Companies are increasingly using artificial intelligence services, especially when it comes to automating internal processes or improving their customers’ experience. The strong development of AI now makes it a commodity. These functionalities can be found in several fields: health, human resources, industry, etc.
These AI technologies come in various forms:
- Image processing: object detection, facial recognition, text extraction, etc.
- Text analysis: keyword extraction, sentiment analysis, etc.
- Machine translation: customer relations, document translation, etc.
- Audio transcription: phone call analysis, video subtitling, etc.
- Prediction: sales prediction, production optimization, etc.
The behemoths of the cloud market (Amazon Web Services, Microsoft Azure or Google Cloud) offer solutions that provide access to this type of service, but there are also smaller providers that are already competing with them: Mindee, Dataleon, Deepgram, AssemblyAI, Rev.AI, Speechmatics, Lettria, etc. Because of their specialization, they often manage to offer very powerful solutions.
In the AI sector, there are many different suppliers offering various solutions. As a result, it is complicated to correctly choose the solution that is best suited to one’s needs, because performance depends on the user’s data. A transcription of audio into text will not necessarily be the same using Google Cloud as using AssemblyAI, for example. Indeed, depending on the language used, one provider might generate a better transcription in Spanish than another.
To see for yourself, here are some more in-depth analyses demonstrating the difference in performance of several providers with concrete examples of data for: vision,OCR, prediction, object detection, audio-to-text transcription and facial recognition. An AI comparator also provides quick access to public benchmarks between vendors based on public data: compare.edenai.run.
To address the complexity of this market, Eden AI is developing an API that allows users to access the AI engines of their choice. The company combines these engines and provides a single entry point to compare, test and use them. Offering different levels of performance, price, and quality of response depending on the data processed, this is where Eden AI stands out thanks to its unique, multi-vendor approach.
The company’s ambition is to democratize the use of AI to make it easily accessible to all developers. To achieve this promise, Eden AI focuses on three main axes:
- The company positions itself as an aggregator operating a standardization: it gives the possibility of using several engines at the same time, as well as being able to replace and combine them with the greatest simplicity. Eden AI takes care of centralizing costs to save time for users.
2. It also develops the “Genius” functionality: an automatic and dynamic recommendation based on each user’s data. Eden AI redirects to the best solution and the engines adapted to the user.
3. Finally, the user will have to combine several AI engines for different uses. The “Pipelines” tool allows to directly create a data processing flow allowing to combine AI solutions instantly.
To carry out its project, Eden AI recently raised 1.5 million euros, during a round of financing supported by the Parisian gas pedal 50 Partners, but also by renowned business angels: Olivier Pomel (Datadog), Nicolas Dessaigne (Algolia), Sébastien Pahl (Docker), Julien Lemoine (Algolia), Benjamin Fabre (DataDome), Laurent Letourmy (Ysance), Jean-Baptiste Aviat (Sqreen), Georges Gomes (Div Riots), and Thomas Grange (Botify) :
Eden AI is thus developing in a booming market, with the ambition of making AI accessible for all developers. To do this, the company wants to expand its team with talented recruits: edenai.co/careers.
Translated from Eden AI lève 1,5 millions d’euros pour unifier les API d’IA/ML
