Security, availability, and confidentiality - independently audited to meet enterprise data protection standards.
ReactorCX was built for complexity. That turned out to be exactly what AI needs to work at depth.
ReactorCX was built API-first, fully programmable, and open at every layer. Every rule, earn rate, tier threshold, and reward definition is structured and directly accessible through the same infrastructure your systems already use.
That architectural discipline - built for enterprise reliability and scale - is exactly what AI needs to reason about loyalty programs with depth and precision. The platform speaks the language AI speaks natively: structured data, machine-readable rules, and well-defined API contracts.
When AI connects to ReactorCX through the Model Context Protocol, it reads your program the way an engineer would: rule conditions, tier qualification logic, version history, earn rate structures.
The platform was already built to be read that way. ReactorCX's structured, machine-readable configuration gives AI complete program context, turning architectural discipline into operational intelligence.
Every loyalty program runs on trust: with members, with finance, with compliance. ReactorCX keeps a human in the loop at every decision point. AI brings the analysis. Your team makes the call. The engine executes with precision.
AI reads your live program configuration - earn rules, tier thresholds, and campaign logic - and surfaces insights your team would otherwise spend hours finding. It flags configuration gaps, rule conflicts, and what to address next.
Your marketer reviews the insight in plain language, asking follow-up questions, stress-testing assumptions, and refining the approach. AI responds with reasoning grounded in your actual data.
Once direction is set, AI drafts the full structured change - a promotion update or rule modification - complete with projected cost impact, affected members, and a summary ready for sign-off.
Your team gives the final sign-off. Only then does the platform engine execute - with full precision, full audit trail, and zero ambiguity. Every point awarded, every rule change is logged and traceable.
Two distinct capabilities. One integrated platform.
Neither replaces the other.
Think of it as assisted driving, not self-driving, for loyalty. When a misconfigured rule can burn through millions in points before anyone catches it, you want human hands on the wheel.
AI capability embedded at every stage of the loyalty lifecycle,
from initial program design through continuous optimization.
Your team describes what they want in plain language. The AI reads your live program configuration, maps intent to the correct rules and promotion mechanics, and returns a fully structured proposal for review.
Before a promotion goes live, the AI models member participation, projects cost, identifies rule conflicts, and flags anything likely to behave unexpectedly at scale. Analysis that used to require an analyst and a spreadsheet runs in a conversation.
Ask your program anything in plain language. Earn rates across properties, tier qualification thresholds, what a specific member earned last month and why. The AI reads the same configuration data your engineers do, returned in plain language.
The AI monitors program health, correlates transaction patterns against your configuration, and surfaces anomalies. Underperforming segments and misaligned earn rates get pushed to your dashboard before they become problems.
A member didn't receive points. A promotion didn't fire. The AI traces the full transaction path, identifies exactly where something failed, and tells you what to fix. Issues that took hours resolve in a conversation.
Call center teams get answers grounded in the member's actual program record, without escalating, querying a database, or waiting. Your team asks in plain language. The member gets an answer on the call.
Connect to your organization's preferred large language model. Your proprietary program data flows through your own approved infrastructure, governed by your own data handling policies.
AI reads the program the way it was always meant to be read: through explicit, machine-readable rules and models that document themselves.
How AI-ready enterprise loyalty works on a deterministic engine with an AI advisory layer.
ReactorCX AI is the AI Advisory Layer of the ReactorCX platform by Loyalty Methods. It combines a deterministic loyalty engine that handles every points calculation, tier qualification, and promotion evaluation with precision - and an AI Advisory Layer that accelerates configuration, surfaces insights, and suggests optimizations.
AI recommends, humans approve, the engine executes with precision.
The current product includes:
ReactorCX processes 2.6 billion transactions annually and has maintained zero downtime in production since 2018.
ReactorCX was built for enterprise complexity, not built around AI. Every rule, earn rate, tier threshold, and reward definition is structured and directly accessible through the same infrastructure client systems already use.
The platform was built API-first, fully programmable, and open at every layer - which is exactly what AI needs to reason about loyalty programs with depth and precision.
