Solving problems and unlocking value with multisensory machine intelligence
Boost operational efficiencies. Transform the customer experience. Enable actionable data insights. Secure your digital ecosystem. Entefy solutions arrive at the intersection of digital transformation and limitless use cases.
Entefy provides end-to-end AI and hyperautomation solutions that address diverse industry needs. Entefy's industry solutions take full advantage of Entefy’s configurable AI technology to enable implementations meet specific organizational or industry needs in a matter of days or weeks, not months or years.
Streamline manufacturing. Add new capabilities. Deliver on safety.
The aerospace and defense (A&D) industry has been undergoing digital transformation for a number of years and is beginning to reap the benefits of advanced AI and automation. From design and manufacturing to maintenance and operations, machine learning helps A&D providers bring technological advancements and improved safety to aircraft as well as space and defense systems. Applications of AI in the A&D industry help improve efficiency, lower costs, and build supply chain resiliency.
This includes AI-powered systems designed to enable everything from smart maintenance to improved equipment readiness and autonomous aircraft operation. The underlying technologies powering these capabilities have far reaching benefits, allowing for improved fuel efficiency, increased automation in operations and manufacturing to reduce reliance on human labor, robust flight training with virtual reality and AI-powered simulators, and even optimized product design and development.
Critical system failures before they happen
Security threats and weather while in flight
The passenger experience before, during, and after each flight
Fleets of IoT sensors and connected systems
Key performance data from every flight
Design for efficiency across the entire product lifecycle
Production and operational costs
Safety and compliance concerns
Processes, workflows, and tasks
Sprouting new opportunities with smart farming
Technology is rapidly redefining nearly every aspect of the global economy and agriculture is no exception. In recent years, a number of core technologies—IoT, machine learning, virtual reality, automation—have come together to transform farming production. Agricultural technology, commonly referred to as AgTech, is reshaping how farmers improve yield with shrinking resources, a necessity in the age of sustainable farming.
In agriculture, AI-powered systems are enabling greater visibility across the value chain, with smarter tools to help monitor and manage crop health and performance, as well as overall supply chain traceability. Advancements in automation continue to make their mark on everything from self-guided farm vehicles to AI-powered market demand and risk modeling, helping farmers produce more with less.
Entire fleets of loT sensors
Crop yield to environmental factors
Optimal harvest conditions
Crop health and performance
Labor costs, equipment downtime, and waste
Market demand and risk factors
AI drives the automotive industry forward
The automotive industry is witnessing a distinct technological revolution catalyzed by three simultaneous transformations: Transition to electric motors, the growth in the shared economy, and advances in artificial intelligence. AI/machine learning is changing not only how vehicles are designed, built, and perform but also inventing new customer experiences. This revolution in the automotive industry is expected to create more jobs, boost our economy, and reduce emissions.
Whether for consumers or businesses, AI is enabling countless use cases for the automotive industry. Examples include: Design and engineering efforts focused on power and fuel efficiency as well as simulations to lower costs in testing; Supply chain and manufacturing optimization such as demand forecasting, cost reductions, predictive maintenance, inventory management, and sustainability; New customer and driver experiences to improve safety and comfort.
Costs, routes, energy usage, supplier selection, and more
customer experience in new ways
Safety for drivers and passengers
Downtime with predictive maintenance
Key performance data from every drive
Vehicle features with advanced voice controls
Fleet and inventory management
Demand for vehicle sales and ride sharing
IT infrastructure and vehicles against cyber threats via autonomous cyber
Engaging with consumers in exciting new ways
The COVID-19 pandemic has brought forth unprecedented disruption to the consumer goods sector. Consumer goods companies continue to grapple with abrupt shifts in consumer behavior and supply chains as well as widespread labor shortages. Combined, these disruptions have created a new operating reality for many organizations across the value chain, where agility and resiliency are fast becoming the two qualities needed most to ensure success. With the rapid pace of new market changes, AI and automation are helping companies build new ways of engaging with consumers with greater efficiency and flexibility.
For those who manufacture and sell products directly for consumer use, machine learning has proven effective in reducing costs, increasing sales, and deepening customer loyalty. AI is helping put the right products in front of the right customers with personalized shopping experiences all over the world. Machine learning is enabling entirely new capabilities for consumers, such as visual search, AR/VR shopping, and smart recommendations. AI and automation are also allowing businesses the opportunity to unearth valuable insights from customer and market data, helping optimize operations, sales, and delivery of products.
Your direct to consumer (D2C) offerings
Customer engagement with hyper-personalization
Sales via smart recommendations
Brand loyalty using insights from customer data
Historical data to improve decision-making
Valuable trends and patterns in consumer behavior
Logistics, delivery, costs, and inventory
Insights into manufacturing pain points and bottlenecks
AI to marketing efforts to increase engagement and conversions
AI is earning its seat in education
What does it mean to bring education into the 21st century? Education technology, or EdTech, is helping unlock potential in the education industry in the face of historic disruptions caused by the COVID-19 pandemic. The pandemic swiftly changed the traditional educational experience for the nearly 1.6 billion learners and 100+ million teachers and school personnel globally. Much of what has ensued is centered on virtual learning supported by a set of technologies dominated by AI and cloud computing.
