Should I Build It Should I Build It
02 Jun 2025
Artificial Intelligence

A chatbot with AI for medical niche, using rag llm lnp

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Pivot

Current solutions aren’t working well, but there might be a way to adjust your approach. This isn’t about starting over, but rather making thoughtful changes based on what you’re learning.

Should You Build It?

No. Think & pivot.

Your are here

Based on similar product launches, your AI-powered medical chatbot idea falls into a category where a pivot is necessary. This isn't necessarily bad news. It suggests that current solutions aren't fully meeting user needs, leaving room for a refined approach. The fact that we found 5 similar products suggests there is demand, but competition is real. The average number of comments (5) indicates a medium level of engagement; people are talking, but not excessively. Unfortunately we have no buy or use signals for these similar products, but the existence of similar products on the market suggests that some users find value in this category. Your task is now to identify the shortcomings of existing solutions and to make sure you address those with your product.

Recommendations

  1. Start by identifying the top three complaints users have about existing medical chatbots. Scour app store reviews, relevant forums (Reddit), and social media. This will provide a solid foundation for differentiating your product.
  2. Building on the identified pain points, sketch out specific features or functionalities that directly address these issues. How can your chatbot be more accurate, reliable, or user-friendly than the competition? Consider focusing on a niche within the medical field to provide more specialized and accurate information.
  3. Before investing heavily in development, create a prototype or MVP and test it with 5-10 potential users. Get direct feedback on whether your solutions are hitting the mark and iterate accordingly.
  4. Explore focusing on a specific demographic or medical condition. A specialized chatbot addressing a niche need might find more traction than a general-purpose solution. Are there underserved patient groups or conditions where AI could make a significant impact?
  5. Set a clear deadline (e.g., 4 weeks) to evaluate the success of your pivot. Track key metrics like user engagement, accuracy of responses, and user satisfaction. Be prepared to iterate further or adjust your strategy if needed.
  6. Given the discussions around ChatMedical.ai, ensure your chatbot has robust safeguards to prevent misdiagnosis or incorrect medical advice. Consult with medical professionals and legal experts to mitigate potential risks and liabilities. Prioritize accuracy and responsible use of AI in healthcare.
  7. Study the discussions around Medical Chat. Emphasize the user-friendliness and helpfulness of your chatbot's interface. Make it intuitive for both patients and healthcare professionals. Positive user experience is key for adoption.
  8. Given that PromptVisor received feedback about potential bugs, prioritize thorough testing and quality assurance. Address any technical issues promptly and actively seek user feedback for continuous improvement. Transparency and responsiveness can build user trust.

Questions

  1. What specific data sources will your RAG LLM LNP use to ensure accurate and up-to-date medical information, and how will you validate the reliability of these sources?
  2. Given the potential for misuse or misinterpretation of medical advice from an AI chatbot, what ethical considerations and safeguards will you implement to protect users and ensure responsible use of the technology?
  3. Considering the competitive landscape of AI-powered medical chatbots, what unique value proposition or differentiator will make your solution stand out and attract users in a crowded market?

Your are here

Based on similar product launches, your AI-powered medical chatbot idea falls into a category where a pivot is necessary. This isn't necessarily bad news. It suggests that current solutions aren't fully meeting user needs, leaving room for a refined approach. The fact that we found 5 similar products suggests there is demand, but competition is real. The average number of comments (5) indicates a medium level of engagement; people are talking, but not excessively. Unfortunately we have no buy or use signals for these similar products, but the existence of similar products on the market suggests that some users find value in this category. Your task is now to identify the shortcomings of existing solutions and to make sure you address those with your product.

Recommendations

  1. Start by identifying the top three complaints users have about existing medical chatbots. Scour app store reviews, relevant forums (Reddit), and social media. This will provide a solid foundation for differentiating your product.
  2. Building on the identified pain points, sketch out specific features or functionalities that directly address these issues. How can your chatbot be more accurate, reliable, or user-friendly than the competition? Consider focusing on a niche within the medical field to provide more specialized and accurate information.
  3. Before investing heavily in development, create a prototype or MVP and test it with 5-10 potential users. Get direct feedback on whether your solutions are hitting the mark and iterate accordingly.
  4. Explore focusing on a specific demographic or medical condition. A specialized chatbot addressing a niche need might find more traction than a general-purpose solution. Are there underserved patient groups or conditions where AI could make a significant impact?
  5. Set a clear deadline (e.g., 4 weeks) to evaluate the success of your pivot. Track key metrics like user engagement, accuracy of responses, and user satisfaction. Be prepared to iterate further or adjust your strategy if needed.
  6. Given the discussions around ChatMedical.ai, ensure your chatbot has robust safeguards to prevent misdiagnosis or incorrect medical advice. Consult with medical professionals and legal experts to mitigate potential risks and liabilities. Prioritize accuracy and responsible use of AI in healthcare.
  7. Study the discussions around Medical Chat. Emphasize the user-friendliness and helpfulness of your chatbot's interface. Make it intuitive for both patients and healthcare professionals. Positive user experience is key for adoption.
  8. Given that PromptVisor received feedback about potential bugs, prioritize thorough testing and quality assurance. Address any technical issues promptly and actively seek user feedback for continuous improvement. Transparency and responsiveness can build user trust.

Questions

  1. What specific data sources will your RAG LLM LNP use to ensure accurate and up-to-date medical information, and how will you validate the reliability of these sources?
  2. Given the potential for misuse or misinterpretation of medical advice from an AI chatbot, what ethical considerations and safeguards will you implement to protect users and ensure responsible use of the technology?
  3. Considering the competitive landscape of AI-powered medical chatbots, what unique value proposition or differentiator will make your solution stand out and attract users in a crowded market?

  • Confidence: Medium
    • Number of similar products: 5
  • Engagement: Medium
    • Average number of comments: 5
  • Net use signal: 0.0%
    • Positive use signal: 0.0%
    • Negative use signal: 0.0%
  • Net buy signal: 0.0%
    • Positive buy signal: 0.0%
    • Negative buy signal: 0.0%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

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ChatMedical.ai's Product Hunt launch garnered positive feedback, with users praising its potential to revolutionize healthcare through global search, local care, and AI assistance. The AI integration was highlighted for promising seamless medical consultations, improved efficiency, and enhanced accuracy. There's interest in its application in developing countries, and the team's commitment to addressing this issue was noted. One user, however, suggested a potential future lawsuit. Many congratulated the team on the launch and wished them success.

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The general sentiment is positive and congratulatory regarding the Product Hunt launch. Users express excitement and appreciation for the product, with specific mentions of its helpfulness in the medical field. The AI-powered medical chat assistant is well-received for its initiative and functionality. Many users simply state their approval with words such as "Nice" and "Wow..nice."

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Vercel's AI SDK makes it easy to build chatbots using a wide variety of LLM providers.We made this demo to show how with Pinecone, you can leverage the Retrieval Augmented Generation (RAG) pattern to improve your chatbot with trustworthy and up-to-date data, and reduce hallucinations.We also made a Vercel template if you want to deploy your own chatbot like this: https://vercel.com/templates/next.js/pinecone-vercel-ai

Vercel's AI SDK simplifies chatbot building with LLM providers.

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