Unable to ignore the benefits of generative AI in serving customers and internal workforces, companies must decide between developing their own AI systems and choosing off-the-shelf or public models.
Training a self-developed AI chatbot is a complex process. In contrast, “training” an off-the-shelf zero code bot from CustomGPT.ai on your own data is as simple as uploading a PDF. What’s more, even with a basic subscription, you can upload thousands of documents and other file formats.
Custom Chatbot Development vs. an Off-The-Shelf Custom GPT
So here, we’re briefly comparing developing your own in-house custom chatbot, which would be your proprietary system, to choosing a pre-built, off-the-shelf, no-code solution.
There are, of course, certain benefits to developing your own AI chatbot, including the advantages of a completely customized build, potential competitive advantage, perfect tailoring, and entirely personalized training and behavior. With a strong development team, a custom development may mitigate some of the risks of AI, allowing you to protect your business against specifically relevant threats or build a model with a defined purpose. Lemonade’s chatbot AI Jim, for example, can settle insurance claims.
The drawbacks to in-house development include accessing the high-quality developer talent required, having the infrastructure to build and host a large language model (LLM), the costs, both short-term and long-term, for maintenance and updates, and, of course, the whole range of AI risks to be considered.
Off-the-shelf or pre-built generative AI chatbot solutions, like CustomGPT.ai, offer immediate access to advanced large language models (LLMs) and the ability to build a working custom chatbot in minutes. Development costs are minimal, and there are zero barriers with a no-code approach. Pre-built adopters avoid lengthy development cycles and benefit from scalability, customer support, and technology updates.
Why is “Training” a CustomGPT.ai Chatbot so Easy?
It can quite literally take months to train an AI chatbot to deliver accurate conversational responses to consumers. The “training” process requires data to be prepared and formatted in a certain way. In contrast, CustomGPT.ai can handle unstructured natural language text.
So, why is that the case? We’ll look at the answer. And then at the accuracy of a CustomGPT.ai bot’s responses.
With a CustomGPT.ai bot, no AI models are actually trained on your data. You can create your CustomGPT.ai account and bot in minutes. Then, there are just a few more steps to upload your data, set the conversational behavior, and configure your persona, which is how your bot interacts with its audience.
CustomGPT.ai ingests your data into our secure and privacy-preserving cloud platform and uses the information to respond to queries using advanced large language models (LLMs). The result is a CustomGPT chatbot that can accurately respond using only your data. CustomGPT.ai uses advanced Retrieval-Augmented Generation (RAG) technology, which combines the retrieval of relevant information (your data) with natural language generation to produce contextually rich and reliable responses with less risk of hallucinations.
Learn more with RAG Development: Building vs. Buying Pre-Built Solutions like CustomGPT.ai
Simple Upload of Documents to a CustomGPT.ai LLMs Powered Chatbot
To “train” a CustomGPT.ai bot on your data you simply use your browser and CustomGPT.ai account interface and choose “Upload” to drop or click to upload files.
CustomGPT.ai supports 1400+ file formats, from popular formats like PDF, HTML, and Microsoft Office documents to less common ones like RTF, email archives (mbox), and zip files. You can also enhance your bot with audio and video formats.
There’s no need to prepare your data in any way, so you can upload:
- Detailed product data, including product features, functionality, FAQs, helpdesk articles, pricing, and offers
- Your entire website – you’ll just need the sitemap and can use a sitemap tool
- YouTube videos, shorts, reels and podcasts
- Any sales and marketing collateral, such as brochures or presentations
- Case studies that emphasize how your product or service overcomes client problems, provides solutions, and delivers results
- Anything else you’d like to add!
You can upload multiple files simultaneously with a batch limit of 1GB and 50 files. The CustomGPT.ai standard monthly plan allows 5000 item uploads per chatbot and 60 million words stored.
CustomGPT.ai helps customers enhance their customer service with personalized support, faster response times, and improved satisfaction effortlessly.
Are CustomGPT.ai Responses Accurate?
When you compare building an in-house chatbot to buying off the shelf, the former requires precisely structured information, whereas the latter option from CustomGPT.ai lets you upload unstructured documents.
Discover ChatGPT GPTs vs CustomGPT.ai: An In-Depth Comparison to Help You Choose
Now, it’s true that ChatGPT GPTs or Assistants also allow unstructured and natural language uploads. However, what’s really exciting is that CustomGPT.ai has recently been evaluated and ranked ahead of OpenAI for its RAG technology performance.
Tonic.ai Evaluates CustomGPT.ai’s RAG Performance for Accuracy
Adam Kamor, Ph.D., Co-Founder and Head of Engineering for developer data solutions company Tonic, has evaluated RAG systems using the RAG evaluation and benchmarking platform Tonic Validate—the sixth part in his series pitches CustomGPT.ai directly against OpenAI.
Read Tonic’s blog: RAG Evaluation Series: Validating the RAG performance of OpenAI vs CustomGPT.ai
The series focuses on AI tools or frameworks that integrate retrieval-based components with LLMs like ChatGPT. Kamor says:
“These tools are great for hackers and developers who are exploring RAG use cases for their generative AI apps; however, there is also another side of the market that we’ve been following focused on abstracting away the technical complexity of building a chatbot on top of your company data: no-code. It’s great for organizations that may not have the technical talent or resources to build a de novo system on their own.”
The engineer uses a collection of 212 Paul Graham essays as the data and a set of 55 benchmark questions.
Source: Tonic
Kamor says, “both systems perform admirably with generally high scores.” But adds:
“CustomGPT.ai wins on a few fronts. First, its aggregates are better, with a mean score of 4.4 vs OpenAI’s score of 3.5. Additionally, CustomGPT.ai only provided 6 answers with a score below 4, which is really fantastic and generally performs better than most systems we have reviewed in the past.
Of note, CustomGPT.ai’s median score was a 5, which is not something seen before by the RAG assistants we’ve evaluated.”
CustomGPT.ai’s “secret sauce,” he notes, is its:
“Proprietary embedding and retrieval models and prompt engineering strategies, which you get out-of-the-box with little configuration needed.”
Tonic has now published its RAG Evaluation Leaderboard with CustomGPT.ai as the clear leader ahead of OpenAI Assistants, Google’s Vertex Search and Conversation, Amazon Titan, and Cohere.
Alden do Rosario, CustomGPT.ai CEO and Founder, says:
“This achievement validates our mission to democratize generative AI by empowering organizations of all sizes and of all technical acumen. Thank you, Tonic, for advancing responsible AI by proving answer quality accuracy.”
Read the full press release: CustomGPT.ai Outperforms OpenAI and Sets New Industry Standard for Answer Accuracy in Industry RAG Benchmark
