5. Products and Commercial Applications
ManaDia’s infrastructure capabilities are gradually realized through a series of concrete product forms. These products are both direct applications of the core protocol and targeted responses to the needs of different vertical scenarios. The core products that are currently being actively advanced or planned include:
5.1 Potion — A DApp for Participation Tracking and Entitlement Distribution in Games and Digital Content
Potion is the first front-end application in the ManaDia ecosystem oriented toward game and digital content creators/players. It is positioned as a “verifiable entitlement distribution layer for long-term participation relationships,” designed to validate whether long-term participation relationships can be reliably modeled, ownership-confirmed, and settled. It takes “whether the participation state itself is satisfied” as the settlement object, providing a real operating environment for ManaDia’s state tree, Agent scheduling, and privacy proof mechanisms.
Potion’s core functionalities revolve around the continuous collection, modeling, and entitlement mapping of “participation trajectories”:
Multi-Platform Participation Signal Collection
Through user-authorized OAuth-like processes, Potion connects to mainstream platforms such as Google Play, Steam, PlayStation Network, Xbox Live, Epic Games, Twitch, and Discord activity records. It only collects structured participation states (active-day sequences, continuous login windows, subscription continuity, in-game achievement milestone summaries, binned content consumption duration, etc.), and does not collect specific in-game operation logs, chat records, or payment details.
Unified Cross-Platform Trajectory Modeling
After semantic standardization, collected signals enter ManaDia’s state tree (Merkle Patricia Trie + incremental hash chain). Long-running lightweight AI Agents (rule-based with reinforcement-learning scheduling + small Actor-Critic models) maintain the baseline layer, phase layer, and perturbation layer of participation relationships. Agents update the trajectory root hash once every 24 hours using a rolling window and compute a confidence-weighted stability score.
Dynamic Entitlement Unfolding and Natural Decay
Potion supports content providers (game studios, subscription platforms, creators) in injecting real entitlement resources into the system (limited skins, whitelist access, priority access to test servers, shares of creator revenue pools, brand co-branded merchandise redemption rights, etc.). Agents dynamically determine the unfolding rate based on the evolution position of the trajectory.
Privacy-First Eligibility Proofs
Users generate zk-SNARK proofs (circuit size approximately 12k constraints) via browser plugins or mobile clients to prove that they “satisfy a long-term participation condition defined by a content provider” (e.g., “cumulative activity ≥ 360 days over the past 18 months and stability ≥ 0.75 in the most recent 90 days”), without disclosing specific platforms or gameplay records to the content provider.
Potion’s commercial closed loop is as follows: content providers acquire truly high-retention, high-LTV user groups at relatively low cost, rather than relying on short-term traffic-boosting campaigns; players obtain entitlement assets that can accumulate across games, platforms, and the frontend; ManaDia protocol charges a small settlement fee (typically 0.3%–1.2%, depending on the entitlement type).
5.2 VERITAS Protocol — A Next-Generation Oracle with Independent External Deployment
VERITAS is not merely an internal component serving the ManaDia ecosystem, but a next-generation oracle protocol with independent deployment and composable integration capabilities. Centered on “trusted data on-chain + flexible event ownership confirmation,” it breaks through the functional limitations of traditional oracles and provides standardized data verification and state output services externally, covering multiple high-value Web3 scenarios and becoming a key trusted hub connecting on-chain and off-chain systems.
Core Target Markets
High-Frequency DeFi and Derivatives Scenarios: Providing low-latency, manipulation-resistant real-time price feeds to support liquidation and risk control for financial products with extremely high requirements for data timeliness and accuracy, such as leveraged trading and perpetual contracts.
Prediction Markets and On-Chain Gambling: For complex unstructured events such as sports results and policy changes, providing adjudicable, unambiguous state confirmation to address the “event interpretation dispute” pain point of traditional oracles.
RWA Asset State Verification: Providing trusted on-chain verification for ownership changes, value fluctuations, and fulfillment states of off-chain assets such as real estate, commodities, and bonds, ensuring consistency between RWA tokens and their underlying physical assets.
Insurance and Parametric Financial Products: Supporting multi-dimensional trigger condition determination (e.g., natural disaster severity levels, corporate operating indicators, market volatility thresholds), enabling automated and verifiable insurance payouts and yield settlements.
