Fortify your Business
with Blockchain!

Disrupt your industry with blockchain industry revolution
solutions.

“Swaran Soft” is the leading Blockchain Solution providers developing enterprise-level applications and offering blockchain consultancy.

What is Blockchain?

The 21st century has evolved many technologies, and blockchain technology is one of the recent technologies to be introduced. The revolutionary technology impacts different industries. The concept of blockchain began with bitcoins - the cryptocurrency. So blockchain is just the digital information stored in public ledger. For a better understanding, the “Blocks” on the blockchain are made up of digital pieces of information, and the “chain” refers to the interconnection between that information. Since security has been considerable concern with the data analysis, blockchain development services assured that every transaction on a blockchain is secured, which happens with a digital signature that proves its legitimacy. As a result of the use of encryption and digital signatures for security, the data stored on the blockchain is tamper-proof, which remains unchanged.

Key Elements of the Blockchain

Distributed ledger Technology

All network participants have access to the distributed ledger and its immutable record of transactions. With this shared ledger, transactions are recorded only once, eliminating the duplication of effort that’s typical of traditional business networks.

Records are Immutable

No participant can change or tamper with a transaction after it’s been recorded to the shared ledger. If a transaction record includes an error, a new transaction must be added to reverse the error, and both transactions are then visible.

Smart Contracts

To speed transactions, a set of rules-called a smart contract-is stored on the blockchain and executed automatically. A smart contract can define conditions for corporate bond transfers, include terms for travel insurance to be paid and much more.

Tools & Technologies we use

Ethereuem

Ethererum is nothing but a distributed public blockchain network. It is blockchain technology based open software platform which allows developers to develop & deploy decentralized applications.

Hyperledger

Hyperledger is commonly used private blockchain, mainly by enterprises to make transactions between businesses more seamless & effective. To assist each case's custom needs, hyperledger has a modular blockchain development framework through which businesses can plug in different functions according to their particular needs.

Openchain

Open chain is an open-source spread ledger technology. It is suited for those organizations that are willing to issue and manage digital assets in a robust, secure, and scalable way. An open chain is more efficient than systems that use Proof of Work.

R3 Corda

Corda allows you to build interoperable blockchain networks that transact in strict privacy. Corda's smart contract technology will enable business to negotiate directly with value.

Big Chain

Big Chain functions as a database in the blockchain. The big chain allows developers and enterprises to position blockchain proof-of-concept, platforms and different blockchain applications with a blockchain database - this supports a wide range of industries and use cases.

Multichain

The Multichain technology is platform that helps users to establish a specific private blockchain. These private blockchain will be further useful for organizations for their financial transactions.

Verticals

Automobiles & Transportation

Government

Healthcare

Logistics

Trading

Insurance

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.

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

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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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