, Bubble isn’t static tech — it’s the beating heart of a Web3 AI OS that’s collaborative, verifiable, and endlessly adaptive, empowering anyone to thrive in crypto’s wild frontier.

— Written by the DAPPOS Team, September 18th, 2025

In the heart of DAPPOS’s Web3 AI Operating System lies a system designed not just to think, but to orchestrate intelligence at scale. We’ve built the Multi-Agent Framework (MAF) as the orchestration engine that powers our Intelligence Layer, coordinating 300–400 specialized vertical agents and over 200 integrated tools to handle everything from quantitative trading strategies to real-time market alpha detection. But MAF isn’t about sheer numbers — it’s about engineering a framework that ensures explainable, reliable autonomy in Web3’s chaotic environment. Today, we’re pulling back the curtain on how we optimized MAF for composable workflows, drawing from hard-won lessons in agentic design.

The Stateful Graph Backbone: Predictability in a Volatile World

From the outset, we knew Web3 demands more than ad-hoc agent swarms. Volatility in markets, protocols, and data sources means AI can’t afford black-box decisions. That’s why MAF’s foundation is the StateGraph — a stateful schema that acts as the single source of truth for the entire system.

At its core, StateGraph tracks a typed collection of variables: messages for agent communication, plans for workflow orchestration, artifacts like generated data or models, UI interrupts for human oversight, final outputs, error states for recovery, and flags for conditional branching. These aren’t just passive records; they’re passed immutably across nodes, enabling deterministic routing that minimizes variability.

In practice, this backbone starts with a main controller node — the task_planner — that parses user intents (e.g., “Optimize my DeFi yield”) and routes them to specialized subgraphs. Controller nodes evaluate the state at each step, updating variables and directing flow without relying on probabilistic guesswork.

Subgraphs: Modular Powerhouses for Domain Expertise

MAF’s real strength emerges in its subgraphs — self-contained modules that handle specific Web3 domains while leveraging the shared StateGraph for seamless integration. This modular design lets us scale intelligence without monolithic overhauls, much like microservices in traditional software.

Take the Search Subgraph as an example: It’s an agentic loop optimized for depth and breadth. The search_controller_node dynamically parallelizes agents — e.g., invoking google_search_agent for off-chain data alongside twitter_search_agent for sentiment — then merges outputs in a coordinator node. An enhanced review loop iterates refinements, filtering for relevance via criteria like source diversity or confidence scores, before a summarize_node outputs cited, frontend-ready responses.

We’ve engineered efficiency here by balancing parallelism: too many agents spike costs, so we use dynamic budgeting based on query complexity. For a meme coin analysis, it might spin up 5–10 agents in parallel, cross-referencing social spikes with on-chain liquidity, all while keeping token consumption under 50K per loop.

The DeFi Subgraph focuses on tool-augmented execution. It kicks off with fetch_market_data to pull real-time blockchain metrics, feeds into strategy_generator for plan creation (e.g., recursive lending loops), and validates via simulation nodes that assess risks like impermanent loss. Interrupts allow user approvals, closing the loop with institutional-grade safety.

Meanwhile, the Opportunity Subgraph scans for alpha: opportunity_search_node detects signals, validates with market data, and synthesizes recommendations — like flagging an emerging protocol upgrade tied to exchange listings.

Across subgraphs, we’ve optimized for composability: outputs from one (e.g., search insights) feed as artifacts into another, enabling chained workflows without data loss. This graph-based approach has boosted generalization — MAF handles 40% more task types than our initial prototypes, with fewer errors in edge cases like volatile meme markets.

Advanced Optimizations

Building on the backbone and subgraphs, we’ve layered in features that push MAF toward production-grade autonomy.

Multi-Agent Search stands out for collaborative efficiency. In the search subgraph, controllers select agents based on intent, executing in parallel for speed. An enhanced review cycle refines iteratively, and we’ve tuned it with episodic memory to recall past refinements — reducing redundant queries by 2.5x. For Web3, this means spotting subtle signals, like a token’s hidden Binance ties, faster than generic AIs.

Tool-Augmented Plan Generation integrates our 200+ tools directly into DeFi and opportunity flows. Validators cross-check against risk params, with optional HCI interrupts for oversight. We’ve optimized tool calls by masking irrelevant ones via state-aware logit biasing, preventing “tool overload” that plagued early versions — where agents would hallucinate inefficient paths.

