Create Running System from Prompt in 1 Minute

Declarative Business Logic Rules

You Stay in Control

Full system from a prompt

Kickstart faster than Low Code

No Database Definition

No Screen Painting

Unique Declarative Business Logic

Spreadsheet-like Rules 40X more concise

Here now: Microsoft's future vision

Designed for Developers

Standard DB, Lang, Tools

Models - not FrankenCode

GenAI - with Governance

Try It Now - Free

At a Glance

The basic process is shown here:

Submit your business idea as a prompt into your browser.
The system creates a running system. Review and iterate to get the requirements right.
- Full Multi-table Systems: DB, App, API.

Not just a single page.

- Declarative Business Logic

Not just "your code here". See below.

- Governable Agentic GenAI

No hallucinations, rules are deterministic. Details here.

Download and customize in your IDE.

Exploring the diagram -- let's ask ChatGPT about GenAI-Logic 😉

SInce we are talking GenAI, we pasted the diagram above to ChatGPT, and asked it to summarize what it saw. It's response (unedited):

The image appears to be a workflow diagram illustrating a low-code/no-code development process for quickly building business applications using AI-generated logic and customization. Here’s a breakdown of what I see:

1. Idea (Left Panel)

• A user interface (Web-based AI tool) allows users to define their system using natural language.

• The prompt describes a business scenario with Customers, Orders, Items, and Products.

• It specifies business rules such as credit limits, order amounts, and item pricing.

• Highlights that the system can be generated and run in 1 minute with business logic automation.

2. Run (Top-Right Panels)

• The generated system includes a multi-page, multi-table web application.

• It provides an admin dashboard for managing customers, orders, and products.

• An API Logic Server is automatically created, exposing REST APIs for the system.

• The system appears to be functional and ready for use immediately after generation.

3. Customize (Bottom-Right Panel)

• A code editor (VS Code) shows Python-based declarative business logic.

• The logic enforces constraints (e.g., customer balance must not exceed credit limit).

• Debugging tools and breakpoints are visible, indicating that the user can inspect and modify the system behavior.

• A logic trace (console output) logs business rule execution, showing automated updates based on the defined logic.

Key Takeaways

• The process transforms a natural language description into a working application with APIs and business logic.

• Users can run and test the generated system immediately.

• Developers have full control to customize the logic via code.

• The tool supports rapid low-code development, particularly for database-driven business applications.

This workflow seems to be an example of AI-driven low-code development—likely related to GenAI Logic or similar technologies that generate database applications with embedded business rules.

Would you like a more detailed analysis or thoughts on how this could fit into your projects?

No Compromise Dev Tooling

Automation should not preclude the use of valuable tools:

Projects are standard directories (details here) you can open in your IDE - use Code Editors, Debuggers, etc. GenAI Code Helpers too.
Customize using Python and libraries
Standard SQL Databases
Standard Container deployment

As shown at right, this means you can customize the logic, the API, add custom apps, etc.

UI Dev Unblocked: Automatic API Creation

A common issue for dev teams is that the UI team is blocked, waiting on API dev. This serializes development, and increases stress on the UI team.

With GenAI-Logic, your prototype includes a complete JSON:API. Your dev teams - and app integration teams - can begin immediately.

Models - Not FrankenCode

The Problem: Excessive Code Generation is hard to understand and customize

Programmers are understandably wary of code generators. These often take simple inputs, and create hundreds / thousands of lines of code. The automation is nice, but understanding and customizing the generated code can be a nightmare. FrankenCode.

Why can't we just run the cocktail napkin?

Solution: Models, Not Code

Models are the antidote: clear, succinct declarations of what, not how. They make the cocktail napkin executable.

Models are expressed in a Domain Specific Language (DSL). These typically invoke underlying runtime engines.

Accordingly, GenAI-Logic creates models, not code. This applies to all elements of system, as shown here.

