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  • Streamline Business Operations with Multi-Agent Systems

Streamline Business Operations with Multi-Agent Systems

Learn how specialized AI agents working together with the help of Multi Agent LLM Systems AI, boost efficiency, customer satisfaction & workflow precision.

  • Aug 24 2024
Table of Contents

TABLE OF CONTENT

 Multi Agent LLM

The market for autonomous AI including AI agents was valued at $4.8 billion in 2023. If we look ahead its expected to soar to $28.5 billion by 2028 showing a CAGR of 43%.

Obviously you can see that businesses are jumping on the AI Agents bandwagon to automate workflows, increase efficiency & enhance CSAT scores.


Now, typically each AI Agent takes a unique role in the operational setting of a business. But when we say ‘business’, it is a pretty broad category. So let’s zoom in on the insurance sector.

In this case, one AI Agent will automate claims intake while the other will take care of claims support & another might handle claims status updates. Each agent has its own task, working individually. And the process is already pretty efficient.

What if the AI Agent managing Claims Intake could directly notify the AI Agent handling Claims Status Updates? With a central coordinator enabling the communication, the process would be even more seamless. So, when a policyholder needs an update on their claim status, they receive the information instantly & without errors!

Multi-Agent LLMs makes this possible where AI Agents collaboration takes efficiency to a whole new level. Let us explore them in detail today.

What is Multi Agent System in AI

Multi agent LLM systems can link custom data sources with LLMs & create multiple LLM based Agents. It can be used for natural language based interaction with documents, data or applications.

They orchestrate between agents for making natural language-based API calls, connecting to your data and automating complex conversations.

The best example of multi-agent LLM is Floatbot’s proprietary GenAI-driven LLM or ChatGPT-based Master Agent developer framework – AGENT M.

Take for example, a relay race where each runner has a unique strength, passing the baton to the next. Thats how these LLM based AI Agents work together, tackling complex tasks more effectively than one agent alone.

A central coordinator which is the Multi Agent LLM system AI, manages their communication, ensuring everything running smoothly. With it you tap into the power of teamwork, making your processes more efficient & effective.

How Multi-Agent systems work

To put it in to simple terms, one AI Agent = one expertise.

Each agent brings its own expertise to the table. You’ll find that they are trained on specific datasets. Each of them excelling in different areas. Instead of working alone these agents collaborate and share information with each other. The central coordinator responsible for their communication is the multi agent systems.

By doing so, we create a dynamic network of problem-solvers that works together to tackle challenges.

what is Multi Agent System in AI

Unique Expertise

Each AI Agent in Multi agent LLM system is trained on a particular dataset, making them experts in their own area. For instance one agent might handle customer inquiries while another focuses on processing data.

Staying Connected

Agents don’t work alone. They communicate and share information with each other much like team members brainstorming ideas together. By pooling their insights and leveraging each others strengths, they come up with solutions that work and are effective.

The Orchestrator

And none of the team work is possible without the coordinator in place. So the multi agent LLM system assigns tasks to each AI Agent and is responsible for ensuring uninterrupted communication between the AI Agents.

Why Multi-Agent systems are the next big thing in BFSI Sector

As you know, in the BFSI sector efficiency & precision is key. Multi-Agent systems in Ai offer a powerful solution by bringing together specialized AI agents meant to specific needs. Ultimately you get better customer satisfaction, empowered human agents and enhanced workflows.

Equip multi agent system AI with the skills your business needs to thrive! Need sales AI agents (generate leads, qualify prospects)? Check. Need help desk AI agents (resolve errors, update tickets)? Check. Need an AI agent to automate claims submissions? Check.

And the list goes on. You can niche it down as much as possible to create a specific AI agent for very specific task. It can be anywhere from digital customer onboarding specialist to compliance checker.

With Floatbot’s Agent M, you don’t have to create LLM based agents from scratch. Use our pre-trained skillsets and enable it for your agents & deploy them instantly!

Floatbot’s Agent M

With Floatbot’s Agent M, you gain instant access to a range of pre-defined skills. Just a few clicks and your bots can handle booking, ordering, scheduling and FAQs. Its that simple.

Agent M acts like a smart connector for your applications and APIs. It effortlessly handles the exchange of data, information and commands between your bots and various applications.

The best part? You don’t need to dive into manual coding or complex setups. Agent M takes care of it all, making integration smooth and hassle-free.

But there is more. Agent M lets you build custom skills tailored to your needs. Our user friendly interface makes it easy to define your own intents, entities, contexts & responses. Whether you are designing a calorie tracker, a weather forecast assistant or a travel guide, Agent M gives you flexibility to create exactly what you need.

With Agent M, transform how your business operates. These are the value delivered by Agent M:

  1. Reduce AI Agent Development time by 60%
  2. Increase CSAT by 90%
  3. Less than 5 second Latency
  4. No hallucinations
  5. Redact PII from text