Streaming and Interrupts add interactivity: Long tasks stream progress messages, and if data’s incomplete, MAF pauses to query users. This human-in-the-loop design cut failure rates in beta tests, turning potential dead-ends into refined outcomes.

Lessons from the Trenches: Engineering for Web3 Realities

Iterating on MAF taught us a few hard truths. First, determinism beats flexibility in high-stakes domains — hence our shift to controller-driven routing over pure LLM autonomy. Second, cache efficiency is king: by stabilizing prefixes and using append-only states, we’ve slashed costs in inference-heavy loops. Third, modularity scales better than monoliths; subgraphs let us hot-swap agents without system-wide redeployments.

These optimizations aren’t theoretical — they’re battle-tested in handling real Web3 chaos, from DeFi simulations to alpha hunts.

— Written by the DAPPOS Team, September 17th, 2025

As we noted in our previous post, Generic AI vs. Web3 AI OS: Why Vertical Intelligence Wins in Crypto, we’re building the first Web3 AI Operating System (Web3 AI OS) — a unified platform that intelligently researches, plans, and executes anything crypto-related through simple natural language conversations. Whether you’re a seasoned trader optimizing DeFi yields or a newcomer spotting meme coin trends, our Web3 AI OS handles the heavy lifting — lowering barriers and unlocking innovation for everyone. Today, let’s give an introduction about what makes DAPPOS unique.

DAPPOS is built on two interconnected layers that work seamlessly to deliver end-to-end Web3 capabilities: the Intelligence Layer and the Execution Layer.

The Intelligence Layer forms the cognitive backbone, powered by our Multi-Agent Framework (MAF). With 300–400 specialized vertical agents and over 200 integrated tools, it excels in Web3 generalization — handling everything from quantitative trading analysis to marketing insights. Unlike generic AIs that scrape surface-level data, our agents dive deep into domain-specific contexts, surpassing them in reasoning and optimization.

Central to this is the Bubble Engine, our reinforcement learning (RL) powerhouse tailored for Web3. It evolves continuously by pulling real-time insights from sources like X and Binance Square, adapting to new trends in hours or days. Users can even accelerate this via the Bubble task platform — posting tweets to “force-feed” novel concepts, which get verified and integrated. What seemed impossible yesterday becomes routine today.

Complementing this is the Execution Layer, anchored by our proven Intent Execution Network. Battle-tested with over 5 million users and 12 million transactions, it turns AI-generated plans into secure, on-chain actions with institutional-grade efficiency and safety. No more manual wallet fiddling or risky bridges — DAPPOS executes flawlessly, minimizing errors and maximizing outcomes.

Built atop our Web3 AI OS, DAPPOS introduces Instant dApps — letting you create and deploy custom Web3 apps on demand via chat. It’s like vibe-coding for crypto: ideas turn into tools effortlessly. The Discover Page supercharges this community-driven vibe. It’s a dynamic hub where users share AI-generated insights and plans — from trading strategies to market analyses. Users can browse, adopt, and execute what resonates, fostering a collaborative ecosystem that democratizes alpha.

DAPPOS isn’t just solving today’s Web3 pain points — it’s pioneering a paradigm where decentralized tech becomes intuitive for all. By unifying research, planning, and execution, we’re turning Web3 into an accessible frontier, empowering users to build, innovate, and thrive.

As we continue evolving our Web3 AI OS, expect even more ways to orchestrate crypto’s potential. Stay tuned for what’s next.

— Written by the DAPPOS Team, September 16th, 2025

Over the past two years, we’ve all watched how fast generic AI platforms like ChatGPT, Claude, or Perplexity have grown into everyday tools. They summarize papers, debug code, and spin up copies with incredible ease. But while general-purpose models shine in horizontal breadth, they start to stumble once they step into the messy, high-stakes, and uniquely coded world of Web3.

That’s where DAPPOS enters: not as another generalist chatbot, but as a full Web3 AI Operating System. To understand why this distinction matters, let’s walk through some concrete cases where generic AI fails Web3 users — and how a Web3 AI OS corrects them.

