VisiRule Business Rules Engine
Graphical Business Rules Engines
VisiRule provides a robust Business Rules Engine set within a graphical decision environment. Authors can create and deliver applications by drawing decision making charts and exploit both forward and backwards business rules engines.
Business Rules Engines are software systems that help organizations automate their decision-making process.
Complex knowledge can be represented clearly and elegantly in decision tree software diagrams. VisiRule extends this by offering a dedicated English-like rules language.
Business Rule Engines & Management Systems naturally separate business logic from executable code in order to gain agility and resilience.
Users can capture business logic visually without coding and implement changes independent of application specific code. This enables greater business clarity and higher degree of maintainability. When combined with RPA, this helps deliver Decision Automation & Intelligent Automation.
What is a Business Rule Engine?
A Business Rule Engine is a software system designed to automate decision-making processes. It helps businesses create automated policies and rules that govern the delivery of products or services, as well as customer relations. Business rule engines can be tailored to a company’s individual needs and are typically used for creating workflow management systems or optimizing customer interactions.
VisiRule encourages authors to represent business process models in a clean, graphical manner using logical expressions to control the execution flow. This enables business professionals to capture, share, discuss, test and automate their business's decision-making processes in a coherent and transparent way.
Business Rule Engines can be used in many parts of organizations, wherever there are clearly defined methods which underpin some decision process. Automation requires clearly defined rules and a dedicated business rule engine.
Incorporating Machine Learning
By incorporating Machine Learning technology, VisiRule FastChart allows charts to be generated from data and then updated and annotated by human experts. Rules used to create the chart are inferred or induced using information gain and entropy.
VisiRule’s approach of "programming via flow charting” permits rapid prototyping and review, and greatly enhances the accurate capture and shared understanding of decision flows. The ability to represent complex decisions in layers enables the decision rules engine to make high quality, transparent decisions.
Intelligent Automation & VisiRule Business Rules
VisiRule can create automated documents in various formats such as text, PDF, XML, HTML and RTF using the answers gathered and calculations computed in the session.
VisiRule can combine complex logic with conditional text selection and insertion.
Documents can be created one at a time or en masse via a data driven process.
Advantages of Using Business Rule Engines
The use of business rule engines offers many advantages. It can significantly reduce manual processes and time costs, helping a company be more efficient. It can also provide a better customer experience by helping companies tailor interactions with customers based on their needs and preferences. Additionally, it helps companies ensure compliance with regulations and laws by making it easier to quickly set up rules that govern interactions.
Understanding the Components of a Rule Engine
A rule engine is composed of three core components. The first component is the rules repository, which stores all relevant rules and associated data. Then there is the management layer which interprets the rule set and ensures consistency across multiple departmental functions. Finally, there is the execution layer which evaluates conditions and activates rules as needed in order to automate processes or provide guidance for decision-making.
Knowing How to Analyze Business Rules for Efficiency
The goal of analyzing business rules is to ensure they remain as efficient and current as possible with the market changes. By analyzing existing business rules and testing new ones, you can develop a knowledge base that is accurate and as concise as possible. This will give you more control over the automation process, which ultimately leads to improved efficiency and consistency for your organization.
Automating Your Decision Making Process with Rules
Business Rule Engines can be used to automate your decision-making process by creating a set of rules that govern how the system should respond. This allows the engine to make decisions, rather than relying on manual input from the user. It can also be used to optimize workflows and processes, as well as expand beyond existing customer profiles to reach new customers more effectively.
Business Rule Automation Tools
Popular target areas for rules-based automation include sales configuration and quotation, insurance underwriting and claims eligibility, financial loan evaluation, robo-advice and robo-lawyer, and also manufacturing and engineering scheduling and support. The VisiRule Business Rules Engine enable business rules to run both interactively, i.e. "question and answer driven" or fully automated, i.e. "data-driven" and mixed, i.e. a hybrid Digital Decisioning Platform.
Rule automation tools are an invaluable addition to a business's workflow, offering improved accuracy and effectiveness. With the help of these tools, businesses can reduce manual labor, increase efficiency and accuracy, and gain access to powerful analytics about their processes.
Automating rules expedites the process of making business decisions and ensures accuracy. Automated rules are reliable and consistent in their application, which can save your business time and resources. Furthermore, automating your rules reduces manual labor, freeing up valuable staff resources to focus on other tasks.
Automating rules can help you make decisions and act upon them quickly, without having to wait for approval or consultation with your team. This improved the speed and efficiency of the decision-making process, freeing up time for other activities. Furthermore, automated rules may be able to access data faster than a manual approach, providing better accuracy and timeliness in your decision-making process.
Automating rules gives you an efficient and cost-effective solution to reduce mistakes. By setting clear, automated rules around decision making, you can guarantee that decisions are taken based on the most up-to-date information available. This reduces human error and therefore minimises risk for your business. Additionally, automating your processes reduces the need for labour costs and saves time - leading to money saved overall.
Enhanced Quality & Consistency
Automating rules can ensure that your business runs the same way each time, with a higher quality of control. No longer will you have to worry about random mistakes occurring due to human error. This can lead to improved customer satisfaction, making your customers happy and increasing repeat sales. Automated rule making also allows for increased safety within the workplace by ensuring that tasks are conducted in an appropriate manner.
Testing & Validation Framework
VisiRule provides a powerful testing framework so that you can see the effect of your rules in various different data-driven scenarios. Furthermore, by including a "compare test results" component, VisiRule AutoAudit also supports regression testing.
