An insight management platform for computer vision model performance. Manot pinpoints where, how, and why computer vision models fail. It accelerates model refinement and redeployment processes by 10x, boosts accuracy by 20%, and reduces costs by 32%.
Hey Samvel! Excited to have your feedback on the platform.
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Consistently assessing and enhancing models is an essential component of any robust AI system. This becomes even more important in the realm of computer vision. Great too see Manot addresses the problem with a right approach. Congrats on the launch!
@dmitri_melikyan thank you for your thoughts! Indeed, computer vision is more complicated and there are a lot of mission-critical applications where reality is essential.
This is very cool. As a product manager, I've definitely felt the pain of endless feedback loops of solving customer problems that pop up once we're in production, then going back to fix those, only to realize that there's some other edge case we've missed. A forward-looking tool like this could really help us be proactive instead of reactive!
@sudosharma Thank you for sharing your experience and summarising the problem-solution! Hope our solution will help you to streamline your AI development pipeline. Let me know if you have any questions while trying it out.
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Love continuous feedback loop between pre and post production environments and key stakeholders. Having this process automated streamlines collection of key model behavior quality metrics in production and allows model developers to make faster changes to their ML algorithms based on empirical data in production
This would have been amazing during my time in Product at Amazon. Saving resources in the engineering/development cycle is the name of the game once you've laid out what you're going to build, and I can see this being extremeley helpful in automated robotic warehouses, security devices and automated delivery system development and improvement.
@michael_laframboise Thank you for sharing your experience! I encountered a similar challenge while working on object detection tasks involving high-resolution images. Now that you're acquainted with Manot, we're eager to witness the positive impact it brings to your work!
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This would have been amazing during my time in product at big tech. Saving resources in the engineering/development cycle is the name of the game once you've laid out what you're going to build, and I can see this being extremeley helpful in automated robotic warehouses, security devices and automated delivery system development and improvement.
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