The Intelligence Gap: Where Generic AI Falls Short

Intelligence in AI isn’t just about regurgitating facts; it’s about gathering, contextualizing, and reasoning over data to deliver actionable alpha. Generic models, trained on vast but static corpora, treat Web3 like any other topic — applying uniform logic that ignores the ecosystem’s opacity, volatility, and implicit rules.

Take data sources, for starters. Generic AIs rely on web scraping and pre-trained knowledge, which means they’re blind to user-specific, on-chain realities. Ask Perplexity for a DeFi yield optimization strategy, and you’ll get generic advice on protocols like Aave or Compound — maybe a nod to APYs from public sources. But it can’t pull your wallet balance, simulate recursive lending loops across chains, or factor in real-time gas fees and liquidation risks without clunky integrations.

DAPPOS’s Web3 AI OS flips this. Our Intelligence Layer, powered by a Multi-Agent Framework (MAF) with 300–400 specialized agents and over 200 tools, taps directly into blockchain APIs and authorized user data. It analyzes transaction histories, queries protocol exposures, and runs simulations on the fly. The result? Personalized plans that evolve with market shifts, turning vague queries into executable strategies.

Then there’s information weighting. Generic AIs apply broad priors, often missing Web3’s high-signal noise. For example, when analyzing Chainlink (LINK)’s recent hotspots, Perplexity might focus on logical fundamentals: oracle upgrades, partnerships in DeFi, and technical indicators like some on-chain metrics from recent quarters. It’s reasonable, but surface-level — it treats Wall Street’s growing interest in LINK as just another data point, which the We3 community truly cares about.

DAPPOS, powered by our Bubble Engine’s reinforcement learning, weights signals with the intuition of a Web3 native. It spotlights mainstream user perspectives: the surging hype around institutional adoption by powerhouses like BlackRock and UBS, linking it to ETF proposals (such as Grayscale’s S-1 filing) and price drivers like RWA tokenization and cross-chain integrations. This isn’t speculation; it’s dynamic prioritization sourced from live streams on X and Binance Square, where community sentiment often predicts pumps before charts do.

Web3’s nuances compound the issue. Slang, scams, and subtle cues — like bot-driven hype or coded exchange listings — trip up generic models. Consider a meme coin like Pengu partnering with McDonald’s for an example. Perplexity might gloss over it entirely, seeing no “substantive” tie and ignoring the activity as irrelevant fluff.

In DAPPOS, we know better: big-brand interactions scream upside in Web3. Our agents flag it as a liquidity trigger, cross-referencing social volume spikes, historical meme precedents , and community traction. Users get alerts on potential entry points, complete with execution plans — because in crypto, “fluff” often turns into fortunes.

We’ve seen this play out in other scenarios too. Generic AI might evaluate a new Web3 AI Agent project by team credentials and whitepaper tech, but overlook wallet clustering signaling insider pumps. DAPPOS detects anomalies via on-chain forensics, filtering manipulation and surfacing real alpha-like hidden ties.

The Execution Chasm: From Plans to On-Chain Reality

Intelligence alone isn’t enough — Web3 thrives on action. Generic AIs stop at suggestions, leaving users to manually operate on wallets, DEXs, or bridges. This creates friction: a Perplexity-generated trading plan might outline steps for a loop lending strategy, but as execution details are not included, users will get confused.

DAPPOS’s Execution Layer closes the loop. Built on our Intent Execution Network — battle-tested with 5 million users and 12 million transactions — it turns AI plans into secure, on-chain moves with institutional-grade safety. Just click the “execute” button and watch the system execute your strategy.

For instance, in a cross-chain arbitrage play, generic AI might describe spotting a price discrepancy between Uniswap and Raydium. While DAPPOS can not watch it, but also analyze the factors in your holdings, and execute the arbitrage strategy for you — minimizing MEV exposure and optimizing for speed.

Toward a Web3&AI Frontier

DAPPOS isn’t just an AI — it’s the OS unlocking Web3’s potential. We’re evolving it to be your crypto co-pilot: anticipating market moves, executing flawlessly, and democratizing alpha for all. In a world where generic tools plateau, vertical AI OS like ours will define the next era.

