How did you add AI into your product ?
Anil Matcha
13 replies
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Dana Rudenko@danarudenko
Snov.io
Our whole product is about making the sales process easier and faster. It only made sense to integrate AI into one of the aspects of sales that takes the most time - writing emails. Our main challenge was to provide the consistency in results that it generated since we were integrating GPT into our platform so we couldn't control the output as much as we'd like. We've discovered some strategies that worked, but the work is far from finished. Still, we're proud to launch Email AI today!
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Eden AI
I would recommend using Eden AI for that. The best AI engines in one API. And we're launching soon: https://www.producthunt.com/prod...
CloudFunnels AI
In my app Tuberank Jeet, I did a deep integration of AI, adding the capability to write YouTube video titles, descriptions and more through AI.
Nautical Calculator
By adding openai package to python script. Flawlessly.
Everything that the user needs to google can be replaced with AI.
Mentor.AI
We integrated AI into our edtech application by leveraging cutting-edge natural language processing algorithms. Our AI technology enhances personalized learning experiences, provides intelligent feedback to students, automates assessments, and offers data-driven insights for teachers. This empowers our users with a more effective and tailored educational journey.
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Zeko AI
We took a much sought-after call when we reccieved some Operational Sucess in our Business model. We soon realised that adding AI , it will not just fasten up our Process but will provide best experience to our users. We embedded AI into our product by leveraging OpenAI's GPT and our in-house LLM. These tools allow our hiring automation solution to efficiently handle complex tasks and scale with demand.
We are taking into count iterative feedback-based improvements, & soon we will be ready to launch an AI-powered tool that revolutionizes hiring by streamlining processes and enabling strategic focus.
We implemented natural language processing (NLP) to enhance our product's chatbot functionality. It improved customer interactions
Upon seeing this question, I was reminded of an interesting phenomenon I recently noticed: despite many people expressing opposition to AI, investors continue to pour funds into AI products. It's like the AI product I launched yesterday, which managed to secure a daily ranking of 17 without any promotion. I must admit, it was quite surprising. I'd like to take this opportunity to share some of my thoughts on the application of AI.
The inspiration for my product came from observing the mixed reactions people had towards ChatGPT. Through careful communication with individuals, I discovered that the main challenge lay in two aspects: the ability to ask the right questions and to consistently provide the correct prompts to ChatGPT. Often, when users encounter a problem, their immediate instinct is to search for answers. However, here lies a fundamental issue: when you lack understanding of the problem you're facing, it becomes difficult to ask the "right" questions accurately.
That's when the idea of AI multi-agent systems struck me as a potential solution. By introducing AI agents with expertise in specific domains, users simply provide a topic (prompt), and these AI agents engage in an ongoing process of questioning and discussion towards a specific goal. This collaborative exchange of ideas generates a series of prompts that form the very essence of the comprehensive solutions users truly desire. Taking it a step further, we can conduct brainstorming sessions based on these prompts and AI roles, resulting in holistic solutions rather than scattered answers.
Just imagine finding yourself in a situation where you have an important meeting, a research paper to write, or a creative task that demands your brain to be in turbo mode, but you find yourself stuck in an "inspiration desert." This is where a product like ours comes in, helping you generate valuable prompts and providing you with additional information and answers based on those prompts. I believe this could be truly beneficial and helpful.
Could you kindly share your experience of integrating AI into your product on Product Hunt's discussion thread? I'm excited to learn about the innovative ways you've leveraged AI technology!
Savvy Planner
Quite easy, actually. I developed and trained our models on my own using Python tools, then just created the necessary APIs using the Flask framework so that they're compatible with the standard Node.js backend side.
I'm a data scientist + web developer (full-stack) + project manager, so it wasn't a difficult thing to fulfill. But it's been a long and bumpy ride to get all these skills😁
Integrating AI into our product was a deliberate and strategic decision aimed at enhancing its capabilities and providing a more intelligent and personalized experience to our users. To accomplish this, we followed a systematic approach. We began by thoroughly assessing our product requirements and identifying areas where AI could make a significant impact. We then conducted extensive research to understand the latest advancements and best practices in AI technology. This allowed us to select the most suitable AI techniques and algorithms for our specific use cases.