AI & ML Development
Make your business
future-ready with AI & ML
Development Services.

Enhance your business to the next level with intelligence
on historical & real-time data.

Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.” – Ray Kurzweil, American inventor and futurist.

What is Artificial Intelligence?

Artificial Intelligence (AI) helps companies do more with less by automating extraordinary, but manual and time-consuming tasks. AI is mostly used to extract new insights, transform decision making, and drive improved business outcomes.

What is Machine Learning?

Machine Learning (ML) is a scientific study of statistical models and algorithms which is helpful to the computer systems in performing specific tasks. ML is an application of AI which helps systems to learn and improve from experience without being programmed.

Why We are the best fit for AI & ML Development?

We are An Innovative and Fast Leading Artificial Intelligence (AI) & Machine Learning (ML) Development Company. At “Swaran Soft”, We have a team of professional AI and ML Engineers and data scientists to help you turn the conventional operating system into new and smart systems. If it helps build architecture for data storage which can be used for data visualization, prediction, and decision making. The integration of AI and ML will build fault tolerance and highly automated processes. This tackled various domains like manufacturing, healthcare, logistics, and many more.

Our AI & ML Development Process

With the development of technologies and the increasing popularity of it, we can find data everywhere. Every character of data can be meaningful. Therefore, at “Swaran Soft”, we diligently collect all the information from your sources.

We follow a standard AI & ML development process to help you grow your business.

Tools & Technologies we use

IBM Watson

IBM's DeepQA project, Watson is the AI platform for business.

AI-One

It is a tool that allows developers to build intelligent assistants within the software applications.

Google AI

Google AI assists data scientists to find datasets stored in repositories across the web easily.

Deeplearning4

It is a deep learning programming library by Java and is compatible with any JVM language.

TensorFlow

TensorFlow is an open-source machine learning platform. It has libraries and community resources that allow researchers to push the state of the art in machine learning.

Apache Mahout

It produces free implementations of distributed machine learning algorithms that are primarily focused in the areas of classification, collaborative filtering, and clustering.

PyTorch

Being an open-source machine learning library, PyTorch is used for applications such as natural language processing.

OpenNN

It is a software library that implements neural networks.

Weka

It is a collection of machine learning algorithms that are used for performing data mining tasks.

Amazon Web Services

AWS offers scalable, reliable, and inexpensive services for cloud computing.

H2O

It is a fully open-source, distributed machine learning platform with linear scalability.

PredictionIO

PredictionIO is a machine learning server that allows developers and data scientists to create predictive engines and build smart applications for machine learning.

KNIME

It is an open-source reporting, data analytics, and integration platform.

Colab

It is a research tool by Google for machine learning education.

Scikit Learn

It is the most useful machine learning library in Python. Scikit Learn consists of a lot of valuable tools for statistical modeling and machine learning.

Keras.io

It is an open-source neural network library.

Shogun

Shogun, an open-source machine learning library, offers data structures and algorithms for solving machine learning problems. Benefits of AI and ML Development.

Use Cases

An Personal AI Email Assistant

Whether you work for a company or for yourself or are a student, email is an integral mode of communication and will play a major role in your success.

kWurd enabled by Artificial Intelligence can analyze your email before it is sent to give you personalized and contextual feedback. It works with Gmail and Outlook.

Getting your email writing skills correct can improve your productivity, relationships and business results.

Gain valuable insights from your video and audio files

Automatically extract metadata such as spoken words, written text, faces, speakers, celebrities, emotions, topics, brands and scenes from video and audio files. Access the data within your application or infrastructure, make it more discoverable, and use it to create new over-the-top (OTT) experiences and monetisation opportunities.

An Personal AI Email Assistant

Whether you work for a company or for yourself or are a student, email is an integral mode of communication and will play a major role in your success.

kWurd enabled by Artificial Intelligence can analyze your email before it is sent to give you personalized and contextual feedback. It works with Gmail and Outlook.

Getting your email writing skills correct can improve your productivity, relationships and business results.

Statistics

Analyze
Create your profile on Crystal and view your friends and coworkers for free.

Statistics

KWurd Engine
Use our Chrome Extension to view anyone’s personality.

Statistics

Overall Score
Get personalized, situation-specific advice to

An NLP and Deep Learning-based AI Coach

A well written email includes three parts: Clarity, Writing Style and Emotion.

Clarity
Means the email is highly readable, crisp, visually appealing, well- structured and has a clear purpose.

Writing Style
Means you followed the correct writing etiquettes. Do you have the right opening and closing? Are there no casual or informal words? All words are spelled correctly and have the right grammar. Is your email sounding like an amateur or a professional?

