ZeroMS applies real-time machine learning to order execution, enabling brokers to detect behaviour and adapt routing decisions instantly.
ZeroMS, the multi-location FIX 4.4 execution bridge developed by Equidity, applies real-time machine learning directly within the order execution path, enabling brokers to classify trading behaviour and adapt routing decisions at the moment of order entry.
The platform represents a structural shift in execution infrastructure. Instead of relying on post-trade analysis and manual intervention, ZeroMS embeds intelligence into the execution layer itself, allowing the system to respond to scalping, arbitrage, high-frequency activity, and other trading patterns in real time.
Further information is available at and https://equidity.com/zeroms.
A Market Defined by Legacy Constraints
The FIX bridge layer sits at the centre of broker infrastructure, controlling how client orders are routed, how liquidity is accessed, and how execution risk is managed. Despite its importance, the technology underpinning this layer has remained largely unchanged for over a decade.
Most existing bridge solutions operate within a framework defined by:
* static routing rules configured through text files
* limited real-time visibility into execution quality
* delayed reporting cycles for critical metrics
* manual workflows for updating execution strategies
* infrastructure tied to single data centre deployments
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These limitations create a disconnect between market conditions and execution decisions.
In practice, brokers often identify execution issues only after they have occurred. Slippage, rejection rates, latency spikes, and toxic flow patterns are typically analysed retrospectively, leaving limited opportunity to prevent their impact.
Machine Learning Embedded in Execution
ZeroMS introduces a different approach by embedding machine learning directly within the execution pipeline.
Every interaction within the system — including orders, fills, cancellations, session behaviour, and market conditions — is continuously evaluated. Based on this data, each trading account is assigned dynamic behavioural scores:
* Risk
* Toxicity
* Scalping behaviour
* Arbitrage characteristics
* High-frequency activity
These scores are recalculated continuously and used directly within execution decisions.
At the moment of order entry, behavioural data is evaluated and used to determine routing outcomes in microseconds.
From Reactive Operations to Continuous Adaptation
Traditional execution environments rely on delayed analysis and manual decision-making. Classification of trading behaviour often occurs after financial impact has already been realised.
ZeroMS replaces this approach with continuous evaluation and automated enforcement.
With real-time behavioural scoring:
* anomalies are detected within minutes rather than days
* routing decisions adapt instantly
* classification remains dynamic
* execution strategies evolve continuously
This allows brokers to move from reactive oversight to proactive execution control.
Competitive Landscape: A Structural Difference
The global FIX bridge market has historically been led by a small number of established providers, including PrimeXM, oneZero, Centroid, and FXCubic.
These platforms have played a significant role in standardising liquidity aggregation and FIX connectivity across the industry. However, their core architecture reflects an earlier generation of trading infrastructure.
Across most implementations, several characteristics remain consistent:
* routing logic is configured through static rule sets
* behavioural analysis is separated from execution
* configuration changes require manual processes or vendor involvement
* reporting is often delayed rather than real time
* infrastructure is tied to specific data centre deployments
While these systems provide stable connectivity, they do not incorporate behavioural intelligence directly into execution decisions.
ZeroMS introduces a structural distinction.
Rather than treating analytics, routing, and monitoring as separate layers, the platform integrates them into a unified execution environment. Behavioural scoring, routing logic, and real-time analytics operate as a single system, allowing execution to adapt continuously.
This integration represents a departure from the modular, configuration-driven approach that has defined the market.
Case Scenario: Managing Toxic Flow in Real Time
Consider a broker operating a multi-liquidity environment with a mix of retail clients and latency-sensitive traders.
Traditional Setup
In a conventional bridge environment:
1. A group of traders begins exploiting latency differences during high-impact news events
2. Orders are routed to external liquidity providers under standard execution rules
3. The broker experiences increased slippage costs and adverse fills
4. After several days, analysts identify abnormal performance patterns
5. A subset of accounts is flagged and moved to a different execution profile
6. By this point, the financial impact has already occurred
The process is inherently reactive.
ZeroMS Execution Model
Within ZeroMS:
1. The same traders begin exhibiting latency-sensitive behaviour
2. The system detects changes in execution timing, trade frequency, and win patterns in real time
3. Behavioural scores increase dynamically as patterns emerge
4. Routing logic automatically adjusts based on predefined policies
5. Orders from these accounts are redirected instantly to alternative execution paths
The response occurs at the moment of behaviour change, not after analysis.
Operational Impact
This difference produces measurable outcomes:
* reduced exposure to adverse flow
* elimination of manual classification delays
* consistent application of execution policies
* improved stability in liquidity relationships
The system does not rely on identifying specific accounts. Instead, it responds to behaviour itself.
Managing Behavioural Drift
Trader behaviour evolves over time.
Accounts that initially appear low-risk may later adopt opportunistic strategies. Conversely, aggressive traders may stabilise under different market conditions.
Static classification systems struggle to track these transitions.
ZeroMS continuously re-evaluates each account, ensuring that routing decisions remain aligned with current behaviour.
This reduces both under-filtering and over-filtering, enabling brokers to maintain precision in execution control.
Visual Execution and Instant Configuration
ZeroMS replaces configuration-driven workflows with a visual execution environment.
Operators can design routing logic through a web-based interface, including:
* A-Book, B-Book, and hybrid strategies
* multi-liquidity provider aggregation
* conditional routing rules based on behaviour, symbol, or volume
* latency-aware execution paths
All changes are applied instantly without system restarts.
This reduces operational friction and enables immediate response to market conditions.
Real-Time Visibility Across the Execution Stack
The platform provides full transparency across all operational layers, with live streaming of:
* order flow and execution latency
* liquidity provider performance and fill rates
* slippage and rejection analysis
* exposure and position monitoring
* FIX session activity and logs
This removes reliance on delayed reporting and allows issues to be addressed as they occur.
AI Copilot for Operational Intelligence
ZeroMS includes an embedded AI assistant, Copilot, designed to provide contextual understanding of trading activity.
Copilot enables operators to:
* analyse order-level execution outcomes
* identify underperforming liquidity providers
* assess client-level trading behaviour
* evaluate real-time exposure
The system retrieves and processes live data, delivering structured insights within seconds.
Copilot operates as a read-only system, ensuring that operational control remains with the broker.
Multi-Location Infrastructure Without Lock-In
ZeroMS supports deployment across major financial data centres, including LD4, FRA, NY4, and SG1.
Unlike traditional systems restricted to a single location, the platform enables seamless deployment and migration across regions.
This allows brokers to optimise execution geographically while maintaining operational continuity.
A New Category of Execution Infrastructure
By combining real-time machine learning, behavioural scoring, visual execution control, and AI-driven operational insight, ZeroMS represents a new category of execution infrastructure.
There is currently no bridge or execution engine in the forex market that integrates behavioural intelligence directly into execution while providing full real-time visibility within a single platform.
The result is a system where execution decisions are continuously informed, automatically applied, and fully observable.
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