Introducing the Oracle HCM Fast Formula Agent – Built with AI to Help You Work Smarter

🚀 Introducing the Oracle HCM Fast Formula Agent – Built with AI to Help You Work Smarter

After months of juggling fast formulas, fielding questions from HR teams, and trying to decode cryptic payroll logic at 2AM, I decided it was time to build something better.

Today, I'm happy to share an open-source project that came from that journey:

👉 Oracle HCM Fast Formula Agent – A smart, simple tool that uses Generative AI to help you generate, validate, explain, and modify Oracle HCM Fast Formulas, and more!

🎥 Check out a quick demo - Watch on Loom

💡 Why I Built It

Working in the Oracle Cloud HCM space, I saw firsthand how challenging it can be to:

• Interpret legacy Fast Formulas written years ago
• Validate logic across hundreds of conditional paths
• Explain formula outcomes to business users
• Generate new formulas based on complex rules — under tight deadlines

And with the rise of AI, I thought: Why not build an assistant that understands Oracle HCM and speaks "formula"?

⚙️ What It Does

With this Flask-based app, you can:

✅ Generate new Fast Formulas from plain-English descriptions
✅ Explain existing formulas in readable, line-by-line language
✅ Validate and suggest corrections for logic/syntax errors
✅ Modify formulas based on user input
✅ Extend the tool with new advanced actions using a plugin system, like the included Summarize advanced action!

It even has a clean admin panel and a dark mode toggle because... well, late-night debugging deserves a good theme.

📦 Plugin Architecture

Want to add your own action like summarize_formula or compare_logic_blocks? Just drop it in the plugins/ folder. No changes to the main app required. It's built for extensibility.

🐳 Docker Ready

Whether you’re developing locally or deploying in the cloud, the app comes with a Dockerfile that runs the app via Gunicorn for production-grade performance.

🔗 Get Started

Clone it, run it, or fork it for your own use:

👉 GitHub: https://github.com/TheOwner-glitch/hcm-fast-formula-agent
📹 Demo: Watch the video

🙌 A Call to the Oracle Community

I built this for consultants, analysts, and developers who need to move fast and support critical Oracle HCM needs in the Fast Formula space, but more importantly to share an example of how AI Powered application development can be compelling and reduce the need for conditional and hardcoded business logic by instead leveraging the power of generative AI  to interpret natural language. If you try it out and find it helpful — or have ideas for improving it — I’d love to collaborate.

Thanks for reading. Now go automate your fast formula headaches away.

— Julio

Leveraging Oracle Cloud’s Generative AI with Cohere: A Hands-On Approach

After days of tinkering and fine-tuning, I'm excited to share something I’ve been working on — OCI Generative AI Cohere Integration with external services. If you're someone who works with AI, Oracle Cloud, or just enjoys diving into new tech, this project might be something you'll find interesting.

What's the Project About?

In short, it's a simple yet powerful integration of Oracle Cloud’s Generative AI service with Cohere's language model by exposing it to external usage in order not to be confined to the chat experience within the OCI console. The goal is to provide an easy-to-use interface for AI-driven responses via a Flask API or function-based approach. Whether you're running the service locally or integrating it into your own applications, this project is meant to be a starting point for building smarter, AI-powered experiences that allow you the flexibility of using your preferred development platform outside of the playground in your Oracle OCI Tenancy.

Why This Project?

If you’re like me, you enjoy playing with new tools but don’t always want to reinvent the wheel every time you build something. That’s why I wanted to simplify integrating Oracle's powerful AI services into everyday applications. The project takes the heavy lifting out of the process and provides a clean, easy-to-use API for interacting with Oracle’s AI models.

But it doesn’t stop there. Whether you're building out something bigger or just playing around with ideas, this project is designed to be flexible and easily extendable.

Here’s What You Get:

• Flask API: If you’re building a web-based application and want easy interaction with the Generative AI service, the Flask API is ready to go. You can send requests, get responses, and scale up as needed.
• Function-based API: For those who don’t need a full web API, you can call the AI service directly from a function that you can import into your Python projects. Perfect for smaller integrations or experimenting within your own apps.
• Configuration Flexibility: With environment variables and a configuration file, you have full control over things like model parameters and Oracle Cloud credentials.

How to Use It?

1. Set up your environment: Whether you're using the Flask API or the function-based setup, you’ll need to configure your environment with Oracle Cloud credentials and some basic settings.
2. Get running: Once configured, you can easily call the API or function with any message you want to send to the AI model, and you’ll get a detailed response in return.

I’ve added full instructions on the project’s GitHub page, including setup steps, environment variables, and how to run both approaches.

What’s Next?

The goal is to keep expanding this project. Right now, it’s all about integration, but as AI services evolve, I want to keep adding new features and I likely will build apps that consume these interfacing endpoints in order to use the power of the Cohere LLM. Expect more updates on this as I add new functionality and more tutorials to help everyone get the most out of the platform.

Feel free to dive into the project, contribute, or just ask questions. I’m always happy to connect with fellow developers who are exploring AI and Oracle Cloud.

Check it out on GitHub: OCI Generative AICohere Integration

I've added some screenshots below showing the interactions with the OCI Gen AI service via Postman by utilizing the Flask API, allowing extensibility outside of the chat experience in OCI which is the default experience. 

By utilizing the API approach you can take advantage of the power of the Cohere LLM through Oracle OCI in your applications and data science tools while maintaining your security assurances of being inside of your OCI tenancy.

Thanks for reading, and happy coding!

OCI Gen AI Playground

Click on the images to expand them for ease of viewing

Postman Interaction with Flask API Exposing the OCI Gen AI Chat Service

OCI Gen AI Traffic from the API

Oracle HCM - Preparing for the USOPTE Transition: What You Need to Know

The payroll landscape is undergoing a significant shift as Oracle HCM customers prepare to transition to the native US Payroll Tax Engine (USOPTE). This change, mandated by Oracle for all customers by update 26A, marks the end of support for third-party tax engines and introduces a new era of integrated payroll tax processing.

Here’s a quick overview of what’s changing—and what organizations should be doing now to prepare:

Transition Overview

• From: Third-party tax engines (e.g., Vertex)
• To: Oracle’s native USOPTE
• Deadline: Update 26A (mandatory)

Key Requirements

• Enhanced Address Validation: Must be enabled as a prerequisite
• ORA_HCM load geography process
• Scope: Impacts HR and Payroll modules (not ERP)

Timeline & Planning

• Many organizations are targeting Q4 2025/Q1 2026 for implementation.
• Early planning is essential to manage dependencies, regression testing, and downstream impacts.

Stakeholder Engagement

• Cross-functional collaboration is critical—HR, Payroll, IT, and vendor partners all play a role.
• Some teams are treating this as a formal project with dedicated resources and governance.

Benefits

• Improved compliance and audit readiness
• Streamlined integration with Oracle HCM
• Reduced reliance on external tax engines

If your organization is navigating this transition, now is the time to engage with Oracle resources, attend webinars, and connect with peers who are further along in the process. Sharing lessons learned and best practices can help ensure a smoother rollout for everyone.

Below are some crucial visuals that aid in understanding the goals and next steps of this effort

Click on each image to expand it