Intelligent Agents: Unlock Growth with Generative AI

3 min read
Oct 15, 2024 5:30:12 AM
Boost your business with AI-powered agents
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With the emergence of Generative Artificial Intelligence, many organizations are creating solutions in which they use this tool to create content, such as images, text, or even music, from existing data. This is achieved through language models that learn patterns and features from data sets and are then able to autonomously generate original content.

This article will explain the role of GenAI Intelligent Agents and how this technology can be applied in banking, retail, and CPG.

What are artificial intelligence agents?

Intelligent Agents are conversational interfaces capable of collecting data to perform tasks autonomously. Today, many organizations use this kind of AI solution to automate different tasks.  

These agents use natural language processing and machine learning techniques to understand questions, execute specific commands, and provide accurate and context-based answers. Additionally, their knowledge base can be augmented with proprietary data, allowing each company to have its own customized and task-oriented task-oriented Intelligent Agent. 

If you need advice on how to develop your own Intelligent Agentes, we invite you to read the article Gregorio Patiño, co-founder and Head of Business Development-FSI at Pragma. 

In the financial sector, for example, Intelligent Agents can be integrated into mobile applications to offer users personalized financial advice, answer their queries, and provide accurate information when purchasing new products. 

Something similar can be said of the retail and CPG sectors, where artificial intelligence agents can help create a personalized shopping experience. They can also be used in supply chain and logistics tasks, managing inventories, and predicting demand to optimize resources. 

Companies can enable different agents to automate operational tasks such as:

  • Accelerate the modernization of legacy systems through programming assistants. 
  • Improve customer service by recommending and answering questions about products, services, legal documents, and processes. 
  • Generate original content that allows, among many other things, the creation of corporate communications, taking into account the company's regulatory frameworks and communication style. 
  • Analyze relevant business information, both structured and unstructured, to make business decisions.
  • Price stimates based on corporate context and specific customer needs.
  • Extract information to auto-fill contracts, sales agreements, templates, etc.

How to select the ideal Intelligent Agent for my business

Choosing the right artificial intelligence agent is crucial to maximize your impact and achieve your business goals. Each type of agent has unique features and capabilities that make it ideal for specific tasks. Here are a few of them.

  • Model-based reactive agents: Model-based agents have a complex understanding of their environment data, which allows them to go beyond following specific rules. Unlike traditional software solutions, this Intelligent Agent can consider the likely consequences and make the best decision autonomously. They are ideal for complex tasks such as making personalized recommendations.
  • Goal-based agents are also rule-based, but their focus is on finding the most efficient path to achieve the desired results. They are used for natural language processing and in applications and route planning systems, where they must optimize travel time considering traffic and other conditions.
  • Utility-based agents: They use complex algorithms to maximize the benefit to the user. They are suitable for tasks that require comparing different options and choosing the most favorable one.
  • Learning agents: They continuously learn from previous experiences to improve their performance. An example of their use is fraud detection systems that update themselves with new data and behavior patterns.
  • Hierarchical agents: They are structured in levels, where higher agents decompose complex tasks and assign them to lower agents. They are used for tasks that require collaboration and coordination between multiple agents, such as traffic management systems that coordinate traffic lights and vehicles to optimize vehicular flow.

As an AWS partner, at Pragma we have teams of professionals who are ready to support you on the creation, integration and scaling of intelligent agents based on generative AI. Thanks to this, we have been able to build solutions that take advantage of this technology for our partners in the financial sector, insurance companies and leading brands in the retail sector. 

For Intelligent Agent development to generate a significant return on investment, it is advisable to prepare the way with several previous efforts. This includes modernizing the technological infrastructure through cloud services, strengthening data collection, analysis and processing, and automating internal processes. Here you can read more on how to prevent GenAI solutions most common threats.

As with other implementations, these types of projects start with a thorough understanding of our client's business objectives, which allows us to create solutions with the technology that best suits their needs. 

Choosing an experienced technology partner is crucial to accelerating the process of building the solution. If you want to take advantage of this technology's potential for your business, we invite you to do so in good company.

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