Over the past few years, decentralized exchanges (DEXs) have focused primarily on a single problem: how to move trading on-chain. Today, the market has entered a new phase—who can become the default trading entry point for the next generation of traders in the AI era.

In an environment where social media, research platforms, and trading terminals are deeply digitized, an increasing share of trading decisions is now generated or heavily influenced by AI. From market interpretation and strategy backtesting to risk assessment, AI has become the first reference point for most traders. 1024EX emerges directly from this shift.

Rather than positioning itself as a high-end terminal for a small group of professional institutions, 1024EX is built around a broader question:

As AI becomes deeply embedded in trading decision-making, does the trading system itself have the structural capacity to support this transformation?

The central question today is no longer whether AI exists, but whether AI-generated decisions can actually be executed effectively.

A growing number of retail and professional traders already rely on AI for:

• Rapid synthesis of market and macroeconomic information

• Directional trade ideation and thesis formation

• Strategy logic design and conditional triggers

Yet on most trading platforms, AI remains confined to the “advisory layer.” Once a decision reaches execution, traders still face fragmented product structures, limited order capabilities, and execution environments that cannot be automated.

1024EX is built on a clear premise:

As trading decisions increasingly originate from AI, trading platforms themselves must become systems that AI can operate—not merely interfaces designed for human clicks.

1024EX’s “AI & Quant-Native” design does not treat models and strategies as add-ons. Instead, it assumes at the system level that automation, conditional logic, and structured risk management will become the norm in trading.

As a result, 1024EX does not compete on surface-level features. It is engineered around more fundamental qualities of trading experience: low-latency feedback, predictable system behavior, and consistency under high volatility and heavy load.

This produces two important outcomes:

• For advanced users and quantitative teams, AI-generated rules and strategies map naturally into on-chain execution;

• For retail traders, even without writing strategies themselves, trading behavior is implicitly shaped by AI-driven and rule-based structures, without requiring deep technical understanding.

In other words, 1024EX is not asking everyone to become a quant—it is making quantitative characteristics native to how more people trade.

1024EX is not built on a general-purpose blockchain. It runs on 1024Chain, a Layer 1 designed specifically for high-frequency financial workloads.

Key performance metrics disclosed include:

• Average block time: ~0.07 seconds

• Peak throughput: 2,000,000+ TPS

• Approximately 10× Solana’s performance under comparable conditions

These numbers matter not because they are “faster,” but because they reflect a structural shift:

On-chain trading systems can now sustain the response density and concurrency stability required by AI-generated decisions.

When AI outputs conditional and structured logic, any delay or instability in state updates turns the execution layer into a bottleneck. The performance characteristics of 1024Chain allow the AI → strategy → execution loop to function coherently on-chain for the first time.

On most platforms, spot, perpetuals, options, and prediction markets exist as isolated modules. Even when AI produces cross-market insights, those insights cannot be fully expressed within a single system.

1024EX takes a different approach: spot, perpetuals, options, and prediction markets are unified under a single on-chain architecture.

Within this system:

• Spot markets enable immediate price discovery

• Perpetual contracts express leveraged expectations and funding dynamics

• Options capture nonlinear risk and volatility structures

• Prediction markets incorporate probabilistic pricing of discrete events

This unified structure allows multi-dimensional, AI-generated views to be executed directly in one market environment—without being decomposed across platforms.

As AI becomes the dominant source of trading insight, traditional asset-class boundaries are eroding. Macro events, interest rates, geopolitics, and technology cycles increasingly impact equities, commodities, and crypto simultaneously.

1024EX’s multi-asset perpetual roadmap reflects this reality, covering:

• Crypto spot and perpetuals

• Equity indices and technology stocks

• Precious metals, energy, and commodities

• FX and interest-rate–related products

Through unified margining and execution, traders can express AI-driven, cross-asset views within a single platform—without reliance on legacy account structures or geographic constraints.

The design principle behind 1024EX’s execution layer is clear: AI- or strategy-generated decisions must be expressed fully and precisely, not degraded at the execution stage.

As AI becomes deeply embedded in trading decisions, a long-overlooked issue is emerging:

Most AI-generated trade recommendations implicitly assume the presence of institutional-grade order types and execution algorithms.

