Generative AI chatbots have human-like conversational abilities and can understand and respond to natural language, even somewhat comprehending context. These bots now offer unparalleled customer support automation and valuable internal tools. There are now several widely available models companies can use to leverage AI’s benefits.
Over twelve months after the launch of OpenAI’s ChatGPT, a number of generative AI large language models (LLMs) are now on the market and available to underpin business-focused chatbot applications. Following our first look at types of chatbots, we delve deeper into the generative AI chatbot options available to businesses that use OpenAI, Google, Amazon, and Cohere technology.
OpenAI Custom GPTs and Assistants
Custom GPTs
In November 2023, OpenAI rolled out the ability to create custom versions of ChatGPT to the public. These GPTs can be made on OpenAI’s site in a browser-based dashboard, without coding, and by providing “instructions and extra knowledge, and picking what it can do, like searching the web, making images or analyzing data.” per the OpenAI announcement which says:
“Anyone can easily build their own GPT—no coding is required. You can make them for yourself, just for your company’s internal use, or for everyone.”
These GPTs allow customization of ChatGPT but generally reside at their appropriate link at chat.openai.com and can only be accessed by users with a ChatGPT Plus subscription. They can’t be easily embedded as a widget or live chat on a website, and any specific data uploaded or conversations may be used to train OpenAI’s model if users don’t opt out. Chat logs aren’t available to the everyday GPT builder. However, per OpenAI’s announcement, developers can use APIs to connect GPTs to other applications, and enterprise customers can deploy internal-only GPTs.
CustomGPT.ai provides a business-grade platform to create custom chatbots that can be populated only with business content and embedded into a business website. These bots use OpenAI’s advanced large language models (LLMs) but with RAG technology and guardrails. We’ll cover these generative AI chatbots as an option for businesses shortly in this article. However the blog post
ChatGPT GPTs vs CustomGPT: An In-Depth Comparison to Help You Choose provides an immediate side-by-side comparison that delves into the full capabilities of both ChatGPT GPTs and CustomGPT.ai custom chatbots.
OpenAI Assistants
Where GPTs are built within ChatGPT’s dashboard, the OpenAI Assistants API allows users to build assistants with their own applications. Assistants can answer end-user questions by leveraging specific files the developing company provides, but creating Assistants requires developer-level coding.
The Assistants API beta was launched at OpenAI’s developer conference in November 2023 to allow the creation of “agent-like experiences” within apps. Assistants can have specific instructions and use data outside of OpenAI’s model as well as the model’s ability to perform tasks. Assistants can be used to build a GPT-powered chatbot on a website. This OpenAI tool is billed to developers based on feature usage and any data is not used to train the company’s models by default.
Google Vertex AI Search & Conversation
In August 2023, Google unveiled new generative AI tools in the form of Google Vertex AI Search and Conversation. The tools allow users to create search and conversation apps (chatbots) that use Google’s LLM PaLM 2. Developers can use their own data, customize the apps, and launch either AI search engines or chatbots to serve customers or employees.
Google Cloud vice presidents Amin Vahdat and Burak Gokturk explained:
“These products enable even developers with little machine learning expertise to build and deploy intelligent apps in as little as a few hours.”
The VPs add, “Enterprise developers can quickly ingest data, add customization, and, with a few clicks, build a search engine or chatbot that can interact with customers and answer questions grounded in the factuality of their enterprise website along with specified structured and unstructured data sources.”
Vertex Conversation allows developers to pre-program prompts and responses in natural language and decide if they want their own data to be supplemented by Google’s foundation model’s training data. Conversation supports audio and text and can display citations or produce interaction summaries that can be handed over to human agents. The use of Google’s tools, aimed at enterprise users, is charged for every 1,000 characters of input (prompt) or output (response).
The chatbots we’re covering in this article use retrieval-augmented generation (RAG) technology. All have recently been evaluated by developer data solutions company Tonic and benchmarked using Tonic Validate, including CustomGPT.ai, which outperformed each one.
Find how OpenAI’s Rag Assistants stacked up against Google’s Vertex Search and Conversation.
Amazon Titan
Available via Amazon Web Services (AWS), Amazon’s Bedrock and Titan Generative AI Services became widely available in October 2023. They allow customers to build generative AI-based applications through an API using several LLMs. Amazon Bedrock works a little like a library of foundation models available in the cloud. Amazon’s Titan model, named Titan Embeddings, is an LLM trained for the model customization technique RAG, giving companies the ability to use their proprietary data.
Amazon Titan’s foundational model can be connected to your own data sources. It then uses RAG technology to make a chatbot that is knowledgeable about your business, purpose, or specific topic. Actually building a Titan chatbot does require AWS and Bedrock access, for which there are costs and coding experience to build the bot’s user interface (UI).
Cohere
Cohere is a Canadian enterprise-focused AI company that was founded in 2019 by ex-Google and University of Toronto co-founders. Its investors include Nvidia, Oracle, and Salesforce, and its infrastructure is powered by Google Cloud.
Cohere generative AI is already used in Oracle products and its chat capabilities in Salesforce. In September 2023, it joined the competition to provide the business world with easy-to-build AI chatbots by launching an API to allow enterprise developers to build chatbots using the Cohere LLM, called Command. Cohere launched its Coral chatbot in July 2023, but the API adds the facility for companies to build chatbots into their own internal or external applications.
Cohere also uses RAG technology to allow developers to limit chatbots to proprietary company data or equally allow them to use information from the web. Cohere explained the advantages of RAG at the time:
“RAG systems improve the relevance and accuracy of generative AI responses by incorporating information from data sources that were not part of pre-trained models.”
Cohere’s Generate, Summarize, and Chat APIs are all aimed at developers to build into their own products. The costs vary based on the model used and the number of tokens, and there’s custom pricing for enterprise users.
CustomGPT.ai
CustomGPT.ai is a simple-to-use privacy first business-grade platform for users to create custom GPT chatbots that use OpenAI’s advanced LLM technology plus RAG in minutes with zero-coding that can generate responses from proprietary content provided for better accuracy.
These bots can be easily embedded into a website for customer engagement or deployed internally for employee productivity. The CustomGPT.ai blog shares chatbot use cases, benefits, case studies, and how to integrate CustomGPT.ai quickly with popular website builders and applications.
Start your CustomGPT.ai journey by learning how to Create chatbots using RAG technology through CustomGPT.
Tonic.ai has recently published its RAG Evaluation Leaderboard with CustomGPT.ai as the clear leader for accuracy ahead of OpenAI Assistants, Google’s Vertex Search and Conversation, Amazon Titan, and Cohere.
