We live in a world where instant gratification is expected.  From processing loan applications instantly, dynamically routing logistics, to reacting to cybersecurity threats in milliseconds, modern enterprises need systems that respond immediately and intelligently. Traditional monolithic applications, burdened by rigid execution models and batch processing, simply can’t keep up.

Enter FlowWright: an enterprise Business Process Management (BPM) platform designed for event-driven, microservice-based architectures. Our platform breaks the chains of monolithic orchestration by leveraging decision tables and microservices to deliver scalable, in-memory workflows capable of real-time execution. This article takes a look at how we transform process automation with real-time responsiveness, and why it's the right choice over legacy BPM systems.

Ho to Go From Legacy to Real-Time Processing

Legacy Monoliths: Traditional BPM solutions operate as large, tightly coupled monoliths. They follow rigid, synchronous process models with limited real-time capabilities. Every process change requires redeployment, and scaling is often expensive and error-prone. Batch-based processing and slow decision-making inhibit innovation and agility.

Today's Demands: Organizations are moving towards reactive systems—architectures built around asynchronous messaging, microservices, and intelligent decisioning. This shift enables immediate responses to events, real-time processing of data, and business agility.

Our Response: Our software is designed from the ground up for real-time operations. Its in-memory process engine, microservices orchestration capabilities, and AI-enhanced decision tables provide a modern alternative to traditional BPM platforms like Pega or Appian.

Microservices-Driven Workflow Automation

Microservices offer modularity, scalability, and autonomy. But orchestrating them efficiently is the real challenge—especially when business logic spans multiple services.

1. Event-Driven Architecture

FlowWright supports event-driven orchestration natively. Every process is executed in-memory, triggered by events such as API calls, database updates, sensor inputs, or external queues (like Kafka or RabbitMQ). This results in:

• Low latency processing (sub-second reaction time)
• Stateless microservice invocations managed via workflow state
• Parallel execution of services using branch/split patterns
• Scalable throughput by auto-scaling process instances

Unlike legacy engines that rely on polling or scheduled execution, FlowWright’s workflows are reactive—they execute as soon as an event is detected.

2. Dynamic Microservice Binding

Rather than hardcoding microservice endpoints, FlowWright allows you to dynamically bind services to process steps at runtime. Using service connectors, developers can orchestrate REST, SOAP, GraphQL, and gRPC services across environments with:

• Dynamic parameter mapping
• Support for retries, timeouts, and circuit breakers
• Conditional routing based on responses
• API authentication (OAuth, API keys, JWT)

This allows true separation of business logic (defined in workflows) from the implementation details of services, supporting rapid iteration.

3. Granular Control with Subprocesses

FlowWright supports nested subprocesses and micro-flows, enabling decomposition of large processes into reusable components. These subprocesses can:

• Execute in-memory within the parent process
• Be versioned independently
• Accept and return parameters asynchronously
• Be deployed across microservices

This modularity aligns with microservice design principles and makes testing and scaling easier.

How to Use Decision Tables for Business Logic

Decision tables are at the heart of real-time rule evaluation. In FlowWright, they act as lightweight, fast-executing engines that decouple logic from code. Unlike BPM engines that rely on slow, monolithic rule evaluators, FlowWright executes decision tables in-memory—ensuring sub-millisecond performance.

Example Use Cases:

• Loan Approvals: Instantly decide approval tiers based on FICO score, income, and credit history.
• Shipping Logistics: Route packages dynamically based on distance, cost, and delivery window.
• Security: Block, route, or log events based on real-time user behavior analytics.

Benefits:

• No code: Build and edit rules via UI
• Version control: Promote rule sets through environments
• Hot swap: Update rules without redeploying workflows
• Scalable: Handle millions of rule evaluations per second

Together with workflows, decision tables become powerful agents of change—enabling logic-driven routing, validation, pricing, and classification in milliseconds.

Micro-services In Practice: Instant Insurance Claim Routing

Let’s walk through a real-world use case where FlowWright’s event-driven microservice orchestration outperforms traditional BPM.

The Challenge

An insurance company wants to route auto-claims instantly based on:

• Claim severity
• Customer history
• Fraud detection score
• Policy type

Legacy BPM solutions require nightly batch jobs to classify and forward claims, leading to delays and missed SLAs.

The Solution

1. Event Trigger: A claim file lands in Azure Blob Storage → FlowWright detects it via listener.
2. In-Memory Process: A workflow instance is spun up instantly.
3. Microservices Called:

• Claim normalization microservice (REST)
• Fraud detection service (Python on AWS Lambda)
• Customer scoring (external CRM)

1. Decision Table:

• Evaluates fraud score, severity, and customer tier
• Routes claim to adjuster pool, fast-track payment, or special investigation

1. Completion: All done in under 1 second—fully automated, fully real-time.

This orchestration spans multiple microservices, includes business rule evaluation, and handles fault tolerance—all in-memory with no database lag.

Top Architectural Advantages

1. In-Memory Execution Engine

FlowWright doesn’t need to write every step to a database before moving forward. This unlocks:

• Sub-second processing
• No I/O bottlenecks
• Efficient parallelism
• Stateless service calls with stateful orchestration

In-memory execution is especially crucial in latency-sensitive environments like manufacturing, fintech, or IoT.

2. Hot Deployment & Versioning

Update workflows and decision tables on the fly with zero downtime:

• Publish new workflow versions
• Migrate running instances
• Backward-compatible subprocesses

This allows DevOps to make fast iterations and CI/CD pipelines to push updates without disrupting live operations.

3. Observability & Logging

Each microservice interaction, decision outcome, and state transition is logged with:

• Full trace IDs (OpenTelemetry compatible)
• Visual process audit trails
• API response snapshots
• Reprocessing capabilities

This ensures end-to-end transparency for debugging, compliance, and analytics.

Why FlowWright Wins Across Global Enterprises

Our platform isn't just a workflow engine—it's an intelligent orchestration platform built for real-time operations. By combining:

• In-memory process execution
• Microservice orchestration
• Decision tables for intelligent routing
• Full API exposure for integration

FlowWright positions itself as a foundational layer for digital transformation. When milliseconds matter, when systems need to talk across clouds, and when decisions must be instant—FlowWright delivers.

Real-time processing and microservices orchestration are no longer futuristic ambitions—they’re operational necessities. Legacy BPM tools fail to meet these demands due to outdated architectures. FlowWright, on the other hand, embraces patterns like event-driven execution, dynamic microservices integration, and intelligent decisioning.

Schedule a demo to explore our microservices capabilities and discover we can help your team and business scale using workflow automation.