Hi!
I'm excited to introduce SendStock AI, the first tool designed exclusively for image contributors on Adobe Stock, Shutterstock, Freepik, and more, to generate perfect titles and keywords in seconds. I built SendStock to save you time every week and eliminate the risk of rejections or account issues.
I'd love your feedback:
* What's your biggest pain point today when tagging and titling images?
* What platforms do you contribute to, and what are your metadata challenges?
* What feature should we improve?
Give us your feedback below and help shape the future of metadata automation!
That's super helpful. I used to sell images through those platforms years ago, and I remember how much work went into all of that. This is such a time saver.
This AI-powered metadata generation tool for image contributors sounds incredible! 🎉 Automating bulk creation while ensuring compliance will save so much time and effort. Really excited to see how it streamlines uploads and makes managing edits easier both locally and online. Can’t wait to try it out! 🚀📸
Hey Michael, congratulations on the launch of SendStock AI! This is a brilliant example of using AI to solve a tedious, high-value problem for a specific niche. As a builder myself, I have huge respect for this kind of focused execution.
While I'm not a stock photo contributor personally, I've worked with many designers and marketers, and I know that metadata is the unglamorous, yet critical, part of the workflow. You're not just saving time; you're increasing the discoverability and earning potential of each asset.
To answer your question from a product perspective: one of the biggest challenges I could foresee is maintaining "authenticity" and avoiding "generic" AI-generated keywords. How does SendStock AI ensure the keywords are not only technically accurate but also capture the unique mood, style, or conceptual nuances that make a photo stand out to a human buyer? Perhaps incorporating user feedback to refine keyword suggestions could be a powerful loop.
This is a fantastic tool with a clear ROI for contributors. Wishing you great success
@felix_foster Thank you for your message of support and encouragement.
To answer your question, AI models currently don't understand "context." To work around this, I've implemented an intermediate (non-mandatory) step to add context to the AI model's instruction.
The application also includes a whole set of parameters that take into account the regulations, requirements, and "best practices" for submissions that the platforms require.
@mickael_bellun Thanks for the detailed reply, Mickael! That makes perfect sense.
Your approach of adding an intermediate step for context is a really smart way to engineer around the current limitations of the models. It shows a deep understanding of both the user's need and the AI's capabilities.
I really appreciate your transparency. It's clear you've thought deeply about this. Keep up the great work!
Replies
SendStock AI
Instance
That's super helpful. I used to sell images through those platforms years ago, and I remember how much work went into all of that. This is such a time saver.
Good luck with your launch.
SendStock AI
@filipgres Thank you.
It's never too late to get back into it; contributing to inventory always provides additional income. 😊
Pokecut
This AI-powered metadata generation tool for image contributors sounds incredible! 🎉 Automating bulk creation while ensuring compliance will save so much time and effort. Really excited to see how it streamlines uploads and makes managing edits easier both locally and online. Can’t wait to try it out! 🚀📸
Auto-generating stock metadata? 📸⚡ That’s a huge time-saver for contributors. Curious how well it handles niche content tags! 🧠🏷️
Hey Michael, congratulations on the launch of SendStock AI! This is a brilliant example of using AI to solve a tedious, high-value problem for a specific niche. As a builder myself, I have huge respect for this kind of focused execution.
While I'm not a stock photo contributor personally, I've worked with many designers and marketers, and I know that metadata is the unglamorous, yet critical, part of the workflow. You're not just saving time; you're increasing the discoverability and earning potential of each asset.
To answer your question from a product perspective: one of the biggest challenges I could foresee is maintaining "authenticity" and avoiding "generic" AI-generated keywords. How does SendStock AI ensure the keywords are not only technically accurate but also capture the unique mood, style, or conceptual nuances that make a photo stand out to a human buyer? Perhaps incorporating user feedback to refine keyword suggestions could be a powerful loop.
This is a fantastic tool with a clear ROI for contributors. Wishing you great success
SendStock AI
@felix_foster Thank you for your message of support and encouragement.
To answer your question, AI models currently don't understand "context." To work around this, I've implemented an intermediate (non-mandatory) step to add context to the AI model's instruction.
The application also includes a whole set of parameters that take into account the regulations, requirements, and "best practices" for submissions that the platforms require.
@mickael_bellun Thanks for the detailed reply, Mickael! That makes perfect sense.
Your approach of adding an intermediate step for context is a really smart way to engineer around the current limitations of the models. It shows a deep understanding of both the user's need and the AI's capabilities.
I really appreciate your transparency. It's clear you've thought deeply about this. Keep up the great work!
seems really helpful for content creators.
Smoopit
Wow! Maybe you can increase your TAM by also generating captions for social media?