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BUSINESS-DRIVEN TECHNOLOGY

SMART BOT DEVELOPMENT

  • Chatbots
    • Web Chatbots
    • WhatsApp for Business Chatbots
    • Facebook Messenger Chatbots
    • Mobile App Chatbots
  • Smart Assistant, Smart speakers, Voice-Activated Assistants, Voice Apps
    • Google Home Bots
    • Google Assistant Tasks
    • Amazon Alexa Tasks
    • Amazon Echo
  • Smart Bots
  • Co-Bots, Collaborative Bots
  • Robo-advisors

INTELLIGENT AUTOMATION

  • Artificial Intelligence
  • Conversational Artificial Intelligence
  • Recommendation Engines
  • Cognitive Automation
  • Semantic Understanding
  • Anomaly Spotting
  • NLP, NLU
  • Instant Flow
  • Machine Learning, CNN, RNN, Reinforcement Learning, Neural Networks, SVM, Decision Tree, K-Means, Regression, Classification Algorithms

DIGITAL TRANSFORMATION

  • Business Process Digitalization
  • Online2Offline, Digital/Physical (OMO, IRL, AR)
    • Internet of Things (IoT) & Smart Home
    • Digital Voice-Enabled Business
  • Analytics, Big Data & Small Data
    • Data Integration and Processing from Different Sources
    • Data Catalog and Meta Data Management
    • Real Time Data Lake and Data Warehouse
    • Hadoop and Spark Clustering
    • Big Data Integration with ETL and ELT
  • Digital Workplace
    • Smart Collaboration
    • Knowledge Management
  • Blockchain for Business:
    • Distributed Ledger Technology (DLT)
    • Directed Acyclic Graph (DAG)
    • Web 3.0 & Smart Contracts

DATA-DRIVEN MARKETING 

  • Connected Experiences, Experience Economy, Experience Design
  • Personal Ads, Conversational Banners, Bannerbots
  • Hyper-Targeting, Look-a-Like, Contextual Marketing & Proximity Marketing
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INTERNET OF THINKING

BIG DATA AND BUSINESS
We help organizations drive strategic value from investments in AI and machine learning.

The three currently most prominent enterprise technologies are without doubt AI, blockchain, and IoT, and the driving factor behind them is data; people even go so far to proclaim that “data is the new oil”. New technologies enable collection, sharing, analysis of data, and automation of decisions based on them in ways that haven’t been possible before in what is essentially a data value chain.

But if data is not aggregated it represents just a cost, this is why we excel in any smart digital data capture techniques combined with AI-powered processing.

Chatbots have demonstrated their effectiveness in gathering Big Data.

With high volume of conversations daily, its velocity of information as well as the variety of questions and needs from users, make bots a potential source of information.

Collaborative bots, or co-bots powered by behavioral science, allow event-based targeting and personalized smart recommendations transforming the user experience in EXTENDED REALITY: Overlaying the real world with digital enhancements to extend human reality (THE END OF DISTANCE).

MICROSERVICES-BASED ARCHITECTURE
We master anything that requires a strong application programming interfaces (API) strategy to deliver relevant data in real-time to the various service layers that connect ecosystem players.

Microservices can be thought of as an approach to technical architecture. As opposed to a monolithic design, where applications are built with a single codebase, the microservices approach breaks down applications into simple components that perform recognized business functions. Each function is treated within the organization as a single service, equipped with its own team of engineers responsible for maintaining their own code and, importantly, API endpoints—URLs that point to the available functionality. What makes this approach different from previous service-orientated architectures is the provision that each microservice manages its own data, access to which may only be gained through the API endpoints. This single rule eliminates much of the complexity found in traditional architectures.

This approach means that a microservices-based architecture has the application modularity, scalability, and reliability to support technology partnerships at scale—doing so quickly and easily with seamless integration of services, and without hindering partners or customers.

PRIVACY-FIRST APPROACH
Giants like Google and Facebook thrive on personal data. In exchange for a list of your likes and topics you search for, they can offer a smarter and more personalized experience.

Customers understand that their data has value and are beginning to demand reciprocity. They’re happy to share their personal data in exchange of faster, easier-to-access services in return.

CONVERSATIONAL AI

LIFEdata creates end-to-end artificial intelligence solutions for enterprise brands who want an easier way to communicate the right information, at the right place, in real-time to their customers with our proprietary technology LIFEdata Halo.

Technology works if it’s an invisible enabler mimicking the human way of communicating.

People can’t express complex ideas with commands, a dialog is needed but today’s commercial natural language systems, like Alexa, Google Assistant, Siri, Cortana…, only understand commands.

LIFEdata Halo has been created to help technology better understanding us.

Our platform is a behavioral, conversational AI empowering natural dialog management for smart bots, smart assistants and voice apps.

Almost any company or product can reap the benefits of a conversational user interface (CUI) when targeted at the right context.

While working with almost all technologies on the market, we learned that almost all app or devices does not take into account the user’s physical world experience, nor does it gain insights from other devices. This narrow view of the user limits the app or device’s ability to impact the user’s choices. The way data is tracked today is narrow in scope, too.

This is why we’ve spent about 3 years integrating behavior science and event-based targeting to transform data into action through natural conversation.

DATA + MACHINE LEARNING = PERSONALIZED EXPERIENCES

TECHNOLOGIES

  • Google DialogFlow
  • Google TensorFlow
  • Google AutoML
  • AWS Lex
  • AWS SageMaker
  • AWS Cognito
  • AWS GreenGrass
  • Microsoft Azure Bot
  • Microsoft QNAMaker AI
  • Microsoft Azure Machine Learning Studio
  • Microsoft Azure Cognitive Services
  • Cloud Inference Stacks
  • ELK, Elastic, Kibana, Apache Lucene
  • ONNX AI, Pytorch
  • Salesforce TrasmogriphAI
  • Salesforce Einstein
  • Rasa AI, AutoKeras
  • Oracle GraphPipe
  • Vidora
  • Hadoop (Cloudera, Hortonworks, MapR, EMR)
  • Spark, Sparkflows, Mahout
  • MongoDB
  • InfluxDB, Apache Kafka, HDFS
  • PostgreSQL, Amazon Aurora
  • MySQL
  • Apache, Apache Cassandra
  • MariaDB
  • Docker
  • Kubernetes
  • AWS
  • Azure
  • Node.js
  • Python
  • React.js
  • Html 5
  • Bootstrap
  • Java 8
  • Express.js
  • Php
  • Javascript
  • Angular.js
  • Golang
  • C, C++
  • Webassembly
  • Solidity
  • iOS
  • Swift
  • Android
  • Ethereum
  • Hyperledger Fabric

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