James (Sevan) Bomar III is a spiritual expert and coach in lifestyle advancement, finance, and self-development. Renowned as a serial entrepreneur, James is dedicated to creating social platforms and AI-driven solutions. With 170K subscribers on YouTube, James is not only a thought leader but also an investor who specializes in developing products to address major problems faced by society.
Our collaboration with James began by supporting his Woocommerce shop, where he sells courses and a range of lifestyle products. As our partnership evolved, he entrusted us with the creation of a platform for generating images on spiritual topics.
And then James came up with another innovative idea: “What if EVNE could build an AI-powered chatbot using a custom Large Language Model (LLM) to help people get answers to any question related to my area of expertise?”. He needed a team that understood deeply his domain and could solve even intricate issues comprehensively instead of simply writing code – and our team was a perfect fit.
That’s how Sibyl AI, the world’s first AI spiritual guide, was born.
Keep reading to discover how EVNE Developers turned this idea into reality, from a business model to a final solution.
After years of collecting books, videos, courses, and all sorts of data on spiritual topics, James was looking to create a vast database that could be easily accessible to users interested in getting answers to spiritual questions. He needed a tech team focused on long-term collaboration that understands the intricacies of engineering with extended release cycles and can facilitate a smooth transition from the MVP phase to a full-scale product without the need to hire in-house. So he reached out to EVNE, his long-term software development partner, to build an AI-powered chatbot that could answer any esoteric question.
Sibyl AI is the world’s first spiritual LLM with a mission to give people access to ancient wisdom and help them grow spiritually. Sibyl leverages artificial intelligence and machine learning to provide tailored answers to user inquiries, leveraging ancient teachings and spiritual insights that James Bomar spent years collecting.
To make the solution possible, we unified 5 datasets in one system, each with 160K pages of metaphysical content, and ensured a direct connection with GPT-4 Turbo for instant response generation. Each dataset has its function:
Here are the main features of Sibyl AI:
After generating a text response, Sibyl can visualize it with a high-quality custom image or generate an image for any given prompt. For this, the Sibyl response is sent to an API, transformed into a prompt, and then a third-party service, Dall-E, transforms it into an image.
Users can add stories and Sibyl will create an illustrative storytelling experience based on them. The system divides a narrative into 10-12 parts based on the context and visualizes it with custom images.
Users can also personalize generated images with the Face swap feature, effortlessly replacing faces on pictures.
AI-2-AI feature allows users to see how two AI systems engage in a dialogue, discussing any spiritual subject. The user offers the topic and the first prompt to steer the dialogue. For an even deeper experience, responses are voiced over with an AI text-to-speech system.
Our goal was to release an MVP as quickly as possible to attract new users. The first pre-launch version was released in a month. After that, we constantly updated it to ensure better user experience, response quality, and the speed of generating answers. Here’s how we managed to overcome the main challenges along the way.
Each dataset is trained on a specific material to better answer user inquiries, whether it’s about numerology, health, or astrology. The primary challenge lay in seamlessly directing user queries to the dataset that would generate the most accurate and insightful responses.
To choose the most suitable dataset, we implemented a two-layer verification process. In the first layer, the system meticulously analyzes the user’s prompt by studying dataset summaries. This initial step helps determine which dataset aligns most effectively with the nature of the question. The second layer involves an in-depth examination of keywords in the user’s prompts, allowing precise matching with the appropriate dataset.
By adopting this approach, Sibyl can confidently respond to user queries most efficiently and accurately, delivering a tailored experience that aligns with the user’s specific spiritual focus.
The next challenge was to accelerate the response generation. Initially, we employed a custom approach when the LLM model analyzed all available data, dividing it into paragraphs known as embeddings.
Seeking an even more efficient solution, we transitioned to Pinecone, a powerful cloud-based service designed for searching, ranking, and organizing intricate data structures.
With Pinecone, upon receiving a user request, the system sifts through the dataset based on prompt keywords. Analyzing a hundred relevant paragraphs, Pinecone identifies the most fitting information. These selected paragraphs are then seamlessly transformed into a cohesive answer through ChatGPT, resulting in a remarkable reduction in response time to a mere 0.5 seconds at most.
By integrating Pinecone into our workflow, we’ve not only significantly enhanced the speed of information retrieval, shortening it from 30 seconds to 0,3-0,5 seconds, but also streamlined the process of generating coherent responses to user queries.
Finally, we had to optimize the quality of vectorization, which is a process of selecting the most relevant information from the entire dataset. To achieve this, we researched different AI models. We meticulously analyzed their functionalities, using plugins to assess their responses to requests and the output.
The main limitation we faced was ChatGPT’s inability to process substantial amounts of text. To solve this, we refined our vectorization process and shortened the length of paragraphs to get responses as quickly as possible.
We had to swiftly make changes to the product as AI-powered solutions progress quickly and it was imperative to be among the first ones to adopt new features and attract users.
We managed to update Sibyl efficiently by leveraging third-party APIs and introducing new functionality. Leveraging this approach, we could add new features in just a day or two, always ensuring the solution remains relevant on the market.
Sibyl AI fully met the goals of our client and ensured a steady flow of organic leads even before the official launch. Now we continue to support the platform and ensure it offers the smoothest experience possible.
400+ users increase before launch
Even without a marketing campaign, the platform effortlessly gained over 400 new users in the initial 2 months at no customer acquisition cost, which proved market fit and validated the MVP concept. The scalable architecture maintains system agility without complexities or excessive costs.
AI-powered knowledge platform
We trained AI on multiple datasets and delivered the ultimate knowledge platform that unifies all the spiritual data collected throughout the years. The product constantly grows and continues to evolve its capabilities, improving user experience and providing insightful answers to all spiritual questions.
Custom dashboard to track success
To allow full visibility into product success, we created an environment to allow the client to track product conversions, expenses, and revenue through a custom dashboard. It ensures a seamless experience, enabling the client to make informed decisions and optimize business strategies.
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