ESPs containing Copy.AI
The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.
Companies that are included in this market leverage natural language generation (NLG) algorithms to generate text based on a given dataset or prompt. This technology can also be used in the advertising space for copywriting, to draft product descriptions for e-commerce, or even in journalism to help write new stories. All these solutions currently need some level of human oversight to make sure th…
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Research containing Copy.AI
Get data-driven expert analysis from the CB Insights Intelligence Unit.
CB Insights Intelligence Analysts have mentioned Copy.AI in 1 CB Insights research brief, most recently on Nov 18, 2021.
Expert Collections containing Copy.AI
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
Copy.AI is included in 4 Expert Collections, including Artificial Intelligence.
This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.
Digital Content & Synthetic Media
The Synthetic Media collection includes companies that use artificial intelligence to generate, edit, or enable digital content under all forms, including images, videos, audio, and text, among others.
Retail Media Networks
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Latest Copy.AI News
Nov 1, 2022
There are a growing number of startups that allow you to generate text based on prompts that are fed into a GPT-3-based generative AI system – could they be the future of legal drafting – at least at the very simple end? There are more coming to market, but one that Artificial Lawyer looked at today is Copy.AI , where you give the system prompts to create text for things like website marketing information, job descriptions, and even job rejection letters. Clearly the output here (see below) is way too basic at present to be used in a formal legal context, but the question is: can this reach the standards needed for lawyers to really use it? This site conducted two experiments. First, one for rejecting a job applicant because of: attire, refusal to work in an office, and that they smelt of elderberries (apologies to Monty Python) – see below. This was based on one of their templates and went quite well, even if it’s a bit comical. Input. Output The second was a very basic effort to create an NDA – which is NOT something that is already a template in their system – and although fun was nowhere near good enough for any kind of real-world use. Input Output The key thing here is that ‘the AI’ has made text that really is very readable. If someone said it had been made by a person you’d believe it. The text is grammatically correct, it’s relevant, it covers the key topics. In short, it works. The challenge is that it’s way too simple at present. But that could change. – So, what does this tell us? First we need to consider where this text comes from. Put simply it’s tapping the GPT-3 ‘library’ and then auto-creating a document that appears to most closely correspond to the multiple tags and prompts that have been given to it. Would this be useable by a lawyer as it is now? No way. This is way too generic and general, too short, too simple, and basically not really serious enough to be used. But could it get better? Yes, it could and there are others out there who are already exploring how to use this approach in a ‘serious’ way for legal doc generation. The main challenge is that GPT-3 and other library approaches, and no matter how clever the AI modelling is, are working off a collection of docs and then creating something fused from many pieces. Would it not simply be easier to create a traditional doc automation template that met your needs? For sure. But, perhaps there is a middle way here? I.e. you create a range of templates, perhaps with a large clause bank also, that meets your specific needs to create a library as such, and then use the generative AI approach to build what you want from there? That way you keep to legally sound source material that has its bona fides and company/law firm approval to use. Would that work? Potentially, yes. Although again, one can see some lawyers saying that if the idea is to avoid having to draft much on your own, then why not just use a template. While if there is no template and no precedent documents or language then how could a lawyer use such a generative approach with confidence, as the source docs would have to be generic? Then you get onto things like data privacy and client confidentiality. Lawyers can’t easily send documents they are drafting off to a third party like this without knowing exactly what’s happening with the information, where it’s kept, and if data gets folded back into the AI system’s library. Conclusion: this is very interesting, and as noted, there are players out there who are looking at serious legal use cases right now, but the more generic tools like this one have perhaps too many challenges to be of use at present. Could all of this evolve in the future and perhaps quite rapidly….? For sure. Share this:
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Copy.AI Frequently Asked Questions (FAQ)
When was Copy.AI founded?
Copy.AI was founded in 2020.
Where is Copy.AI's headquarters?
Copy.AI's headquarters is located at 1661 International Dr., Memphis.
What is Copy.AI's latest funding round?
Copy.AI's latest funding round is Series A.
How much did Copy.AI raise?
Copy.AI raised a total of $16.82M.
Who are the investors of Copy.AI?
Investors of Copy.AI include Wing Venture Capital, Sequoia Capital, Craft Ventures and Atelier Ventures.
Who are Copy.AI's competitors?
Competitors of Copy.AI include Jasper, Rytr, Metaphysic, Rephrase.ai, Hour One, Abyssale, Rosebud AI, Kalendar AI, Klleon, Synthesia and 12 more.
Compare Copy.AI to Competitors
Jasper is an AI content platform that helps teams create content for social media, advertising, articles, emails, websites, and art. The platform enables teams to create high-converting marketing copy, brainstorm new ideas, collaborate, and create content in a wide range of languages. Jasper was formerly known as Proof Technologies. The company was founded in 2018 and is based in Austin, Texas.
Rephrase.ai creates videos with text as inputs, using artificial intelligence (AI). It offers generative AI, facial mapping, audio cloning, and video creation for personal messaging campaigns. It uses cloning avatars of celebrities and influencers for brand promotions. The company was founded in 2019 and is based in Bangalore, India.
Dresma offers a digital platform that specializes in providing AI-powered e-commerce images that aim to enable instant scale and hyper-personalization for businesses.
Hour One is a synthetic video creation platform powered by AI. It was founded in 2019 and is based in Tel Aviv, Israel.
Concured is a predictive artificial intelligence platform for content marketers.
Splash, fka Popgun, is a software company specializing in music intelligence. It uses AI tools and techniques to develop new methods for music search, recommendation, and generation.
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