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Large cloud vendors like Amazon, Google, Microsoft, and IBM offer APIs enterprises can use to take advantage of powerful AI models. But comparing these models — both in terms of performance and cost — can be challenging without thorough planning. Moreover, the siloed nature of the APIs makes it difficult to unify services from different vendors into a single app or workflow without custom engineering work, which can be costly.
These challenges inspired Samy Melaine and Taha Zemmouri to found Eden AI (previously AI-Compare) in 2020. The platform draws on AI APIs from a range of sources to allow companies to mix and match models to suit their use case. Eden AI recently launched what it calls an AI management platform, which the company claims simplifies the use — and integration — of various models for end users.
Prior to starting Eden AI, Melaine and Zemmouri worked as consultants on data science and AI projects at startup DataGenius, where they collaborated with corporations to leverage AI models from various providers. While there, they realizated data processing projects often involve several different APIs and obtaining the best performance — and cost savings — might require combining models from different providers, like Google Cloud’s optical character recognition combined with IBM’s translation and Amazon Web Services’ keyword extraction.
Unifying AI models
Eden AI’s new offering, which can deployed in the public cloud or on-premises, connects to AI models for computer vision, natural language processing, speech recognition, and machine learning to allow users to access, test, and compare the costs of vendor-specific models. From a dashboard, companies can create AI projects, generate keys, complete payment, upload datasets, and manage and delete AI projects from different providers.
For example, using Eden AI, a company could feed a document in Chinese into Google Cloud Platform’s optical character recognition service to extract its contents. Then it could have an IBM Watson model translate the extracted Chinese characters into English words and queue up an Amazon Web Services API to analyze for keywords.
Eden AI makes money by charging providers a commission on the revenues generated by its platform.
“We are driven by the desire to democratize the use of AI by offering our users simplified access to these technologies. In particular, we want to highlight innovative providers offering high-performance engines,” Eden AI writes on its website. “We believe that the use of AI engines will continue to develop in companies and that it becomes a commodity that must be easily integrated. We are therefore working to guarantee to facilitate the test and use of different AI engines.”
In the future, Eden AI aims to integrate open source models and build an algorithm that can automatically suggest the best AI model — trained in part on metadata from Eden AI’s customers. The company also plans to enable users to deploy their own algorithms on the platform, which they’ll be able to benchmark against third-party models to gauge their relative performance.
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