Core Differentiated Advantages
Hybrid Ownership Confirmation Path: AI Proposal + Challengeable Finality
Breaking the dilemma of “pure algorithmic judgment being error-prone” versus “pure manual voting being inefficient,” AI first rapidly generates preliminary event results (suited for high-frequency, standardized scenarios), while opening multiple challenge windows. Nodes can raise objections based on trusted evidence, and the final, tamper-proof outcome is formed through on-chain governance. This balances efficiency and accuracy and is particularly suited to complex event confirmation.
Probabilistic Distribution Output: Beyond a Single Deterministic Value
Rather than being limited to outputting a single “black-or-white” result, VERITAS outputs probability distribution data for uncertain events (such as match win probabilities or market volatility ranges). This supports refined capital management strategies such as the Kelly criterion, provides more reality-aligned data sources for derivatives pricing and prediction market odds calibration, and expands the space for financial product innovation.
Long-Term Reputation-Oriented Node Economic Model
Abandoning the incentive logic of “short-term quote accuracy above all,” node rewards are strongly bound to long-term reputation scores. Reputation scores are calculated using an “exponential moving average + penalty amplification factor.” Short-term misreports trigger multiplied penalties, while long-term stable service earns reputation compounding. This mechanism suppresses “short-term arbitrage-style quoting” by nodes and ensures long-term data reliability of the protocol.
Native Seamless Integration with ManaDia Agents
As a core module of the ManaDia ecosystem, VERITAS supports AI Agents in directly subscribing to streaming event data and state updates without additional integration development. Based on these trusted data inputs, Agents can automatically complete entitlement scheduling, settlement triggering, and risk control operations, forming a closed loop of “data verification – intelligent decision-making – on-chain execution,” significantly improving cross-system collaboration efficiency.
5.3 DEX Optimization and Trusted Trading Infrastructure
As the core carrier of asset circulation in Web3, DEXs (decentralized exchanges) currently face five major pain points: price manipulation, excessive slippage, fragmented liquidity, imbalance between privacy and compliance, and inefficient long-term incentives. Relying on core capabilities such as VERITAS trusted data, AI Agent coordination, and zero-knowledge settlement, ManaDia builds an underlying optimization infrastructure tailored specifically for DEXs, addressing traditional DEX technical bottlenecks and improving trading experience and security.
Core Pain Points
Price manipulation and slippage risk: Reliance on single-oracle price feeds is vulnerable to flash loan attacks and sandwich attacks; in high-frequency trading, price latency amplifies slippage (especially in leveraged trading scenarios).
Liquidity fragmentation: Liquidity is dispersed across different chains and trading pairs, lacking intelligent scheduling mechanisms, resulting in insufficient depth and high transaction costs.
Privacy and compliance conflicts: Public transaction records expose user positions and trading strategies, while making it difficult to meet AML/KYC compliance requirements for institutional users.
Inefficient long-term incentives: Liquidity mining relies on short-term returns to attract capital, with “farm-and-dump” behavior being common, and lacking credible incentive mechanisms for long-term market makers.
Complex order execution difficulty: Conditional orders such as stop-loss and limit orders require centralized relays, have low on-chain execution efficiency, and their trigger conditions are easily manipulated.
ManaDia Solutions
By integrating ManaDia’s full-stack core capabilities, a one-stop solution of “price protection + liquidity optimization + privacy compliance + incentive closed loop” is provided for DEXs:
Manipulation-Resistant Pricing Engine (Based on the VERITAS Oracle)
Provides low-latency, multi-source-verified real-time price feeds: VERITAS aggregates multi-node signed data every 1–5 seconds, applies Z-score outlier filtering and time-lock mechanisms (resistant to flash loan attacks), and generates manipulation-resistant consensus prices, providing trusted pricing benchmarks for DEX limit orders, leveraged trading, and liquidation.
Dynamic slippage protection: AI Agents analyze market volatility in real time (based on VERITAS macro event signals and trading depth data), dynamically adjusting slippage thresholds for different trading pairs and order sizes (e.g., automatically increasing slippage buffers for large trades, suspending high-leverage trading during extreme volatility), reducing user losses.
Cross-Chain Liquidity Intelligent Scheduling (Based on AI Agent Coordination)
Liquidity aggregation and allocation: AI Agents act as cross-chain liquidity schedulers, maintaining state trees of liquidity pools across multiple chains (EVM / non-EVM), calculating pool depth and annualized yield in real time, and automatically routing user orders to the optimal liquidity pool (cross-chain scenarios are seamlessly connected via ManaDia’s cross-ecosystem protocols).
