Every enterprise has them — complex business calculations buried in spreadsheets, legacy systems, or worse, someone's head. Pricing formulas, compliance calculations, insurance premiums, tax computations. These calculations are critical but often fragile, undocumented, and impossible to maintain.

We've been exploring a powerful approach that combines AI with JSON Logic to transform these calculations into automated, maintainable, and auditable rule engines.

The Problem with Traditional Approaches

Most business calculations live in one of three places:

Spreadsheets: Flexible but fragile. No version control, no audit trail, prone to human error
Hard-coded logic: Embedded in application code. Every change requires a developer, testing, and deployment
Legacy rules engines: Complex, expensive, and often require specialized knowledge to maintain

All three approaches share a common flaw: the business logic is tightly coupled to its implementation.

Enter JSON Logic

JSON Logic is a simple, declarative format for expressing business rules as JSON. It's human-readable, machine-executable, and infinitely portable. Here's a simple example:

A pricing rule that gives a 10% discount for orders over $1,000 can be expressed as a JSON structure with conditions and actions. The beauty is that this rule can be stored in a database, version-controlled, modified by non-developers through a UI, and executed on any platform.

Where AI Comes In

Here's where it gets interesting. We use AI to:

1. Extract Rules from Legacy Systems Feed your existing spreadsheet formulas, policy documents, or code to an AI model. It can identify the business rules, edge cases, and exceptions — then generate the corresponding JSON Logic rules.

2. Generate Rules from Natural Language Business stakeholders describe rules in plain English: "If the customer is in Kenya and the order is over KES 50,000, apply a 5% loyalty discount unless they have an outstanding balance." AI translates this into executable JSON Logic.

3. Validate and Test Rules AI can generate comprehensive test cases, identify conflicting rules, and flag edge cases that humans might miss. It can simulate thousands of scenarios in seconds.

4. Optimize Rule Sets Over time, AI analyzes execution patterns and suggests optimizations — simplifying redundant rules, identifying unused conditions, and improving performance.

Real-World Applications

We've applied this approach across several domains:

Healthcare (EVV Compliance): Automated visit verification calculations for 21st Century Cures Act compliance. What was a manual process involving 15+ rules per visit is now instant and error-free.

Insurance: Premium calculation engines that previously required actuarial specialists to modify can now be updated by business analysts through a visual interface.

E-Commerce: Dynamic pricing rules that consider inventory levels, competitor pricing, customer segments, and seasonal factors — all expressed as composable JSON Logic rules.

The Architecture

Our typical implementation looks like this:

•Rule Editor UI: Visual interface for creating and modifying rules (built with React)
•Rule Engine: Server-side JSON Logic evaluation engine (Node.js)
•AI Layer: GPT-based model for rule generation, validation, and optimization
•Audit Trail: Complete version history of every rule change with who, when, and why
•Testing Framework: Automated test generation and regression testing for rule sets

Getting Started

The path to automated business calculations starts with three questions:

Where are your most complex business rules today?
How often do they change?
What's the cost of getting them wrong?

If the answers are "spreadsheets," "frequently," and "significant" — you're a perfect candidate for this approach.

At IntelliByte, we've built this capability into our AI solutions practice. We can take your existing business rules — however they're documented — and transform them into automated, maintainable, AI-enhanced calculation engines.

The era of fragile spreadsheets and hard-coded business logic is ending. The future is declarative, AI-enhanced, and auditable.