— Written by the DAPPOS Team, September 15th, 2025

Introduction

dappOS continues to optimize and expand the Web3 intent layer, delivering a more efficient, secure, and cost-effective Web3 experience for users. dappOS now introduces the new Pilot mode for its spot trading feature, intentEX, specifically designed to meet users’ trading needs for popular on-chain tokens. With advantages such as “institutional-level, full-market liquidity + low fees + USDT trading pair + transparent order books,” the intentEX Pilot mode has become the go-to choice for users engaging in on-chain transactions.

1. Why is IntentEX Pilot Needed?
   The demand for on-chain transactions is currently at an all-time high. However, many existing on-chain exchanges fall short in terms of liquidity, execution speed, and fee structures, significantly impacting user experience. On one hand, trading liquidity for popular assets is often fragmented across various CEXs and DEXs, making it difficult for users to access full-market liquidity on a single platform. On the other hand, to ensure instant purchases at desired prices, users often have to pay substantial fees to trading platforms; otherwise, they risk transaction failures or MEV attacks.
   The dappOS intentEX Pilot mode was created to address the issues of liquidity, transaction costs, and efficiency. By collaborating with numerous professional CeDeFi service nodes, we aim to help users complete on-chain transactions efficiently and at low costs, truly realizing their trading intentions.

2. IntentEX Pilot Overview
The Pilot mode is primarily designed to help newly supported tokens on intentEX quickly meet its liquidity standards in the initial stages. In this mode, a small amount of tokens is lent out in the form of CeDeFi to professional nodes, enabling them to leverage their advantages for low-cost arbitrage settlements across chains and exchanges. Once trading volume or token holders reach a certain scale, we will continue building by collaborating with market makers and project teams.

In terms of security, the Pilot mode adheres to CeDeFi industry standards, ensuring the safety of lent tokens through “margin staking + liquidation mechanisms.”

3. Core Advantages of IntentEX Pilot

• Variety of Token Selection: Comprehensive support for popular tokens on Solana, Base, BNB, and other chains, with fast listing.
• High Liquidity: Professional market makers conduct full-network arbitrage, ensuring deep order book depth.
• CEX-like Experience: USDT trading pairs and order book trading.
• Low Fees: Transaction fees as low as 0.1%, with gas costs at the 0.0001U level.

Experience dappOS intentEX Pilot today and embark on a new chapter in your Web3 trading journey!

Introduction

dappOS is committed to building a comprehensive Web3 Intent Layer, simplifying user interactions while delivering institutional-grade execution efficiency. The three core components of the Web3 Intent Layer are: Operations, Assets, and Transactions. Previously, dappOS introduced the Intent Operating System (IntentOS) and Intent Asset, enabling the transformation of operations and assets into intent-centric processes. Based on this foundation, dappOS has now launched IntentEX, a spot trading based on dappos intent excecution network designed to further enable intent-centric transactions, completing a crucial part of the dappOS Intent Layer ecosystem.

The core advantage of IntentEX lies in providing ordinary users with direct access to institutional-level liquidity resources, faster trade execution, and lower fees, delivering an experience that closely rivals top centralized exchanges (CEX).

I.Background

The crypto market is currently experiencing a surge in new assets and MEME tokens, driving strong on-chain trading demand from users. However, many existing on-chain exchanges struggle to provide sufficient liquidity, suffer from slow execution speeds, and impose high transaction fees. These issues significantly degrade the user experience.

The root cause of these challenges lies in the fragmentation of asset liquidity across various exchanges, preventing users from accessing comprehensive liquidity for a given asset on a single platform.

With the launch of dappOS IntentEX , liquidity, transaction cost, and efficiency issues are effectively addressed. IntentEX enables users to truly execute their trading intentions, delivering a seamless and efficient trading experience.

II. Mechanism of IntentEX

The core design innovation of IntentEX lies in its ability to transform traditional order book exchanges by treating users’ limit orders as intent tasks, which are then delegated to the nodes within the dappOS Intent Execution Network. These nodes are allowed to execute trades on any blockchain.

This design not only leverages the liquidity advantages of professional institutional traders, effectively providing tokens within IntentEX with liquidity superior to that of all CEXs and DEXs, but also offers users faster transaction speeds and lower execution fees.

2.1 Publishing Intent Tasks

When a user places a limit order on IntentEX, it is equivalent to publishing an intent task on the dappOS Intent Execution Network. The matcher nodes in the network will match the task to the most competitive service node. When selecting a service node, the matcher node will consider various factors, such as the node’s collateral, execution costs, execution speed, and the number of orders the node is willing to take at certain price deviations from the order book.

