Content Guardian AI
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Don't depend on just one AI checker No single checker can guarantee complete confidence. We integrate with leading AI content detectors to give unparalleled confidence that your content appears to be written by a human. One-click, Eight Checks Demo link story.screenspace.io/2161397443/0cb05324
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Content Guardian AI's answer
Content Guardian is the first multi-AI Content Detector to connect to multiple content checker services simultaneously. 8 checks in 1 click.
Content Guardian AI's answer
AI is a very fast-paced environment with new advances happening weekly. Not all AI Content Detector models can keep pace. This is where Content Guardian comes in. You can get a much higher level of assurance about the accuracy of the results as we check up to 8 checkers and provide an aggregate score based on our algorithm. We update this regularly so it is reflective of the latest developments in AI LLM.
Content Guardian AI's answer
We have 3 target audiences. Writers, Media publishers and Education.
Content Guardian AI's answer
Next.js PHP Javascritp Node.js
Content Guardian AI's answer
Content Guardian was born out of necessity. We all work with external collaborators and we wanted to have confidence that the content was authentic and original.
We felt having to rely on one AI checker left the business open to a wider margin of risk that it was solely generated by AI, so we started to use multiple AI Content Checkers.
This became very cumbersome for the team, so we decided to create a tool that seamlessly integrates into our workflow whilst connecting to multiple AI Content Checkers. We wanted to build a tool that provides convenience and higher assurance that we can spot unauthentic content.
The tool is ready to be released to the wider world. So here it is!
We will be actively developing the tool with new features and tweaks to make it the best tool it can be.
Based on our record, Scale Nucleus seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago
To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 years ago
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