In traditional finance, this assumption holds. Exchanges like CME and NASDAQ, and brokerage platforms such as IBKR, natively support rich order semantics and execution algorithms, allowing strategies to be implemented with precision rather than constrained by platform limitations.

In contrast, crypto markets face a persistent structural gap:

• Most CEXs and DEXs support only a narrow set of basic orders

• Standard TradFi execution algorithms are largely unavailable

• The more professional and AI-dependent a strategy becomes, the greater the execution loss

This leads to an unavoidable conclusion:

As AI increasingly drives trading decisions, underpowered execution tools create an inherent unfairness for crypto traders.

1024EX is designed to close this gap by supporting a progressive spectrum of execution capabilities, including:

• Stop / Take-Profit (Market & Limit)

• Trailing Stops

• OCO and Bracket Orders

• Iceberg, Scale, and Pegged Orders

• TWAP, VWAP, and POV algorithms

• Composable conditional and logic-based orders

These tools are not about complexity for its own sake. They ensure that AI-generated views—directional, conditional, or portfolio-based—can be executed in a manner comparable to professional traditional markets.

Their shared purpose is to transform risk control, trading discipline, and execution logic from personal habit into systematically reproducible structures.

Beyond serving traders, 1024EX is also designed as a developer-native platform for strategies and AI agents.

As AI and Web3 converge, trading logic increasingly originates from strategies, models, and agents rather than individual accounts. The core question is no longer whether strategies can be written, but whether they have a native lifecycle for development, deployment, distribution, and monetization.

Through the 1024 Quant framework, 1024EX provides an end-to-end solution:

• Native quantitative and AI support within the trading interface, including function calling and visual analysis directly on price charts

• Strategy Store, where developers can publish strategies or AI agents for others to use

• Coding Agent & Online IDE, enabling development, testing, and iteration directly on the platform

• Open-source projects and developer SDKs, supporting broader ecosystem collaboration

Within this system, development, trading, distribution, monetization, and data accumulation form a single closed loop—allowing AI strategies to operate on-chain, be adopted by users, and continuously improve.

As AI becomes deeply involved in trading decisions, platforms are no longer just execution venues—they become part of decision quality itself.

An observable shift is already underway: many retail traders now interact with AI using natural language—asking for market views, constructing strategies, and defining risk conditions. Yet on most exchanges, these insights collapse into severely limited execution options.

1024EX aims to eliminate this disconnect by enabling users to invoke institutional-grade trading capabilities through natural language interaction.

On 1024EX, complex institutional operations—conditional triggers, portfolio-level risk controls, and execution algorithms—no longer require traditional professional backgrounds. They are accessed through more intuitive, human-centric interaction.

At its core, this represents a long-overdue principle: financial inclusion.

• Giving retail traders their first exposure to institutional-grade tools

• Making quantitative and systematic capabilities broadly accessible

• Reducing the extent to which trading outcomes depend on institutional status or privileged access

If quantitative trading has long been the most brilliant yet inaccessible jewel at the peak of Wall Street, then 1024EX’s ambition is Promethean in nature: to bring that jewel down from the summit and place it in the hands of everyday traders.

The resulting psychological shift is profound:

Users of 1024EX no longer feel like mere market participants—they feel equipped with capabilities once reserved for institutions.

This perception, more than short-term incentives, drives organic adoption and long-term retention.

As AI becomes the primary source of trading decisions, the true dividing line is no longer who has better insights, but:

Whether trading platforms themselves are capable of executing those insights in full.

In traditional finance, this problem was solved long ago. Institutional order types, execution algorithms, and structured risk systems became baseline infrastructure. Strategies could be expressed precisely, without degradation at execution.

In crypto markets, this layer has been largely absent. Many CEXs and DEXs remain constrained by limited execution models, causing the most sophisticated and AI-driven decisions to suffer the greatest loss at the point of execution.

1024EX is built to address this structural gap—bringing mature trading structures and execution capabilities from traditional finance onto the blockchain, so that AI-generated decisions are fully expressed rather than constrained by platform limitations.