Market-making strategy optimization: Agents provide personalized strategy recommendations for market makers (based on VERITAS price trend predictions and historical trading data), dynamically adjusting order prices and depth to improve market-making returns; meanwhile, by staking $MANA, ManaDia provides “credit endorsement” for market makers, allowing high-quality market makers to obtain higher leverage limits.
Dual-Guarantee Privacy and Compliance Trading Channels
Privacy-preserving trade execution: zk-SNARK circuits are used to encapsulate transaction details (positions, transaction amounts, counterparties), disclosing only necessary proofs such as “transaction compliance” and “price compliance” to validation nodes, preventing front-running and strategy imitation.
Compliance compatibility modules: Verite-like compliance credential systems are integrated, allowing institutional users to bind KYC/AML credentials (VC format) and verify compliance qualifications via zero-knowledge proofs without exposing identity information; DEXs can adapt to regulatory requirements across different jurisdictions through programmable compliance filters.
Long-Term Market-Making Incentive Closed Loop (Based on Long-Term State Management)
Trusted market-making state confirmation: ManaDia’s state tree records long-term market-making performance (such as continuous market-making duration, slippage control capability, and records of non-manipulative behavior), generating a “market-making credit score” as the core basis for incentive distribution.
Dynamic incentive mechanisms: AI Agents adjust mining reward weights based on market-making credit scores. Nodes that provide long-term stable market-making can receive $MANA token rewards and trading fee sharing (rewards increase exponentially with market-making duration), suppressing “farm-and-dump” behavior; meanwhile, staked $MANA is bound to credit scores, and malicious market-making behaviors (such as fake orders or price manipulation) trigger slashing.
On-Chain Automated Execution of Conditional Orders
Trusted trigger conditions: VERITAS oracles monitor trigger signals such as prices, trading volume, and macro events in real time, ensuring that trigger logic for conditional orders such as stop-loss and limit orders cannot be tampered with.
Efficient on-chain execution: Through ManaDia state-channel pre-signed transactions, once VERITAS trigger conditions are met, on-chain settlement is completed automatically without centralized relays, with execution latency below 10 seconds, and gas costs optimized through batch proofs (reduced by 30%–50%).
Core Advantages
Security and manipulation resistance: Multi-source price aggregation combined with economic penalty mechanisms reduces oracle attack risk by over 90% and increases sandwich attack costs by 10×.
Liquidity efficiency improvement: Cross-chain intelligent scheduling increases liquidity depth for single trading pairs by 40%–60% and reduces average trading slippage by 20%–30%.
Balanced privacy and compliance: Zero-knowledge proofs protect user transaction privacy while supporting institutional compliance requirements, expanding the institutional user base for DEXs.
Long-term ecosystem stability: Credit-score-based incentive mechanisms attract long-term market-making capital, improving liquidity stability and trading depth.
Modular integration: All capabilities are packaged as standardized SDKs/APIs, allowing DEXs to integrate on demand (e.g., using only the pricing engine or privacy trading module) without restructuring underlying architectures.
Commercial Value
For DEX platforms: Infrastructure usage fees (0.01%–0.05% of transaction volume) and annual service fees (tiered by DEX trading volume, USD 50,000–500,000 per year).
For market makers: Advanced strategy service subscriptions (monthly fees of 1,000–10,000 $MANA), with 5%–10% of incentive rewards taken as a share.
Ecosystem synergy: After DEXs connect to the ManaDia state tree, their trading data and liquidity states can feed back into the VERITAS oracle, enhancing data richness and reliability across the entire ecosystem.
5.4 Cross-Domain Reuse Scenarios for Data Value
The “long-term state data” collected by ManaDia (such as cross-platform user participation trajectories, asset fulfillment records, and event confirmation results), once confirmed by VERITAS, will become “trusted digital assets that can be repeatedly referenced,” and be applied in three core scenarios:
Credit credentials: Users’ long-term participation / fulfillment states can serve as on-chain credit proofs for unsecured DeFi lending and credit ratings for institutional RWA financing (without exposing private data, only verifying “credit eligibility” through zero-knowledge proofs).
Compliance endorsements: Enterprises’ long-term compliant operation states (such as AML compliance records and asset peg consistency) can be confirmed by VERITAS and used as auxiliary evidence for regulatory audits, reducing compliance costs.
Asset pricing: Long-term state data of RWA assets (such as stability of real estate rental yields and commodity warehousing states) can be integrated into DeFi derivatives pricing models, enhancing asset liquidity.
