Hey everyone nice to meet you all, I’m currently exploring a niche intersection between AI, healthcare, and sustainability—a high-demand area in the sustainability sector where I live. As a young entrepreneur, the challenge I'm facing involves managing diverse data systems within companies, especially when ensuring data security and compliance like HIPAA in healthcare. I'm considering developing an AI-driven service to streamline sustainability data management in healthcare businesses. This service would simplify data collection and reporting, reduce costs, and enhance compliance with regulations. However, the main challenge is the varied data storage practices across organizations, which complicates standardizing processes. I’m wondering if using AI to better integrate and interpret data might offer a more unified approach to managing sustainability metrics alongside patient data. Has anyone worked on or seen solutions in similar spaces? I'm interested in tools, technologies, or strategies that could assist in this integration, ensuring robust compliance while enhancing data operability. Any insights or suggestions would be greatly appreciated as I aim to develop this solution further. Thanks in advance for your help !!

Has anyone here read Automate Your Busywork by Aytekin Tank?

Hey friends! I want to share an important lesson I’ve picked up on my AI journey, and I hope it resonates with some of you. If you’re eager to dive into real-world AI applications, here’s a pro tip: blend coding skills with no-code tools. For example, shoutout to @Dave, who's doing an amazing job in this community teaching people to build AI projects with Python—huge respect for that! 🙌 But let me share something from my experience: a lot of clients don’t need a full-blown Python-based solution. Often, they’re just looking for a quick, simple automation or a chatbot. And guess what? Tools like Make.com, Flowise, and Relevance AI can help you deliver exactly that—fast and efficiently. Why spend days coding when you can create the same solution in a fraction of the time with no-code tools? It’s not just about saving your time—it’s also about saving your clients’ money and earning their trust. You’ll still make a solid income, but the lower cost and faster turnaround can make it easier for clients to say yes. Of course, when a project is too complex for no-code tools, that’s when you bring out the big guns—code-based solutions. And yes, you can (and should) charge more for those. The key is knowing when to use which approach. It’s all about finding the sweet spot between efficiency, profitability, and client satisfaction. What’s been your experience? Do you combine coding with no-code tools, or stick to one approach? Let’s discuss! 🚀

After two years of building with GenAI, here’s what I wish I’d had from day one... This has been a long time in the making, and I’m excited to finally pull back the curtain on what we’ve been building behind the scenes: The GenAI Launchpad — officially launched on Product Hunt today! 🎉 For the past two years, my team and I at Datalumina have been deeply involved in the world of AI, building solutions with large language models (LLMs) for clients across industries. Each project taught us so much about what it takes to bring AI to life in practical, high-impact ways. But there was one recurring challenge... We spent way too much time setting up project structures, handling integrations, and putting out fires in the infrastructure — leaving less time for the real AI work, the work that brings ideas to life. Not only was setup eating into our time, but we also found that the agent frameworks on the market were just too optimistic. Real-world use cases are more complex and demand reliability and precision that many frameworks simply can’t deliver. So, we got to work! 👷🏼‍♂️ And after two years of trial and error, working with every system and structure you can imagine, we built our own solution. The GenAI Launchpad is the result of our journey — a project repository that streamlines everything from initial setup to deployment, ready to handle the demands of production at scale. And the time savings? ⏳ We’ve calculated that it saves us over 50 hours per project on average, so we can dive right into the creative work that actually advances AI. Today, we’re launching the GenAI Launchpad to share that time-saving power with you — our community of fellow AI enthusiasts and builders. This is more than just a repository; it’s a battle-tested, engineer-approved blueprint that I wish I’d had when we started. It’s here to help you skip the headaches, bypass the boilerplate, and focus on what matters: building innovative AI solutions for real-world problems. If you’ve ever spent weeks fighting project setup, only to finally reach the real work, then you’ll understand why I’m so excited to share this.

ChatGPT can now search the web in a much better way than before. You can get fast, timely answers with links to relevant web sources, which you would have previously needed to go to a search engine for. This blends the benefits of a natural language interface with the value of up-to-date sports scores, news, stock quotes, and more. ChatGPT will choose to search the web based on what you ask, or you can manually choose to search by clicking the web search icon. https://openai.com/index/introducing-chatgpt-search/