In today’s rapidly evolving technological landscape, AI Virtual Assistants have become indispensable tools for personal and professional productivity. From managing tasks to providing information and even simulating human-like conversations, these digital aides have revolutionized the way we interact with technology. While many rely on existing platforms like Siri, Alexa, or Google Assistant, there’s a growing interest in creating custom virtual assistants tailored to individual needs.

Some of the most common use cases of Virtual Assistants are:

• Smart-home Management
• Information Retrieval
• Entertainment and Media
• Data Analysis and Business Intelligence
• HR and Employee Self-service

Understanding Language Models

Before diving into the process of creating your AI Virtual Assistant, it’s crucial to understand the technology powering it. Language Models, especially Large Language Models (LLMs) like GPT-3, Llama2 etc, are at the heart of Modern AI Virtual Assistants. These models are trained on extensive text datasets, allowing them to comprehend and produce text that resembles human writing. They can comprehend context, generate responses, and even perform specific tasks based on input.

Steps to build your AI Virtual Assistants

1. Define the Purpose and Scope

Begin by clearly defining the purpose and scope of your AI virtual assistant. Will it be a personal productivity assistant, a customer service chatbot, or something else entirely? Understanding the intended use case will guide the development process.

2. Choose a Language Model

Select the appropriate Language Model for your project. While GPT-4 is a powerful option, there are other models available, each with its strengths and weaknesses such as Llama2 by Meta, Claude by Anthropic etc. Consider factors like model size, computational requirements, and available APIs.

3. Attach Knowledge Base with Assistant

Gather relevant data that your virtual assistant will need to perform its tasks effectively. This may include text corpora, FAQs, or domain-specific knowledge bases. Preprocess the data to ensure compatibility with the chosen language model.

4. Attach the Action Groups

Define the tasks you want your Assistants to execute. You can define the action groups with standard schemas like OpenAPI Schema etc.

5. Integration & Deployment

Integrate the model into your virtual assistant application or platform. The user will send the input to the assistant and then assistant will process this message in the following sequence to generate the response:

• Pre-Processing: Here, the assistant sends a prompt to the model with all the information like action groups, user input, etc.  After running the prompt, the model tells if the user input is identified as malicious or outside the assistant’s domain.
• Orchestration & Knowledge Base: Here, the assistant sends a prompt to the model with context from the Knowledge Base. This prompt helps to understand the linear chain of thoughts used by assistants.
• Post Processing: This covers from the API invocations to get the API responses. Then a prompt is sent to the model with API responses to generate the final user input response.

You can deploy this virtual assistant to the desired cloud services on Amazon Web Service (AWS), Google Cloud or Microsoft Azure, etc.

If you are looking for AWS, it is providing multiple services like AWS Bedrock, AWS SageMaker, etc.

6. Continuous Improvement

Iterate on your virtual assistant based on user feedback and performance metrics. Monitor its interactions, identify areas for improvement, and update the model accordingly. Continuous improvement is essential for ensuring that your virtual assistant remains relevant and effective over time.

Architecture Diagram

Next Steps

The integration of AI virtual assistants in both consumer and business environments aims to enhance efficiency and productivity by offloading routine tasks and providing instant access to information. This technology continues to evolve, with ongoing advancements in AI and NLP driving more sophisticated and human-like interactions.

Contact BigStep Technologies today and discover how our cutting-edge solutions can fulfill your requirements in building such AI products. Get in touch with us at info@bigsteptech.com.