Contrast this to many AI Coding Tools that are Natural Language Code Generators. That's the road to FrankenCode.

UI Model

Effective prototypes require sophisticated apps to read / update data - multiple pages with related data, page navigations, automatic joins, lookups, etc.

This typically involves enormous amounts of complex HTML, CSS and JavaScript. This would be tedious to understand and customize.

Instead, GenAI-Logic creates a model file in yaml. As shown at right, you can edit to control captions, field order, even when fields are displayed / hidden. These declarations are handled by the Safrs React Admin runtime engine.

API Model

Enterprise-class APIs require a great deal of sophistication:

Endpoint for each table, with CRUD support - create, read, update and delete.
Filtering, sorting, pagination, including related data access, based on relationships in the models file (typically derived from foreign keys)
Automatic Swagger
Enforces logic and security - partitioning of logic from (each) client app

The entire API creation process is shown at right. It is completely driven off the data model, relying on the sophisticated SAFRS API engine.

Add new endpoints using standard Flask and SQLAlchemy - see here.

Declarative Business Logic: the Key Differentiator

It's Half the Effort

Business Logic is typically nearly half the effort for most systems. It's the iceberg under the API.

But most products provide only "your code goes here", often in a proprietary scripting language. More is required.

Domain Logic, Integration Logic

Business Logic addresses:

Integration logic for participating in a larger enterprise-level interaction with other systems (e.g., above, "send to order to shipping...")
Domain logic for multi-table derivations and constraints (e.g., above, "balance is the sum of orders...")

Business Logic Automation

GenAI-Logic automates business logic:

1. Provided in Natural Language
2. Expressed as Rules (intents) of how data is to be derived and validated
  - - Concise: rules are 40X more concise than procedural code, since dependency management is automated
3. Declarative, ensuring:
  - - Quality: rules are automatically applied (re-used for) all relevant transactions (inserts, updates, deletes) - no missed corner cases
    - Maintainability: rules can be stated (or later added) in any order - no "archaeology" required to determine where to insert code
    - Performance: the Business Logic Agent automates and optimizes data access

Rules are handled by the Logic Bank rules engine.

Business Logic

The iceberg under the API

Spreadsheets also provide declarative logic. The sum formula watches and reacts to inserts, updates and deletes in the AmountTotal column. Business Rules provide the same level of abstraction for transaction processing.

Our criteria for declarative logic is:

automatically applied
automatically ordered
automatically optimized to minimize SQL

Architecture: APIs, Logic Reuse, Microservices

Architects will appreciate that project begins with a solid backend:

an enterprise-class API: providing filtering, sorting, pagination, optimistic locking
Logic re-use and partitioning: traditional procedural development often winds up with logic in UI controllers. This makes it hard to re-use between applications, and impossible to re-use for services.
- - Automatic Partitioning: declarative logic is automatically enforced by the API, whether for interactive apps or services
  - Re-use over Use Cases: Logic is automatically re-used over Use Cases. For example, the Customer Balance derivation is automatically applied to inserting orders, deleting orders, etc.
Declarartive support for Kafka messaging, so you can create interoperating microservices.

Reduce Rework: Get Requirements Right

Rework is disappointing to everyone: stakeholders and developers alike. These often come from requirements misunderstandings.

Since you can create running prototypes within a minute, and iterate, it makes it far easier to get the requirements right.

Effective Partnering With Line of Business Users

Many products improve velocity with proprietary databases and dev tools. These can provide real value.

But, for projects that require developers to address complexity, proprietary approaches can make it difficult for developers to use their standard tools. This creates organizational stress.

With GenAI-Logic:

LOB users get instant prototypes (no database design or screen painting),
and standard projects that enable developers to use their tools.

This reduces organizational stress, and the need to master multiple technologies.

AI... with control-- auditable, deterministic, transparent. GenAI Coding Tool Friendly.

Let's examine the created project shown at right.