Emotion
Means the feeling the reader gets while reading your email. You could write a very clear and expert email but if the reader feels it is tentative, aggressive, negative, unsure, etc. it hurts your relationship and image with that person.

Gain valuable insights from your video and audio files

Automatically extract metadata—such as spoken words, written text, faces, speakers, celebrities, emotions, topics, brands and scenes from video and audio files. Access the data within your application or infrastructure, make it more discoverable, and use it to create new over-the-top (OTT) experiences and monetisation opportunities.

Features

The following list shows the insights you can retrieve from your videos using Video Indexer video and audio models:

Video insights

  • Face detection: Detects and groups faces appearing in the video.
  • Celebrity identification: Video Indexer automatically identifies over 1 million celebrities—like world leaders, actors, actresses, athletes, researchers, business, and tech leaders across the globe. The data about these celebrities can also be found on various websites (IMDB, Wikipedia, and so on).
  • Account-based face identification: Video Indexer trains a model for a specific account. It then recognizes faces in the video based on the trained model. For more information, see Customize a Person model from the Video Indexer website and Customize a Person model with the Video Indexer API.
  • Thumbnail extraction for faces("best face"): Automatically identifies the best captured face in each group of faces (based on quality, size, and frontal position) and extracts it as an image asset.
  • Visual text recognition(OCR): Extracts text that's visually displayed in the video.
  • Visual content moderation: Detects adult and/or racy visuals.
  • Labels identification: Identifies visual objects and actions displayed.
  • Scene segmentation: Determines when a scene changes in video based on visual cues. A scene depicts a single event and it's composed by a series of consecutive shots, which are semantically related.
  • Shot detection: Determines when a shot changes in video based on visual cues. A shot is a series of frames taken from the same motion-picture camera. For more information, see Scenes, shots, and keyframes.
  • Black frame detection: Identifies black frames presented in the video.
  • Keyframe extraction: Detects stable keyframes in a video.
  • Rolling credits: Identifies the beginning and end of the rolling credits in the end of TV shows and movies.
  • Animated characters detection(preview): Detection, grouping, and recognition of characters in animated content via integration with Cognitive Services custom vision. For more information, see Animated character detection.
  • Editorial shot type detection: Tagging shots based on their type (like wide shot, medium shot, close up, extreme close up, two shot, multiple people, outdoor and indoor, and so on). For more information, see Editorial shot type detection.

Audio insights

  • Automatic language detection: Automatically identifies the dominant spoken language. Supported languages include English, Spanish, French, German, Italian, Chinese (Simplified), Japanese, Russian, and Brazilian Portuguese. If the language can't be identified with confidence, Video Indexer assumes the spoken language is English. For more information, see Language identification model.
  • Multi-language speech identification and transcription(preview): Automatically identifies the spoken language in different segments from audio. It sends each segment of the media file to be transcribed and then combines the transcription back to one unified transcription. For more information, see Automatically identify and transcribe multi-language content.
  • Audio transcription: Converts speech to text in 12 languages and allows extensions. Supported languages include English, Spanish, French, German, Italian, Chinese (Simplified), Japanese, Arabic, Russian, Brazilian Portuguese, Hindi, and Korean.
  • Closed captioning: Creates closed captioning in three formats: VTT, TTML, SRT.
  • Two channel processing: Auto detects separate transcript and merges to single timeline.
  • Noise reduction: Clears up telephony audio or noisy recordings (based on Skype filters).
  • Transcript customization(CRIS): Trains custom speech to text models to create industry-specific transcripts. For more information, see Customize a Language model from the Video Indexer website and Customize a Language model with the Video Indexer APIs.
  • Speaker enumeration: Maps and understands which speaker spoke which words and when.
  • Speaker statistics: Provides statistics for speakers' speech ratios.
  • Textual content moderation: Detects explicit text in the audio transcript.
  • Audio effects: Identifies audio effects like hand claps, speech, and silence.
  • Emotion detection: Identifies emotions based on speech (what's being said) and voice tonality (how it's being said). The emotion could be joy, sadness, anger, or fear.
  • Translation: Creates translations of the audio transcript to 54 different languages.

Audio and video insights (multi-channels)

When indexing by one channel, partial result for those models will be available.

  • Keywords extraction: Extracts keywords from speech and visual text.
  • Named entities extraction: Extracts brands, locations, and people from speech and visual text via natural language processing (NLP).
  • Topic inference: Makes inference of main topics from transcripts. The 2nd-level IPTC taxonomy is included.
  • Artifacts: Extracts rich set of "next level of details" artifacts for each of the models.
  • Sentiment analysis: Identifies positive, negative, and neutral sentiments from speech and visual text.

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