Once the user completes the signature, the service node that accepts the intent task will commit to a specific order quantity that it guarantees the user will be successfully executed. Due to the dappOS Intent Execution Network’s OMS mechanism, once the service node signs and confirms the exclusive execution quantity, the node will be liquidated if it fails to fulfill the commitment. Therefore, by this stage, the user can consider the committed portion of the order as already completed without needing to wait for final on-chain confirmation. When the user’s order price is near the order book, the service node will tend to commit to executing all the orders, allowing the user’s order to be filled faster than the base block time of the public blockchain.

2.2 On-Chain Order Processing

After committing to the order, the service node will complete the order processing on-chain in the following three steps under system constraints:

1. Internal Fill: If there is a matching order in the IntentEX order book, the system will directly match and execute the trade. Any unmatched portion of the order will proceed to the next stage.
2. Node Exclusive Fill: The remaining orders, within a certain time frame, will be exclusively handled by the service node. If the service node did not complete the committed order quantity during the internal fill stage, the service node must execute the orders itself, or face liquidation by the execution validator nodes in dappOS network. The service node can also choose to execute more orders than initially committed during this phase.
3. Open Orders: Any remaining orders will be posted to the IntentEX order book for other users to trade.

If a service node has a slow execution speed or commits to executing fewer orders for the user, its competitiveness in matcher nodes will decrease, making it harder for the node to receive more orders. This mechanism encourages service nodes to commit to executing more orders for users and to complete transactions more quickly.

2.3 A Specific Use Case

Let’s walk through a concrete example: Assume that the $A token on IntentEX has the following sell-side order book:

• Sell 1: Total $990 at a price of 9.9 USDT.
• Sell 2: Total $1010 at a price of 10.1 USDT.

At this point, a user places a limit buy order for 300 units of $A at 10 USDT. This order is then published as an intent task on the dappOS Intent Execution Network, and the matcher node within the network will assign the task to the most optimal service node.

Let’s say a service node successfully competes for this intent task. It will need to commit to a minimum number of orders it will help the user fulfill (e.g., 250 $A buy orders). The specific commitment amount usually depends on the node’s strategy and the current market depth of $A token in other markets. For instance, the node may be willing to commit to at least 250 orders because:

• IntentEX’s order book already has 100 orders at 9.9 USDT ready to be filled.
• After observing other DEX and CEX markets, it finds another 150 $A orders that cost less than 10 USDT (after considering transaction fees).

From the user’s perspective, 250 out of their 300 limit buy orders are already filled when the service node submits its commitment to the network. This fill speed is faster than the block speed of the public blockchain. In this example, the depth of the $A order book is not very large, but in cases where there is sufficient liquidity, the node would commit to filling all the orders near the market price, ensuring that the user’s orders are executed immediately.

Next, the service node will proceed with the following order execution process:

1. Internal Fill:
   100 of the user’s 300 10 USDT limit buy orders will be matched with 100 existing 9.9 USDT sell orders on IntentEX and executed at 9.9 USDT.
2. Node Exclusive Fill:
   Since the service node has committed to helping the user fill at least 250 orders, it must fulfill the remaining 150 orders in this stage, or face liquidation.
   Here’s where IntentEX’s advantage shines: Instead of leaving the remaining unfilled orders on the order book and waiting for other market makers to arbitrage them, the professional service nodes within the intent execution network take on this role directly. On one hand, this provides users with liquidity across all markets for $A tokens; on the other hand, it ensures faster execution of the user’s orders.
3. Open Orders:
   The final 50 of the 300 10 USDT limit buy orders, if not filled by the service node, will appear on IntentEX’s $A token buy-side order book.
   Generally, this scenario occurs only when the user’s limit price is far from the current market price, or when the liquidity of the relevant token is insufficient across all trading markets.

III. Core Advantages of IntentEX

1. Institutional-Grade Market-Wide Liquidity

dappOS’s professional service nodes can monitor all CEXs and DEXs in the market and match user orders in real-time. As a result, token trades within IntentEX benefit from market-level liquidity.

