Confident Decisions Begin with Proof
Partner with our elite team of Pega Certified Lead System Architects (CLSA) for a free consultation and a fully tailored proof of concept (POC)—crafted to fit your unique business needs. Whether you're looking to build a core Pega application, an AI-powered CDH strategy, or a seamless Pega Customer Service solution, we've got you covered.
Our no-cost POC gives you a hands-on preview of what's possible—demonstrating real-world outcomes like faster time-to-market, reduced operational costs, and smarter customer engagement. From idea validation to architecture advisory, our CLSAs work closely with you to deliver clarity, confidence, and results—before you spend a single dollar.
Dynamic case management with SLA-driven workflows Data modeling and reusable integrations (REST, SOAP, Kafka, etc.) Declarative rules, decision tables, and UI-driven design DevOps pipelines with Deployment Manager and branch-based development Reusable assets for scaling across business units
Next-Best-Action design with arbitration, treatments, and channels AI/ML model configuration and outcome-based learning Always-on decisioning integrated with inbound and outbound channels Customer Profile Designer and decision data integration Simulation, diagnostics, and performance insights
Unified agent desktop with guided workflows Pre-configured service cases (address change, disputes, billing, etc.) Knowledge management, intent detection, and real-time agent assist IVR, chat, email, and social channel integration Interaction history, wrap-up automation, and analytics
Assessment of current on-prem or self-managed environments Migration to Pega Cloud with minimal disruption Readiness analysis, rule optimization, and guardrail compliance Performance tuning and scalability improvements post-migration Cloud-native enablement (e.g., Kubernetes, Dockerized services)
Assessment of current on-prem or self-managed environments Migration to Pega Cloud with minimal disruption Readiness analysis, rule optimization, and guardrail compliance Performance tuning and scalability improvements post-migration Cloud-native enablement (e.g., Kubernetes, Dockerized services)
Assessment of current on-prem or self-managed environments Migration to Pega Cloud with minimal disruption Readiness analysis, rule optimization, and guardrail compliance Performance tuning and scalability improvements post-migration Cloud-native enablement (e.g., Kubernetes, Dockerized services)
At Rule Dynamix, we don’t just follow the evolution of intelligence—we engineer it. While today’s AI excels at pattern recognition, decision automation, and predictive analytics using deep learning, reinforcement learning, and knowledge graphs, we’re already laying the groundwork for the next frontier: Artificial Super Intelligence (ASI). ASI will not only reason autonomously and self-optimize across domains—it will dynamically generate hypotheses, orchestrate multi-agent collaboration, and architect its own learning pathways in real time.
Our solutions bridge present-day intelligence with future capability. We design intelligent automation frameworks, neuro-symbolic systems, and cognitive agents capable of continuous learning, real-world reasoning, and complex decision chains. Leveraging state-of-the-art techniques in transformer-based architectures, federated learning, edge inference, and explainable AI (XAI), we deliver systems that are not only smart but also transparent, scalable, and adaptive.
At Rule Dynamix, we are building AI that is self-aware of its performance, capable of ethical decision-making, and designed with embedded alignment frameworks to ensure safety, compliance, and control. From automating enterprise workflows to constructing AI ecosystems with the cognitive flexibility to evolve, we are leading the transition from narrow AI to purpose-driven ASI—with foresight, precision, and responsibility at the core. Below is just a preview of what we are doing with AI.
Cognitive Process Automation (CPA) Combine deep learning, NLP, and process mining to build autonomous systems that can understand, reason, and act—beyond rule-based RPA. Cognitive agents can learn from case history, user behavior, and feedback loops.
Fine-tune or build custom neural networks for image recognition, anomaly detection, and time-series forecasting using frameworks like PyTorch, Keras, and TensorFlow.
Build Explainable AI (XAI) layers to make model decisions transparent. Ensure compliance with data privacy laws (GDPR, CCPA) using differential privacy, fairness metrics, and adversarial robustness testing.
Develop models that interpret and integrate multiple data types—text, audio, images, video—for enriched decision-making. Useful for customer sentiment analysis, intelligent claims processing, and security systems. These systems enable holistic intelligence by understanding context across channels, improving accuracy and responsiveness in real-world scenarios.
Deploy compressed, low-latency AI models at the edge (e.g., mobile devices, IoT sensors, field equipment) to enable real-time inference without relying on the cloud. This empowers autonomous decision-making at the source, reducing latency, preserving data privacy, and enabling always-on intelligence in bandwidth-constrained environments.
Create custom generative models (text, code, images) and deploy domain-specific autonomous agents capable of learning and evolving within bounded environments. Integrate with LLMs (e.g., GPT-4, Claude, Gemini) via secure APIs.
Integrate multiple predictive models (e.g., fraud, churn, conversion, intent) into a single decision engine using model fusion and ensemble techniques. Deploy stacked models with dynamic weighting based on confidence scores or context.
Analyze event logs to map, discover, and optimize business processes using AI/ML. Predict bottlenecks, recommend automation, and simulate process outcomes with minimal manual input.
Develop tailored AI transformation blueprints for large-scale adoption—balancing innovation with governance, architecture with execution, and experimentation with ROI.
Whether you're automating workflows with Core Pega, deploying Customer Decision Hub to drive contextual engagement, or modernizing service operations with Pega Customer Service and AI assistants, our tool breaks down:
• Cost savings from reduced manual effort
• Efficiency gains from improved SLAs and resolution times
• Revenue uplift from predictive engagement and next-best-action strategies
• Operational value from cloud-native scalability and system consolidation
Tailored by industry and use case, the Rule Dynamix ROI tool gives you the insights to build a rock-solid business case—and move forward with confidence.
From AI-driven insights to end-to-end Pega automation, we don’t just modernize—we future-proof.
Let’s build what’s next, together.