The architectural discipline required to operate enterprise-scale loyalty programs - explicit logic, structured configuration, observable behavior, embedded governance - turned out to be the same discipline that lets AI operate safely inside the platform without scaffolding.
Architecture and AI capability are the same discipline serving two purposes.
ReactorCX combines two distinct capabilities in one integrated platform. The deterministic engine handles points calculations, tier qualifications, discount arbitration, and promotion evaluation with mathematical precision and full audit trails.
The AI Advisory Layer provides intelligent guidance across the platform, surfaces recommendations, and helps program teams work faster.
AI never touches the calculations. The engine guarantees accuracy. The AI accelerates the humans operating it.
Think of it as assisted driving, not self-driving. When a misconfigured rule can burn through millions in points before anyone catches it, you want human hands on the wheel.
ReactorCX AI keeps a human in the loop at every decision point. Nothing executes without sign-off. AI does not touch the live program without explicit human approval - every time, no exceptions.
Every action is fully traceable, with the deterministic engine logging what ran, when, why, and who approved it.
AI handles the analysis. Marketers handle the decisions. The engine handles the execution.
This operating model protects enterprise programs against the kind of misconfigured rule that can burn through millions in points or create compliance issues if executed autonomously.
Yes. ReactorCX AI is multi-LLM by design and supports Bring Your Own LLM (BYOM). Clients can connect their organization's preferred large language model - including Claude, GPT-4o, Gemini, Grok, or their own internal models.
Proprietary program data flows through the client's own approved infrastructure, governed by the client's own data handling policies.
The RCX AI Server is the open book for any compliant enterprise AI agent, exposed through the Model Context Protocol (MCP). When an AI agent connects through MCP, it reads the program the way an engineer would: rule conditions, tier qualification logic, version history, earn rate structures, active promotions, member records, and transaction data.
ReactorCX's structured, machine-readable configuration gives AI complete program context. Any compliant enterprise AI agent - Claude, Gemini, Copilot, or custom - can connect and reason across the platform.
The platform was already built to be read that way. MCP did not require a new architecture - it required an open door.
The Loyalty World Model is the comprehensive, structured representation of the loyalty program that AI agents reason across. It includes configuration, runtime data, members, activities, partner integrations, NiFi flows, transaction logs, and rule dependencies.
Most loyalty AI operates on a narrow slice - a configuration chat or offer recommendations. The Loyalty World Model gives AI a comprehensive view of configuration, runtime behavior, integration state, and financial impact.
This is the difference between AI that can suggest a tweak to one rule and AI that can:
RCX Nexus is the next version of ReactorCX - a reimagined interface with AI agents embedded directly inside every workflow. Roadmap capabilities under the RCX Nexus umbrella include:
The foundation that Nexus productizes - the AI Assistant, MCP open book, Bring Your Own LLM, and the Loyalty World Model - is already in production today through ReactorCX AI.
Loyalty Methods does not put timelines on Nexus because the foundation is already shipping.
Loyalty Methods clients have moved promotion configuration from approximately one week to approximately one hour using Conversational Configuration in ReactorCX AI. The insight-to-action cycle has compressed from weeks to hours.
Program managers describe what they want in plain language, the AI reads the live program configuration and returns a fully structured proposal, and the marketing team reviews and approves before anything executes. The deterministic engine guarantees that what executes matches what was approved.
ReactorCX is SOC 2 Type II certified, with an independent audit by CertPro covering Security, Availability, Processing Integrity, Confidentiality, and Privacy controls. Loyalty Methods performs SOC 2 assessments on an annual basis.
AI operates within the same guardrails as the platform itself. It cannot bypass approval workflows, create untracked changes, or violate access controls.
Because governance is embedded architecturally, AI-assisted actions go through the same validation, audit trails, and approval gates as manual operations.
With Bring Your Own LLM, client program data flows through client-approved infrastructure under client data handling policies. Enterprise logging through AI routers provides cohesive observability.
ReactorCX AI runs across enterprise programs in every vertical Loyalty Methods serves:
Industry-specific AI examples in production:
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