AI in education provides students with much needed personalization, specialty tutoring powered by chatbots and digital agents, as well as 24/7 location-agnostic access to learning at their own pace. For educators, AI provides task automation to evaluate student performance, answer questions, and help close the educational gap. With AI tools, educators can spend more time teaching and less time on lesson planning, grading, or administrative tasks.
24/7 customized learning
Student preferences and aptitude
Educators and administrators with data-driven insights
Data to inform policy and other key decisions
Outcomes and overall engagement
Capacity for research and learning
Operational costs and improve productivity
Administrative tasks and reduce workloads for educators
Smart content to enhance interactivity and engagement
Smarter ways to power our future
Everything we do requires energy and, today, 80% of that need is satisfied by fossil fuels, such as oil, gas, and coal. Aside from environmental concerns, fossil fuels are non-renewable, putting our future at risk with their finite supply and rising costs. The rapid pace of industrialization and modernization has placed our society at a crossroads where the increasing demand for energy, shrinking fossil fuel reserves, and pressing climate change mandates meet. And it is at this crossroads that a growing number of businesses, non-profit organizations, governments, and academic institutions are leveraging advanced AI to solve problems and invent new solutions.
Organizations in the energy and utilities eco-system are using machine intelligence, blockchain, and big data to help optimize energy production, costs, delivery, usage, emissions, and safety. AI is proving effective in tracking and maintaining assets with an eye on identifying defects and preventing failure. Utility companies are also using chatbots to improve customer service and education, giving their customers better ways to manage or monitor their energy consumption. Innovators in this space are using machine learning to design new solutions, tools, and business models.
Streams of usage data at grid and user levels
Energy demand, supply, and costs
Anomalies and inefficiencies across the value chain
Key areas of operations with advanced automation
Uptime with predictive maintenance
Customer dissatisfaction and minimize churn
Quality control and regulatory compliance
Entire fleets of loT sensors & smart machines
Blockchain and AI disrupt (and modernize) financial services
The financial services industry is experiencing significant disruption due to the rise of new technologies that have enabled algorithmic trading, decentralization of finance via cryptocurrencies and blockchain, and the whirl of digital fraud. Today, financial services firms require sophisticated systems to ensure business continuity, weather market volatility, secure assets, keep customers happy, and comply with ever-evolving regulatory requirements.
Applications of AI in financial services range from 24/7 customer support chatbots to AI-powered loan underwriting, fraud detection and prevention, automated workflows and tasks, personalized banking and money management, computer vision and natural language processing to analyze documents, and predictive modeling to accurately forecast revenue, stock prices, and risk.
Pricing and directionality for stocks and cryptocurrencies
Lending and underwriting processes
Fraudulent behavior and activity
The customer experience with tailored services
Pricing and trading trends across products
Every portfolio on a per-client basis
Streams of news and market data
Key events and decrease portfolio risk
Improving public outcomes with transformative technologies
Complexity defines our modern world. Gone are the days when people and society were expected to move at a relatively predicable pace. Today, information overload and unanticipated social, health, political, and economic disruptions are compelling government entities to adopt advanced technologies in order to better ensure seamless delivery of services, public safety, and overall operational resiliency.
Technology transformation for government is being accelerated via use of machine learning, IoT, and automation. These technologies are designed to accelerate critical data sharing, enhance remote workflows, uncover hidden insights crucial to the work of the intelligence community, deliver personalized services, create smarter cities, better prepare for and respond to disasters, and improve physical and cyber defenses.
IT infrastructure for speed, scale, and security
Operational resiliency with AI and intelligent automation
Critical data to enable fluid data sharing among teams and departments
Productivity using smart communication and collaboration tools
Ethics in the complex and fast-evolving worlds of big data and AI
Seamless delivery of services to constituencies
Data records with adaptive privacy management
Defense and national security readiness with cognitive computing and advanced analytics
Cybersecurity threats and enable protection via autonomous cyber
AI paves a smarter path to health and happiness
From patient care to drug manufacturing to public health, digital and intelligence transformation is helping organizations create business value and make lives better for many. The market for healing is vast and complex, powered by sophisticated science from a myriad of disciplines. Success in the health care sector is of paramount importance to our society—literally a matter of life and death in many cases. And that success is being accelerated via applications powered by advanced AI and automation.
Use cases involving machine intelligence in health care and life sciences are diverse. These use cases are generally aimed at cost reduction, better engagement between providers and patients and modernizing operations to accelerate research, development, or delivery of products and services. Further, AI is helping build trust and transparency in health care by streamlining regulatory compliance and protecting against fraud and ever-growing cybersecurity threats.
Service delivery and communication with patients, customers, and providers
Treatment, care, and engagement
Patient data using adaptive privacy management
Costs and operational complexity via intelligent process automation
Patient populations via advanced data visualization
Research and development to fuel innovation
IT infrastructure and protect sensitive patient records
Multiple sources of data to improve clinical trials, drug manufacturing, diagnosis, patient engagement, and regulatory compliance
Critical aspects of supply chain to address disruptions and reduce waste
Improve bookings. Transform experiences. Make it safe.