Business Process Automation
VisiRule can be used to model various tasks and drive them in an automated fashion using exposed end-points and shared payloads as found in Decision Engineering.
Modularity & Multiple Charts
To enable manageability and scalability, decision models can be split across multiple VisiRule charts and files. This means the development of large models can be shared between multiple authors. Individual charts can be developed and tested on their own, and then combined within a larger framework.
VisiRule REST Services
You can deploy your VisiRule application using Windows containers. Containers provide the tools to organize and build micro-services. They wrap the VisiRule application up within in a complete file system that contains everything it needs to run:the code, run-time rule engine, system tools and system libraries. This guarantees that it will always run the same, regardless of the environment in which it runs. Containers can be deployed on-premises or as a hosted service.
High-Performance Business Rule Engine
The high-performance VisiRule rule engine is capable of handling over 100K rules in 1 minute on a 2 server installation. As more servers are commissioned, this increases.
Business Rules Engine Integration
Big Data Decision Making Engines
VisiRule can access data in almost any database system both RDMS (SqlServer, Oracle, MySQL, SAP, Access) and NoSQL such as Redis. VisiRule can receive data from spreadsheets (Excel), text files and remote devices (SCADA etc). VisiRule is a Big Data Rules Engine. When coupled with tools such as Azure IoT Hub and the Azure Event Grid, VisiRule can provide intelligent support for IOT.
VisiRule Mapper provides a UI to map questions on to fields in external tables, so that rather than be asked, they are answered by using existing data. Computed output can be sent back to the screen, uploaded to a server or written back into a database.
Explaining Automated Decision-Making
Each decision point leaves a marker. By collecting up all these markers, and the values used to determine them, it is possible to reconstruct the reasoning behind how a conclusion was reached based on the data used. VisiRule can produce a justifiable explanation for its decisions. This is essential to produce transparent and trustworthy systems. Contrast this to neural nets which can NOT offer explanations as to how a decision was reached and are very much an unaccountable 'black boxes'.
Decision Visualization & Decision Analytics
Each visitor leaves a footprint of their visit, the path they took, the answers used, rules fired and the conclusion reached. VisiRule collects these. You can visualize and analyze this traffic to gain insight into a chart's performance, and learn how to improve it based on actual usage.
Multi-layered Engine Architecture
VisiRule generates executable rules in terms of the Flex expert systems toolkit. Flex supports both forwards and backward chaining rules, frames, slots, actions, groups and uses an English like Knowledge Specification Language (KSL) which you can use to define and invoke additional rules in Flex or Prolog. Flex is built on LPA Prolog, a well established logic-based AI language, which supports meta-reasoning and backtracking across alternate solutions. Prolog also supports recursion, list processing and backtracking to find alternate solutions.
Additional AI-based Tools from LPA
Flex supports frames, procedures, as well as, access to other programming languages such as Prolog, Python, C#, Java, VB and .NET. This provides for a multi-layer development environment. LPA also provide toolkits to support Data Mining and Case Based Reasoning. The high-performance LPA Business Rule Engine plus this wide range of rules tools and integration into back-end services, makes VisiRule+Flex+LPA Prolog a very powerful Digital Decisioning Platform.
Conditional Rules and Complex Expressions
Many automated Business Rules Engines only allow for simple rules, i.e. atomic tests. VisiRule provides a comprehensive set of logical operators which means the expressions and rules can be as simple or complicated as needed.
Powerful Maths and Logic Processing
VisiRule includes a powerful maths package and complete set of logical operators. This includes scientific maths functions and high-precision floating-point numbers. In addition, you can call code defined in other languages such as Python, C, etc.
Text Processing Capability
VisiRule includes a powerful package of text handling routines which enables you to parse, analysis and extract text from text fields and documents.
Business Rules Management System
Business rules management is focused on the administration and automation of business rules. Business rules are statements which describe a business policy or procedure. The goal of this approach is to improve the agility and responsiveness of the organization. Companies that are reply on business rules usually automate their decision processes, thus improving their efficiency and reliability. This means more autonomy without depending on the IT department every time there’s need to change the business logic.
Business Rules Engines & Management System
VisiRule supports the design, documentation and execution of the dense chain of reasoning that is a common feature of business rules engines, and, thanks to modern server farms, VisiRule solutions are scalable from internal users to outside business partners and customers. The VisiRule Rules Manager provides a layer of management. Integration with repositories such as BitBucket and GIT provide version control.
Separation of Code from Logic
The separation of operational business rules from the application code means that Business Rules can be managed, updated and maintained more easily without needing to change any program code, and by non-technical staff rather than programmers. The rules are executed by a dedicated high-performance Business Rules Engine. The resulting systems are more robust, resilient and adaptable.
Multiple Rules Engines
Backward Chaining Logic
VisiRule is a graphical tool which generates executable rules in the form of Flex backward-chaining rules as denoted by the KSL keyword 'relation'. These often labelled as goal driven. The logic-based engine supports complex logic which can be used to solve complex problems in a manner comparable to human experts.
Flex also supports forward-chaining production rules denoted by the keyword 'rule'. These are data driven. These are not represented graphically in VisiRule but can be introduced as in the insurance demo on the Financial Expert System Demos page.
Interleaved Forward and Backward Chaining
VisiRule/Flex supports both forward and backward chaining inferencing. You can interleave these, so that from within a forward-chaining session you can use backward chaining to establish local provability.
Read the article entitled "Forward Chaining vs. Backward Chaining in Artificial Intelligence" written by Parag Radke
Read how Charles Forgy describes the difference between Forward and Backward chaining.