Compared to pure on-chain pricing designs like routers, IntentEX combines both on-chain and off-chain liquidity to provide institutional-grade liquidity capture capabilities. This allows each user order to be matched with the best price source, resulting in higher fill rates and faster execution, while tapping into full market liquidity.

Unlike other intent-based architectures, dappOS’s unique Optimistic Minimum Staking (OMS) mechanism ensures that nodes don’t occupy capital when accepting tasks. As long as the task can be completed, the funds can be used for multiple operations concurrently without the need for special liquidity provision or staking, reducing the overall operational costs

2. Faster Execution
Leveraging market-wide liquidity, IntentEX provides users with faster execution speeds than conventional on-chain trading by rapidly matching orders to the best available prices.

The execution efficiency is powered by dappOS Intent Execution Network and its specialized service nodes, which can typically complete order signature confirmation within 500 ms. This significantly reduces wait times, offering a trading experience that is closer to that of centralized exchanges (CEXs).

3. Lower Transaction Fees
With its network of professional service nodes, IntentEX significantly optimizes transaction fees, reducing costs to as low as 0.1%, which is much lower than most on-chain exchanges. This makes IntentEX a more economical choice for users when trading on-chain.

4. Decentralization and Transparency
All transactions on IntentEX are recorded on-chain, ensuring system transparency and trustworthiness. The decentralized mechanism of the dappOS Intent Execution Network guarantees reliable order execution. Even if a service node fails, other nodes can seamlessly take over, ensuring continuous order fulfillment. This decentralized structure provides users with a more stable trading experience, without dependence on any single-point server reliability.

IV. IntentEX and the dappOS Ecosystem

IntentEX is a key component of the dappOS ecosystem. Following the successful implementation of intent-centric operations and assets, dappOS introduced IntentEX to facilitate intent-centric trading for users.

The previous sections have detailed how IntentEX operates based on the dappOS Intent Execution Network. For more information on the underlying principles of the dappOS Intent Execution Network, please refer to：https://dappos.gitbook.io/docs/dappos/how-dappos-works

Additionally, the assets traded on IntentEX — USDT, BTC, and ETH — are actually intent assets within dappOS, known as intentUSD, intentBTC, and intentETH. This means that users can earn interest on these mainstream assets even when they are not actively trading, without hindering the ability to use them for immediate transactions. For a detailed explanation of dappOS Intent Assets, please refer to：https://dappos.gitbook.io/docs/dappos/intent-task-frameworks/intent-assets

dappOS is thrilled to announce a strategic partnership with Pencils Protocol, a cutting-edge decentralized platform offering auction services and leveraged yield aggregation for blockchain native assets and RWAs. This collaboration will introduce a series of underlying assets to dappOS Intent Assets (IA), enabling users to tap into enhanced yield opportunities through Pencils’ innovative Vaults system.

By integrating Pencils Protocol’s Vaults, users will have access to highly flexible yield farming strategies. The Vaults Pool, connected to leading DEX liquidity pools, allows participants to select their preferred LP tokens and customize leverage multiples. This ensures that users can maximize returns while benefiting from dappOS’s seamless intent execution network. Vault 1.0 empowers early participants with additional rewards, including multiple tokens such as Pencils, DEX, and Scroll tokens. Vault 2.0 will further extend these benefits by integrating with leading Liquid Restaking protocols, offering native restaking yields along with extra rewards from EigenLayer and other partners. This creates a comprehensive and rewarding experience for users.

Through this partnership, dappOS users can enjoy diversified and efficient yield management, leveraging the advanced features of Pencils Protocol to achieve consistent returns while maintaining asset flexibility on-chain.

About dappOS

dappOS is an intent execution network that revolutionizes how users interact with decentralized blockchain systems. Instead of manually navigating through multiple steps in traditional dApps, users can simply focus on what they want to achieve with dappOS. The network’s service providers handle all the intermediate processes, ensuring users get their desired outcomes with minimal effort and institutional-level efficiency.

Learn more about dappOS

About Pencils

Pencils Protocol is the next-gen decentralized platform that offers auction services for blockchain native assets and RWAs, along with unified and leveraged yield aggregation services for users to maximize asset utilization.Pencils Protocol also serve as Scroll native gateway for liquid staking and restaking assets.