In the AI era, traders do not just need smarter sources of insight. They need a trading entry point worthy of those insights and capable of keeping pace with them. 1024EX is designed to be that entry point.

https://www.1024ex.com

Over the past few years, decentralized exchanges (DEXs) have focused primarily on a single problem: how to move trading on-chain. Today, the market has entered a new phase—who can become the default trading entry point for the next generation of traders in the AI era.

In an environment where social media, research platforms, and trading terminals are deeply digitized, an increasing share of trading decisions is now generated or heavily influenced by AI. From market interpretation and strategy backtesting to risk assessment, AI has become the first reference point for most traders. 1024EX emerges directly from this shift.

Rather than positioning itself as a high-end terminal for a small group of professional institutions, 1024EX is built around a broader question:

As AI becomes deeply embedded in trading decision-making, does the trading system itself have the structural capacity to support this transformation?

The central question today is no longer whether AI exists, but whether AI-generated decisions can actually be executed effectively.

A growing number of retail and professional traders already rely on AI for:

• Rapid synthesis of market and macroeconomic information

• Directional trade ideation and thesis formation

• Strategy logic design and conditional triggers

Yet on most trading platforms, AI remains confined to the “advisory layer.” Once a decision reaches execution, traders still face fragmented product structures, limited order capabilities, and execution environments that cannot be automated.

1024EX is built on a clear premise:

As trading decisions increasingly originate from AI, trading platforms themselves must become systems that AI can operate—not merely interfaces designed for human clicks.

1024EX’s “AI & Quant-Native” design does not treat models and strategies as add-ons. Instead, it assumes at the system level that automation, conditional logic, and structured risk management will become the norm in trading.

As a result, 1024EX does not compete on surface-level features. It is engineered around more fundamental qualities of trading experience: low-latency feedback, predictable system behavior, and consistency under high volatility and heavy load.

This produces two important outcomes:

• For advanced users and quantitative teams, AI-generated rules and strategies map naturally into on-chain execution;

• For retail traders, even without writing strategies themselves, trading behavior is implicitly shaped by AI-driven and rule-based structures, without requiring deep technical understanding.

In other words, 1024EX is not asking everyone to become a quant—it is making quantitative characteristics native to how more people trade.

1024EX is not built on a general-purpose blockchain. It runs on 1024Chain, a Layer 1 designed specifically for high-frequency financial workloads.

Key performance metrics disclosed include:

• Average block time: ~0.07 seconds

• Peak throughput: 2,000,000+ TPS

• Approximately 10× Solana’s performance under comparable conditions

These numbers matter not because they are “faster,” but because they reflect a structural shift:

On-chain trading systems can now sustain the response density and concurrency stability required by AI-generated decisions.

When AI outputs conditional and structured logic, any delay or instability in state updates turns the execution layer into a bottleneck. The performance characteristics of 1024Chain allow the AI → strategy → execution loop to function coherently on-chain for the first time.

On most platforms, spot, perpetuals, options, and prediction markets exist as isolated modules. Even when AI produces cross-market insights, those insights cannot be fully expressed within a single system.

1024EX takes a different approach: spot, perpetuals, options, and prediction markets are unified under a single on-chain architecture.

Within this system:

• Spot markets enable immediate price discovery

• Perpetual contracts express leveraged expectations and funding dynamics

• Options capture nonlinear risk and volatility structures

• Prediction markets incorporate probabilistic pricing of discrete events

This unified structure allows multi-dimensional, AI-generated views to be executed directly in one market environment—without being decomposed across platforms.

As AI becomes the dominant source of trading insight, traditional asset-class boundaries are eroding. Macro events, interest rates, geopolitics, and technology cycles increasingly impact equities, commodities, and crypto simultaneously.

1024EX’s multi-asset perpetual roadmap reflects this reality, covering:

• Crypto spot and perpetuals

• Equity indices and technology stocks

• Precious metals, energy, and commodities

• FX and interest-rate–related products

Through unified margining and execution, traders can express AI-driven, cross-asset views within a single platform—without reliance on legacy account structures or geographic constraints.

The design principle behind 1024EX’s execution layer is clear: AI- or strategy-generated decisions must be expressed fully and precisely, not degraded at the execution stage.

As AI becomes deeply embedded in trading decisions, a long-overlooked issue is emerging:

Most AI-generated trade recommendations implicitly assume the presence of institutional-grade order types and execution algorithms.

