Back to insights

Applied AI APIs

By Marcus Lambert

Online AI services; the two ends of the spectrum differ significantly. At one end there are infrastructure solutions which grant more control and customisation. Whereas at the other, we have pre-built API services. Here at Omobono, we're finding that many solutions now involve both of these, and over the past year, we've been using more service APIs. Here's a breakdown of some of our favourites.


Broadly they’re divided into these areas of implementation:

  • Image and facial recognition
  • Machine learning and predictability
  • NLP, text analysis, and sentiment analysis
  • Language and speech translation

Applied AI APIs
Image and facial recognition


Having been on the market for less than a year, True Face has already established itself as a leader amongst similar offerings with a range of excellent features like spoof detection and blurring of unknowns. Its beta also sports nice features around gender and age detection.

2. Kairos

Karios has a useful feature set which includes, gender, age, attention, emotion, ethnicity and facial matching.

3. Amazon Rekognition

A great fit if you are an AWS user with features like suspicious content recognition, text in image detection, face comparison and emotion detection. Amazon Rekognition is very easy to use.

4. Lambda Labs

Face detection and facial feature location.

5. Eyedea Recognition 

Besides facial recognition, it has a range of number plate, car make and model recognition models as well.

6. FaceRect

A straightforward and free API for face detection.

7. IBM Watson Visual Recognition 

Mature facial recognition API

Main features include:

  • Understands other objects in an image
  • Determines the age and gender of people in photos
  • Can find similar images to the one previously analysed
  • The API can be trained

8. Skybiometry Face Detection and Recognition

The face detection by Skybiometry is also a reliable solution that allows for the detection of people with or without glasses, captures multiple faces in the photo and analyses their emotion.

9. Antimetrics Face Recognition

To analyse and recognise faces more efficiently, this API can transform a 2D picture into a 3D model. The recognition is performed by detecting a face and comparing it to an existing set of faces until the match is found.

10. Face ++

This API can be used for online advertising and is fully featured with detection, landmarking, comparison and searching. It also has an offline SDK for iOS and Android. It can provide facial detection and comparing even when a user’s phone has no reception. This gives a broader range of possibilities to developers.

11. Microsoft Cognitive Services

With many of the same features as Google Cloud Vision and IBM Watson, including celebrity detection and OCR. An exciting piece of this API is that in addition to listing tags along with confidence predictions it also attempts to generate a natural-language description based on those tags.


Upstart image recognition service that also uses a REST API. One interesting aspect is that it comes with a number of modules that help tailor its algorithm to particular subjects, like weddings, travel, and food.

13. CloudSight

Taking a slightly different approach to image recognition. CloudSight’s website offers significantly fewer details than some of their competitors. Providing a combination of algorithmic and manual (meaning human) tagging.

14. Google Cloud Vision 

Google’s visual recognition API based on the open-source TensorFlow framework and using a REST API detects individual objects and faces. It contains a pretty comprehensive set of labels and also comes with a few bells and whistles, including Optical Character Recognition (OCR) and integration with Google Image Search to find related entities and similar images from the web.

Machine Learning and predictability

1. Big ML 

BigML provides a selection of Machine Learning algorithms by applying a standardised framework.

BigML covers not only classification, regression and time series forecasting but also unsupervised learning tasks such as cluster analysis, anomaly detection, topic modelling and association discovery.


An E-commerce recommendation engine.


MLJAR provides a selection of Machine Learning algorithms that you can tune and deploy models as services to the cloud.


NLP, text analysis, and sentiment analysis

1. Bitext

An NLP API that provides support for bot building, customer feedback analysis and general NLP tools. It also includes features like Lemmatization, Post Tagging, Language Detection, Phrase and Entity Extraction and Sentiment.

2. Datum Box

This API provides, Sentiment Analysis, Topic Classification, Language Detection, Subjectivity Analysis, Spam Detection, Reading Assessment, Keyword and Text Extraction

3. Microsoft Cognitive Services

With features like Bing Spell Check, Language Understanding (LUIS) Intent recognition using NLU, Text Analytics and Translator Text. This is an API we’ve used extensively to build bots for clients.

Language translation and recognition

1. Google Cloud Speech-to-Text

2. Houndify

Automatic Speech Recognition (ASR) and Natural Language Understanding (NLU) all in one engine. This is used a lot in automotive and OEM industries.

3. Microsoft Cognitive Services

Speech to text, Text to Speech, translation across 60 languages, Speaker recognition and a custom speech service that you can train.

We are the digital experience company for business brands.

In today’s connected world, experience is brand.

So we help you create better experiences for your customers, employees, partners and stakeholders. Ones that work in empathy with them to achieve their goals, engage and delight them, and build brand loyalty.