AI Launching Associations Forward: Multi-Agent Response Systems

Vaibhao Chawale
07 August 2024

As AI continues to expand our vision of the future of software we’re starting to see some new programming patterns emerge. One of the most interesting new patterns is the use of “agents” which allow multiple LLM models to interact together and produce a result.  This is the approach used by the Microsoft AutoGen.Net framework which is a current leader in knowledge and reasoning benchmarks. 

How can we use this type of framework to benefit projects? With the goal of “work smarter, not harder” we can create “agents” that are each aware of a part of the system and act accordingly. This gives much more control over an API for any system to help the LLM act correctly and consistently. 

We’ve developed a multi-agent response system (MARS) framework that leverages AI to connect to a complex API to a backend system such as any association management systems (AMS). This allows for natural language to be used when interacting with the AMS API and perform complex tasks quickly and efficiently. 

This can be used for multiple use cases to streamline development and increase productivity such as: 

AI Between Your AMS and Website 

An association’s AMS and website need to communicate accurately and efficiently. In a typical integration, both systems are connected through an application programming interface (API). Each platform integration requires its own API connection to share information so that membership information is accessible to the website and vice versa. This is important for a personalized membership experience, viewing member-only content, online purchases, and more. 

Implementation of a MARS that leverages AI opens the possibility of creating a platform-agnostic integration based on natural language. The MARS is a natural language wrapper placed on top of the API to convert the CMS and AMS-specific queries into natural language queries. To break it down simply, AI becomes a universal translator.   

Smooth AMS and CMS Transitions 

It’s critical for your AMS to connect with your selected CMS. But over time, as your organization grows and business and technology needs change, you may need to change AMS platforms. This is where the benefits of an AI-based MARS truly shines. 

Since MARS implements AI for natural language queries for outbound integration with an AMS, your transition to a new one becomes a lot easier because your front end remains the same. Previously, research would need to be conducted to ensure that the new AMS has an API integration with the CMS. limiting your platform options. With the MARS, you’re able to select the AMS of your choosing without worrying about the API connections. 

Natural Language Query Chatbot 

Another benefit of using a MARS is the natural language query capabilities through a chatbot. Each AMS has its own naming conventions and organization of member information, and it’s not always intuitive. A MARS in connection with a chatbot means that users can type in a question to the chatbot and receive the information without digging around through the AMS.  

This means that when a customer service member receives a call, they can quickly retrieve membership information, or a salesperson can easily retrieve sales information with a simple question.  

AI is excitingly changing every industry. As we continue to explore AI and its capabilities, we’re excited at the possibilities of transforming the way associations work through MARS. 

 

Are you considering AI solutions? 

Contact the Adage team to discuss and identify AI options for your organization.

Vaibhao Chawale



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