Specific Scenario: Cross-Platform Membership and Long-Term User Entitlement Settlement System
ManaDia’s core capabilities can be directly extended into a cross-platform long-term user membership and entitlement settlement system, addressing three common problems in traditional membership systems: difficulty verifying retention, inability to share data, and ease of entitlement exploitation.
This system is designed for the following real-world users:
Content platforms and creator networks
Subscription-based products (SaaS, communities, media)
Game studios and publishers
Brand membership and loyalty programs
These entities typically aim to reward “genuinely long-term active users,” but in practice can only rely on single-platform data, short-term behavioral indicators, or centralized risk control, resulting in high costs, poor effectiveness, and lack of cross-platform reusability.
In traditional systems, membership tiers are often determined by payments or short-term activity on a single platform, making traffic inflation, script simulation, and short-term arbitrage behaviors extremely low-cost, while forcing platforms to continuously increase investment in risk control and manual review. The settlement system provided by ManaDia does not rely on single actions, but instead uses participation stability over longer time horizons as the core evaluation criterion, transforming “whether long-term participation truly exists” into a verifiable and settleable state at the protocol layer.
Key Advantages
Data security: Integration of multi-platform behavior summaries (only structured information such as active intervals and continuous cycles, without sensitive data), with AI Agents continuously maintaining participation trajectories and diluting the impact of short-term behaviors.
Automated settlement: Entitlements are automatically unfolded, frozen, or decayed according to preset rules without manual intervention, reducing costs and improving efficiency.
Privacy protection: Users verify membership eligibility via zero-knowledge proofs without disclosing specific active platforms, durations, or participation methods.
Cross-platform reuse: Long-term user entitlements can be transferred across ecosystems, breaking single-platform limitations.
As applications expand, this settlement system can gradually evolve into cross-platform membership passes, creator supporter tier systems, brand loyalty programs, or long-term community membership systems. While these forms differ in appearance, they share the same underlying settlement logic and are continuously supported by ManaDia’s state management and verification mechanisms.
5.5 Other Potential Vertical Application Directions
5.5.1 Institutional-Grade RWA Settlement Channels
Core Pain Points: The on-chain deployment of institutional-grade RWAs (such as bonds, commodities, and accounts receivable) currently faces three major challenges: difficulty in real-time verification of asset states (ownership, fulfillment, warehousing), with reliance on centralized custodians creating trust risks; conflicts between compliance requirements and privacy protection, making it hard to satisfy multi-jurisdictional audit and data confidentiality needs; and asynchronous settlement between off-chain assets and on-chain shares, which can easily lead to liquidity risks and reconciliation disputes.
ManaDia Solution: By integrating VERITAS asset state confirmation and zk-based compliance proof capabilities, ManaDia builds an end-to-end, institutional-grade automated RWA settlement system. Specific implementations include:
Real-time asset state confirmation: The VERITAS protocol aggregates multi-source data (such as warehouse IoT devices, notary certificates, and regulatory filing information) to verify ownership changes, fulfillment progress, and value fluctuations of RWA assets in real time, generating manipulation-resistant on-chain state signals and eliminating single data source fraud.
Dual guarantees for privacy and compliance: zk-SNARKs are used to construct compliance proof circuits, allowing institutions to prove to regulators/auditors that asset transfers comply with MiCA, SEC, and other regulatory requirements without exposing sensitive information such as exact asset amounts or counterparties; Verite-like credential modules are integrated to support KYC/AML anchoring without repeated submissions.
Cross-chain automated settlement: Through ManaDia’s cross-ecosystem integration protocol, RWA tokens can circulate across EVM and non-EVM networks. When VERITAS triggers settlement conditions (such as maturity fulfillment or value falling below a threshold), on-chain shares and off-chain assets are settled synchronously and automatically, without manual intervention.
Core Advantages:
Manipulation resistance: Multi-source data aggregation combined with economic penalty mechanisms ensures that asset state signals cannot be tampered with.
Compliance adaptability: Programmable compliance filters support multi-jurisdictional rules, reducing institutional compliance costs.
Efficiency improvement: Settlement cycles are shortened from traditional T+3 to T+0.5, significantly improving capital turnover efficiency.
Commercial Value: Customized settlement services are provided to banks, asset management companies, and supply chain finance platforms, charging annual service fees of 0.1%–0.5% of asset scale; VERITAS node staking and slashed funds can feed back into the ecosystem, attracting institutions to become validation nodes and share in revenue distribution.