Powered by Scroll, Pencils Protocol redefines the Layer-2 sectors by utilizing Scroll’s zero-knowledge technology. We focus on scalable and private DeFi services, enhancing yield aggregation and farming. By leveraging the synergy between our launchpad and farming solutions, we aim to become the primary TVL gateway for the Scroll ecosystem.

Learn more about Pencils

dappOS is excited to announce a strategic partnership with Zircuit, a $1.7B staked zk-rollup with sequencer-level-security. This integration will introduce a new underlying asset for dappOS Intent Assets (IA), offering users enhanced yield opportunities while preserving asset flexibility.

Zircuit will protect users at the sequencer level by monitoring the mempool for malicious transactions and preventing their inclusion into a block. By integrating dappOS intent execution network, Zircuit can quickly attract user funds and migrate transactions to Zircuit, ensuring a robust and dynamic ecosystem.

Through this integration, dappOS Intent Assets can leverage the benefits of Zircuit, allowing users to earn consistent yields while seamlessly using their assets on-chain. For instance, intentETHs can be used directly in DEXes to provide liquidity for the ETH/USDT pair, or deposited to CEXes and traded as $ETH while generating an APY of 6–12%.

About dappOS

dappOS is an intent execution network that revolutionizes how users interact with decentralized blockchain systems. Instead of manually navigating through multiple steps in traditional dApps, users can simply focus on what they want to achieve with dappOS. The network’s service providers handle all the intermediate processes, ensuring users get their desired outcomes with minimal effort and institutional-level efficiency.

Learn more about dappOS

About Zircuit

Zircuit is an EVM-compatible zero-knowledge rollup powering the limitless potential of web3. Backed by pioneering L2 research, the network’s unique hybrid architecture combines battle-tested infrastructure with zero-knowledge proofs to give developers the best of both worlds. With cutting-edge performance and security at the sequencer level, users can explore new frontiers with faster transactions, reduced fees, and complete peace of mind.

Learn more about Zircuit

dappOS is joining forces with Berachain, a high-performance EVM-identical Layer 1 blockchain, to revolutionize the user experience and asset utility in the Web3 space.

Berachain’s Proof-of-Liquidity (PoL) consensus mechanism rewards ecosystem liquidity, which is essential for efficient trading, price stability, and network growth. This aligns perfectly with dappOS’s innovative Intent Assets, which enable users to earn yield while keeping their assets readily available for transactions.

By integrating dappOS intent execution network, Berachain dApps can quickly attract user funds and migrate transactions to Berachain, ensuring a robust and dynamic ecosystem.

By introducing Berachain’s native yield assets into intent assets, users can enjoy the yield opportunities in the Berachain ecosystem without losing flexibility in different scenarios. This will also make it easier for Berachain dApps to attract existing Web3 users and funds.

Furthermore,Berachain’s high performance will significantly reduce the cost and increase the speed of multiple core use cases of dappOS, such as intent assets and intentEX (a new use case tailored for spot trading based on the intent execution network). Quick and cost-efficient transactions can elevate the user experience to the next level, driving mass adoption of the dappOS ecosystem.

The integration between Berachain and dappOS exemplifies the potential of intent to transform the Web3 landscape. This integration ensures that users can effortlessly use Berachain applications by leveraging dappOS use cases like intent assets,intentEX,dApp interaction task execution, enabling both sides to achieve a fast and efficient user acquisition process.

About dappOS

dappOS is an intent execution network that empowers decentralized infrastructure and applications to be intent-centric, streamlining user interactions within the blockchain ecosystem. dappOS enables users to specify their desired outcomes, or intents, without detailing the execution steps. By introducing the Optimistic Minimum Staking (OMS) mechanism, dappOS ensures efficient and secure execution of these intents.

Learn more about dappOS

About Berachain

Berachain is a high-performance EVM-Identical Layer 1 blockchain that leverages Proof-of-Liquidity (PoL) as its consensus mechanism, built on the modular BeaconKit framework. This design ensures complete compatibility with the Ethereum Virtual Machine, allowing Berachain to seamlessly adopt EVM updates and support existing EVM tooling. PoL incentivizes ecosystem liquidity, promoting efficient trading, price stability, and network growth. Berachain’s BeaconKit framework enhances composability and achieves single slot finality, contributing to the robust and scalable infrastructure of Berachain.

Learn more about Berachain