How confident can you really be in your decisions if a large chunk of the data isn’t even considered during the process?
Today’s enterprises rely on an ever‑expanding set of applications and services - ranging from SaaS platforms like Salesforce and Jira to cloud services and internal systems - that expose data exclusively through REST APIs. At the same time, most analytics and integration tools, including Informatica, Power BI, and Tableau, are fundamentally designed around SQL‑based connectivity.
This mismatch creates a critical bottleneck. While REST‑based data continues to grow exponentially, connecting to these sources remains manual, time‑consuming, and error‑prone. The result is slower insights, increased development effort, and valuable data left untapped.
The Solution: Progress DataDirect Autonomous REST Connector with AI
Progress DataDirect addresses this challenge with the Autonomous REST Connector (ARC), a powerful solution that enables SQL‑based access to REST APIs using a JSON description file - known as a model file. For years, developers have relied on ARC to build REST API connectivity in days rather than weeks, dramatically simplifying integration compared to traditional approaches.
However, even with ARC, creating and maintaining model files still requires manual effort, deep API expertise, and careful mapping. While faster than alternatives, this step has remained a point of friction for development and integration teams.
With advances in AI, there is now a better way.
We are introducing an AI‑powered capability that makes ARC model generation up to 10x faster and significantly more accessible - transforming a process that once took days into one that takes hours.
Introducing AI-Driven Model Generation for ARC
This new AI‑driven solution transforms REST API connectivity from a manual, configuration‑heavy task into an intelligent, guided experience.
Using advanced AI agents, the solution automatically generates Autonomous REST Connector model files directly from Swagger or OpenAPI specifications. By understanding the structure of your API, the AI eliminates much of the manual mapping and guesswork and produces a strong starting configuration aligned with ARC requirements in minutes.
While the generated model is not fully production‑ready, it gets you most of the way there - allowing you to validate, refine, and finalize the configuration with significantly less effort.
The result is faster onboarding, fewer errors, and a smoother path to querying REST data through standard SQL tools.
The Impact: 10x Faster REST Connectivity
With this AI‑powered, agentic workflow - available as an open‑source add‑on directly in your favorite IDE like VS Code - you can increase the speed of building connectivity to any REST endpoint by up to 10 times. The solution intelligently converts Swagger or OpenAPI documents into ARC‑compatible model files that are approximately 80% ready to test out of the box.
This means:
- For customers: Reduce REST connectivity development from days to hours
- For ISVs: Significantly lower driver development and maintenance efforts to offer extensive connectivity breadth through your tool
- For all users: Accelerate time to value while minimizing manual configuration
What once required days of mapping, validation, and refinement can now be achieved in minutes. AI handles the heavy lifting, while you remain fully in control of the final configuration.
What This Means for You
For Data Engineers and Integration Developers
Stop spending hours on manual configuration. Upload your Swagger or OpenAPI file and receive a model file ready for review in seconds. Spend time building integrations and delivering value, not wrestling with configuration files.
For Business Analysts and BI Users
Gain seamless SQL access to REST-based data without needing deep REST API expertise. The AI-powered generation abstracts the complexity, enabling faster access to insights and more complete data analysis.
For Solution Architects
Design scalable, consistent, and maintainable integration solutions across diverse APIs. Automatically generated model files improve accuracy, reduce risk, accelerate deployments, and enhance customer satisfaction.
Key Benefits
- Faster time to value with model files generated in minutes
- Higher accuracy through reduced schema and mapping errors
- Lower complexity without requiring deep REST expertise
- Scalable onboarding for new APIs with minimal manual effort
- User-friendly, guided workflows with clear next steps
How It Works
- Upload your Swagger or OpenAPI specification
- AI analyzes the API and generates an ARC-compliant model file
- Review and customize the configuration as needed
- Open the model in ARC Composer (if available on the machine) and start querying your REST API
The process is transparent and guided throughout. AI simplifies the work, while you retain full ownership and control over the final output.
We Want Your Feedback
This capability is currently available through an Early Access Program, and your feedback is essential. Whether you are integrating a single API or managing dozens, your real-world use cases will help shape and refine this solution.
Be Among the First to Experience ARC AI-powered Model Generation
ARC AI-powered model generation is currently being offered exclusively through the DataDirect Customer Validation Program (CVP).
CVP members receive early access to emerging DataDirect capabilities, including ARC AI-powered model generation, and can influence product direction through direct feedback and evaluation.
Ready to become a member? Go to DataDirect Customer Validation Program, and click the “Ask to Join” button.
Already a member? Check out our announcement post to learn more about early access.
The Bottom Line
REST API integration doesn’t need to be this complicated. With AI-powered model generation for the Autonomous REST Connector, you can eliminate manual configuration, reduce errors, and accelerate your time to productivity.
Reach out to our sales team to learn more and explore how AI-powered ARC model generation can accelerate your integration projects.
Kumar Vikesh
Kumar has been at Progress for the past 15 years, having worked as a developer, engineer and most recently as a Technical Product Manager.
Projects
MYSQL-UDT: The project involves design and implementation of new SQL statement for User Defined data type (UDT) for distinct types. The statements would be ANSI SQL standard statement. The aim of the project is to do the changes to MYSQL database engine to support the distinct User Defined Types. This project will add new code to the different component of the database engine, such as syntaxes, parser, and executor modules as appropriate.
Environment: Linux
Role: Involved in Preparing Requirement specification, Preparing High Level Design and Low level design for the project. I developed the module that will create UDT, Drop UDT and use UDT in Create table, alter table etc.
SQL Grammar Test Framework: This is a framework that generates SQL in an automated manner. The objective of this framework would be as follows: Complementing the feature and systems integration testing that each of the database solutions providers may already have, as part of their testing process.
Environment: Linux
Role: Involved in preparing the requirement specification, design documents.I worked on the development of UI part and Query generation module using BNF grammar file.
MATRIX: Developing an antivirus solution for the Vmware virtual infrastructure. The Software provides security against malware (virus, spyware, Trojans etc.) for OSes running within the virtualization environment. The technologies involved are C/C++. Target platforms are Windows Server 2003 and for RTA (Real-time agent) component Win2k, 2k3, XP, Vista for 32/64-bit platforms.
Environment: Windows, VMware
Role: Developed the Update Module of the software. This also involves Reading and Modifing the registry, mounting the Registry Hive of a remote virtual machine into the local registry. Implementing the Proxy setting page for getting pattern and engine updates. VmWare installations.
Specialties
C, C++, VC++, Unix, System Programming Windows, Win32 SDK Prograaming, MFC, PERL Scripts, GDB, NETBEANS, Vi editor, Database Internals, Antivirus Software, SDLC, Rational Rose