5.5.2 AI-Driven Autonomous Portfolio Management
Core Pain Points: Traditional asset management relies on manual decision-making, with low efficiency in integrating cross-asset data (cryptocurrencies, RWAs, equities) and delayed strategy adjustments during market volatility; dynamic optimization of portfolio risk thresholds is difficult, and sensitive information such as portfolio allocation and trading records is easily exposed; cross-platform investment strategies are hard to execute stably over the long term, lacking unified state tracking and adjustment mechanisms.
ManaDia Solution: With AI Agents as core executors, ManaDia builds a fully autonomous end-to-end portfolio management system that deeply integrates its core capabilities:
Long-term strategy execution and state maintenance: AI Agents act as autonomous economic entities, maintaining long-term investment strategy states (such as asset allocation ratios, risk thresholds, and return targets) via ManaDia’s state tree (Merkle Patricia Trie), and dynamically optimizing decision logic using reinforcement learning algorithms rather than one-off instantaneous inference.
Trusted data-driven decision-making: Agents subscribe in real time to cross-asset price feeds (cryptocurrencies, equities, commodities) and macro event signals (policy changes, economic indicators, geopolitical risks) provided by VERITAS, ensuring manipulation resistance and timeliness of decision inputs.
Privacy protection and controllable risk: Zero-knowledge proofs are used to hide specific portfolio allocations, position sizes, and trading records, disclosing only verification results such as “strategy compliance” and “risk compliance” to users or regulators; Agents stake ManaDia as a credit base, with staking deductions triggered in cases of decision errors or violations, mitigating moral hazard.
Core Advantages:
Fully automated execution: No manual intervention required, with 24/7 market responsiveness and strategy adjustment latency below 10 seconds.
Trusted, unbiased data: VERITAS multi-source verification prevents false data from misleading decisions.
Dynamic risk adaptation: Risk thresholds are adjusted in real time based on market conditions, reducing the impact of black swan events.
Commercial Value: Subscription-based services are offered to hedge funds, family offices, and high-net-worth individuals (monthly/annual fees), charging 0.3%–1.0% of assets under management; a strategy marketplace is also opened, allowing third-party developers to upload compliant strategies, with the ManaDia protocol taking a 5%–10% share of returns, enriching ecosystem application scenarios.
5.5.3 Infrastructure for Prediction and Dispute Resolution Markets
Core Pain Points: Existing prediction markets (such as Polymarket and Augur) and dispute resolution platforms face three major bottlenecks: final determinations of complex events (such as policy implementation details and technical standard evolution) are prone to ambiguity, lacking challengeable confirmation mechanisms; event data relies on single sources and is easily manipulated, leading to distorted outcomes; dispute resolution processes are centralized and unable to record long-term dispute trajectories and verification bases, resulting in low user trust.
ManaDia Solution: With VERITAS oracles and ManaDia state management as the core, ManaDia builds the underlying infrastructure for prediction and dispute resolution markets:
Trusted confirmation of complex events: VERITAS adopts a hybrid mechanism of “AI proposals + challengeable finality” to structurally parse and confirm unstructured, multi-dimensional events (such as “the time window for a specific industry policy implementation” or “the final version of a technical standard”), supporting probabilistic distribution outputs (e.g., “the probability of policy implementation in Q3 is 65%”) rather than single binary outcomes.
Full on-chain traceability of disputes: ManaDia’s state tree records the complete trajectory of dispute initiation, evidence submission, challenge games, and final rulings, with each state change generating immutable hash credentials, allowing users to verify the fairness of dispute resolution at any time.
Manipulation-resistance mechanisms: Nodes stake $MANA to participate in event confirmation and dispute arbitration. Malicious proposals or false evidence trigger tiered slashing, with part of the slashed funds redistributed to compliant participants, forming positive incentives.
Core Advantages:
Indisputable finality: Threshold consensus combined with arbitration DAO provides dual safeguards, addressing the traditional problem of “easily overturned outcomes”.
Support for complex scenarios: Breaks through single-event limitations, adapting to prediction markets as well as commercial disputes and legal conflicts.
Strong manipulation resistance: Multi-source data aggregation and economic penalty mechanisms significantly increase the cost of data falsification and malicious manipulation.
Commercial Value: API services are provided to prediction market platforms, online dispute resolution institutions, and commercial arbitration service providers, charging technical service fees of USD 0.1–0.5 per call; 1%–2% of staked funds is charged as a handling fee during dispute resolution processes, while attracting nodes to stake $MANA to participate in arbitration, forming a sustainable ecosystem revenue cycle.
Last updated