Welcome to ActionChat
I'm Logan, I built ActionChat because of the advancements with AI. When ChatGPT was released, I immediately recognized the potential to train it using your own data. And guess what? We've not only accomplished that, but we've gone even further. We've developed a chatbot that can be customized with your data and seamlessly integrated into your website. This empowers your users to effortlessly ask questions and receive instant answers from LLM's that have the context of your data.
What truly sets ActionChat apart, however, is our innovative approach to handling situations where AI doesn't have the answer. In cases where AI falls short, we offer users the option to connect with a human (that's you!). This feature is designed to save you an enormous amount of time. AI effectively handles approximately 60% of the inquiries, while the remaining 40%—often more complex or critical—are redirected to you. Just imagine the hours you can save each week with this process.
We didn't want to rely solely on an AI chatbot, as it can sometimes create a robotic experience that lacks human interaction. However, we understand the importance of efficiency, and that's where AI becomes invaluable. We've found the perfect balance, allowing robots and humans to collaborate seamlessly in resolving customer issues effectively. As an extra bar we are collecting user feedback with ActionChat's widget in which we hope to improve up on greatly over the next few months.
But how exactly did ActionChat come into existence? A few years ago, I embarked on a project called LibDesk, a platform that enabled libraries to have a knowledge base and a live chatbot on their websites. Unfortunately, LibDesk, like many of my other projects, never saw the light of day. I had struggled with launching them. However, ActionChat is different, and you're witnessing its launch right now! A while back, I stumbled upon an inspiring article by Aaron Francis on Publishing your work increases your luck, which motivated me to make ActionChat a reality. Now, let's dive into how ActionChat came to be. I revisited my previous work on LibDesk, extracting and repurposing certain components, such as the live chat widget. I rewrote it entirely, using a different language—no longer Preact but instead embracing my newfound admiration for Alpine JS. Although it presented some challenges with compatibility, I managed to incorporate Alpine JS elegantly, and I intend to share the process in a future article. By leveraging the foundations laid during the development of LibDesk, such as session sharing and various other functionalities, this helped me get ActionChat up and running a little faster. While ActionChat was taking shape, several competitors entered the market, including SiteGPT Chatbase and a few others. While many of these platforms primarily focused on AI chatbots and perhaps offered a way for humans to leave an email, we took a fundamentally different, human-centric approach with ActionChat. I believe this distinction will set us apart from the crowd. Some other live chat competitors, like Intercom and Chrisbar, are beginning to realize the value of this approach, but I'm confident that ActionChat has a strong chance of becoming one of the best human-centric chatbot solutions available.
Of course, there were challenges we had to overcome. Thankfully many challenges had already been solved by the opensource community around Laravel. The OpenAI package built by Nuno, other packages include readability and the browser shot lambda. To accelerate development, we leveraged Filament to create the SaaS app rapidly. If you're curious about the specific software and packages we utilized, we will be providing a detailed blog outlining all the tools that went into building ActionChat very soon.
One significant challenge we faced was the occasional inconsistency in AI responses. Sometimes, the AI would fail to provide an answer aligned with the given prompt and context, which was quite perplexing. To mitigate this, we engaged in prompt engineering to improve accuracy. However, it's important to note that ensuring precise AI responses 100% of the time is still elusive in the current AI landscape. There are techniques available, such as querying AI multiple times using different models to rank and rate answers, which can yield more reliable results, however that will slow down response times.
In conclusion, I hold a strong belief that ActionChat is poised to improve your workflow in ways you have not yet even though about. Our seamless integrations with Slack, webhooks, and email are geared towards significantly improving response times. At its core, ActionChat is designed with to prioritize your users' experience. ActionChat is prepared to save you tons and time and we are planning many more exciting features and improvements, around shared inboxes, better customer feedback, and analytics. Our ultimate goal is to establish ourselves as the preeminent chatbot solution in the market, saving you - your customers time and money.
ActionChat is Alive! 🎉