In traditional finance, this assumption holds. Exchanges like CME and NASDAQ, and brokerage platforms such as IBKR, natively support rich order semantics and execution algorithms, allowing strategies to be implemented with precision rather than constrained by platform limitations.

In contrast, crypto markets face a persistent structural gap:

• Most CEXs and DEXs support only a narrow set of basic orders

• Standard TradFi execution algorithms are largely unavailable

• The more professional and AI-dependent a strategy becomes, the greater the execution loss

This leads to an unavoidable conclusion:

As AI increasingly drives trading decisions, underpowered execution tools create an inherent unfairness for crypto traders.

1024EX is designed to close this gap by supporting a progressive spectrum of execution capabilities, including:

• Stop / Take-Profit (Market & Limit)

• Trailing Stops

• OCO and Bracket Orders

• Iceberg, Scale, and Pegged Orders

• TWAP, VWAP, and POV algorithms

• Composable conditional and logic-based orders

These tools are not about complexity for its own sake. They ensure that AI-generated views—directional, conditional, or portfolio-based—can be executed in a manner comparable to professional traditional markets.

Their shared purpose is to transform risk control, trading discipline, and execution logic from personal habit into systematically reproducible structures.

Beyond serving traders, 1024EX is also designed as a developer-native platform for strategies and AI agents.

As AI and Web3 converge, trading logic increasingly originates from strategies, models, and agents rather than individual accounts. The core question is no longer whether strategies can be written, but whether they have a native lifecycle for development, deployment, distribution, and monetization.

Through the 1024 Quant framework, 1024EX provides an end-to-end solution:

• Native quantitative and AI support within the trading interface, including function calling and visual analysis directly on price charts

• Strategy Store, where developers can publish strategies or AI agents for others to use

• Coding Agent & Online IDE, enabling development, testing, and iteration directly on the platform

• Open-source projects and developer SDKs, supporting broader ecosystem collaboration

Within this system, development, trading, distribution, monetization, and data accumulation form a single closed loop—allowing AI strategies to operate on-chain, be adopted by users, and continuously improve.

As AI becomes deeply involved in trading decisions, platforms are no longer just execution venues—they become part of decision quality itself.

An observable shift is already underway: many retail traders now interact with AI using natural language—asking for market views, constructing strategies, and defining risk conditions. Yet on most exchanges, these insights collapse into severely limited execution options.

1024EX aims to eliminate this disconnect by enabling users to invoke institutional-grade trading capabilities through natural language interaction.

On 1024EX, complex institutional operations—conditional triggers, portfolio-level risk controls, and execution algorithms—no longer require traditional professional backgrounds. They are accessed through more intuitive, human-centric interaction.

At its core, this represents a long-overdue principle: financial inclusion.

• Giving retail traders their first exposure to institutional-grade tools

• Making quantitative and systematic capabilities broadly accessible

• Reducing the extent to which trading outcomes depend on institutional status or privileged access

If quantitative trading has long been the most brilliant yet inaccessible jewel at the peak of Wall Street, then 1024EX’s ambition is Promethean in nature: to bring that jewel down from the summit and place it in the hands of everyday traders.

The resulting psychological shift is profound:

Users of 1024EX no longer feel like mere market participants—they feel equipped with capabilities once reserved for institutions.

This perception, more than short-term incentives, drives organic adoption and long-term retention.

As AI becomes the primary source of trading decisions, the true dividing line is no longer who has better insights, but:

Whether trading platforms themselves are capable of executing those insights in full.

In traditional finance, this problem was solved long ago. Institutional order types, execution algorithms, and structured risk systems became baseline infrastructure. Strategies could be expressed precisely, without degradation at execution.

In crypto markets, this layer has been largely absent. Many CEXs and DEXs remain constrained by limited execution models, causing the most sophisticated and AI-driven decisions to suffer the greatest loss at the point of execution.

1024EX is built to address this structural gap—bringing mature trading structures and execution capabilities from traditional finance onto the blockchain, so that AI-generated decisions are fully expressed rather than constrained by platform limitations.

In the AI era, traders do not just need smarter sources of insight. They need a trading entry point worthy of those insights and capable of keeping pace with them. 1024EX is designed to be that entry point.

https://www.1024ex.com