Logic Translation

GenAI does not invent rules. It translates your logic into Rules as shown here. You review them, correct any issues.

The rules are completely deterministic, like the formulas in a spreadsheet.

You can add additional rules in your IDE, using code completion.

Your Code

You can add your own code. It is not realistic to create complete complex systems from only Natural Language.

Use AI Coding Helpers

GenAI-Logic addresses project creation from a prompt, including logic.

IDE-based project customization enables all the relevant tools, including AI Coding Helpers such as Gemini, CoPilot, Cursor, All Hands, etc..

Logging and Debugging

You are running in a standard IDE, with full access to the debugger. The rules also provide detail logging that shows every rule that fire. This makes it easier to verify regulatory compliance.

Your Tests

You test the logic using your favorite test tools / methodologies (e.g, Behave BDD testing).

Standard projects/IDEs enables the use of complementary AI coding tools such as CoPilot, ChatGPT, Gemini, etc.

Try it now

Create a system - it's free: click here
Explore the documentation here.
Contact us at info@genai-logic.com
Open source at GitHub.

Fernando Vazquez Nuñez

CEO | Director General

(Strategic Partner)

GenAI Logic allows us to further accelerate the development of innovative software solutions that respond to the growing need for digitalization and process automation. Ontimize Web, our low-code web application framework, allows developers to declaratively implement powerful user interfaces for complex business applications. By integrating Ontimize Web with GenAI Logic, we automatically obtain a robust rules-based backend that fully supports the needs of our frontend and a fully documented API.

Furthermore, the generative capabilities of GenAI Logic allow us to automatically generate 90% of the application from a prompt. That’s really impressive! Most importantly, it means that our developers no longer have to manually declare hundreds of user screens, with their corresponding CRUDs, business logic and API endpoints. They can now focus on understanding the business requirements and designing a user experience that customers will love.

Mark McLellan Director

(Partner)

Rowbot is a new breed of data management platform that enables a true Data Mesh architecture. It allows non-technical business users to integrate data from multiple disparate databases and create a unified view of activity across the organization.

We output a unified dataset and pass that to GenAI Logic. In 2 minutes we have a fully functional application, allowing an analyst to see customer activity across all participating systems.

Then we can incrementally introduce business rules. These rules can range from alerts based on the data to propensity flags for marketing. Users cannot believe how quickly a unified view of the data can be presented and then enriched by the GenAI Logic rules engine.

Thomas G. Peters

Imagery Business Systems, LLC

(Partner)

I can’t say enough about ApiLogicServer. I’ve been using ALS for a number of years now having successfully delivered several solutions that started as an ALS app. ALS provides us an advantage when not only starting new projects, but also when gathering requirements. Including ALS as a tool within the SDLC has been instrumental in several migration projects as well. Data is our bread-n-butter, and we're usong ALS more than any other framework in our projects.

I am excited to see the evolution of ALS into GenAI Logic using AI as the nexus for new project implementations. Thank you Val, Tyler and Thomas P. for a promising and powerful solution. ALS's iterative capabilities are especially helpful; driving the requirements process live with business stake holders. Getting the requirements right is very important in todays competitive market by helping us keep the costs down and ensuring customers are delighted with the outcome.

César Quinteiro Rendo

CTO Intergal S.Coop. G.

(Partner)

*“E-Cometa is a platform designed for the front end, enabling you to generate and maintain your forms on the fly, as well as define and manage processes dynamically. For back-end operations, GenAI allows you to define databases using AI and seamlessly integrate them with ApiLogicServer (ALS). ALS then provides the capability to add simple rules, enabling the creation of complex systems that integrate with your data.

By combining both, you will get a very flexible and powerful solution that allows you to create any web and mobile app easily, making it simple to develop and maintain—even if you are not a technical expert.

We also want to thank ALS for making it possible to migrate from the obsolete Live API Creator (a back-end rules engine with RESTful services), ensuring we could continue innovating with a modern and reliable solution.”*

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