Rule engine

Idea §

The idea is to take complex un-structured data, convert it to simple primitive data types (usually called features or facts). And then have a logical rule which can run with the set of features/facts & evaluate if the rule is true or not.

Rule engine’s excel when you have a complex discrete function to compute to decide if it evaluates or not. This will be more clear with examples explained below.

Use cases §

Deciding on user status §

Let’s say you have a user object with around five statues. And let’s say the user status is decided on a combination of data points like:

• if the user updated name, gender and other basic information. move the user from INITIATED to VERIFICATION_PENDING.
• if the admin approves the data and confirms that the data is valid. move the user from VERIFICATION_PENDING to VERIFIED. In this case, the function is discrete in the sense that the result is one of three states. And a rule for each state would solve the issue of structuring the business domain rule in a way business people can visualize, edit & back test the rule.

Deciding on user loan eligibility §

Let’s say you are running a fin-tech which gives out loans. Deciding if a user is eligible for a loan or not is a discrete function with a bool output. Having a complex, large rule which uses hundreds of features for rejection helps in structuring the domain complexity in a way both business & engineering can manage it better.

Building it from scratch §

We’ve built a simple rule engine from scratch over at From scratch.

Battle tested libraries §

• json-rules-engine: Javascript library in which rules are written in JSON, this is extremely useful if you want to to store and version rules in the database.