The disruptions and uncertainties brought forth by the COVID-19 pandemic were felt globally across virtually every industry. Adapting to our new reality remains a central challenge for many organizations. Providers in the hospitality and travel industry are facing dramatic changes.
From restaurants to hotels to airlines, the digital renaissance is already afoot and that includes a revived focus on data management and machine intelligence. Chatbots, intelligent automation, and other AI-powered technologies are being leveraged to optimize processes across multiple areas of operations, boost bookings, personalize the customer experience, build operational resiliency, and create contactless solutions for ordering, check-in, and concierge functions.
Customer experience with virtual assistants and contactless services
Market and consumer behavioral trends
Operational costs using hyperautomation
Engagement across channels
Reservations and bookings via smart search and service pairings
Customer sentiment based on machine learning analysis of internal and external data
Sales using smart recommendations, dynamic pricing, and personalized promotions and offerings
Communication and collaboration for teams and partners
Unplanned maintenance of assets via advanced predictive analytics
On safety for employees and travelers
Preparing the world for speed, scale, and safety
Thanks to the strides made over the recent decades in information technology, every company is or has already become a tech company. Today, virtually every organization is enabled by or highly dependent on software, hardware, IT services, semiconductors, or electronics to operate and deliver products or services. Companies serving the IT sector are no exception. The demand for digital is at all time high and thus the need for AI and automation.
The adoption of machine learning in the IT sector has manifested in several ways. This includes use of advanced analytics to enable better cybersecurity and data privacy, self-healing infrastructure, task and workflow automation, compute optimization, and cost reductions across operations. AI is even helping programmers write better code and improve quality assurance.
Disparate data systems and streams
IT infrastructure and networks with autonomous cyber
Costs across multiple functional areas via intelligent process automation
Advanced monitoring and smart notifications
Server and storage utilization
Productivity with the use of AI-supported coding, communication, and knowledge management systems
Customer experiences with chatbots, virtual assistants, and personalized services
Critical information across multiple languages
Innovation via AI tools that surface hidden insights, designs, and patterns
Propelling our economy and society forward
Our manufacturing future will be defined by two overlapping trends: Making smarter things and smarter ways of making things. Both trends benefit from use of machine learning, IoT, digital twins, and intelligent process automation to bring unprecedented efficiency to manufacturing. Industry 4.0 (the 4th Industrial Revolution) has already begun, giving rise to a number of smart manufacturing and supply chain use cases.
These use cases include a series of supply chain and production optimizations—from supplies to costs, inventory, and logistics—as well as new ways to predict and improve yield, manage energy consumption, minimize unplanned downtime and equipment failure, improve quality control and compliance, and maintain workplace safety.
Uptime with predictive maintenance
Heath and safety risks at the workplace
Fleets of loT sensors and entire machines
Multiple key processes, workflows, and tasks to achieve hyperautomation
Plant performance and other parts of operations with centralized insights
Costs and improve yields with advanced processing of data from multiple sources
Waste and unnecessary energy consumption
Physical facilities and assets with AI-powered surveillance
Against cybersecurity threats
Going digital all the way…and all the time
The COVID-19 pandemic may have moved many of us away from our offices but it has brought us much closer to our digital devices. The global creation of digital content is exploding and our thirst for on-demand knowledge and entertainment seems unquenchable. Add these trends to increasing competitive pressures and fading attention spans among audiences, and you’ll begin to see why this industry is undergoing massive change.
The case for digital and AI transformation in media and entertainment begins with personalization and smart content creation. Today, companies are using machine learning to create more interactive and engaging experiences while leveraging data-driven insights to improve marketing, content distribution, demand forecasting, budgeting, and administrative tasks.
Audience needs and behavior
Content with multisensory AI
Engagement and satisfaction with hyper personalization
Diverse media content; structured, unstructured, and semi-structured data
Demand, behavioral trends, and content performance
AR/VR with advanced AI
Machine-generated content tagging, summarization, and translations
Internal processes and workflows
And monetize intellectual property (IP)
Strategic focus on service quality and speed
For decades, software and computing has been paving the way for productivity in professional services. Today, growing demand for expert services and consulting is compelling providers to introduce AI and automation to their practices as a way of ensuring service reliability, client loyalty, and business continuity.
AI adoption in professional services is growing in response to increasing client demand for better, more cost-efficient services. AI-powered solutions can help dramatically improve workflows, decision-making and forecasting. These solutions also displace mundane, redundant work that could be performed faster and more accurately via smart machines.
Operational efficiency and service delivery
Team morale and productivity
New monetization opportunities with smart solutions
And analyze diverse data from multiple sources
Idle data into valuable insights
Scoring for leads and opportunities
Relationships with clients and reduce attrition
Contract reviews and credit agreements
Transforming customer experiences and business models
The retail landscape’s multi-decade digital evolution is undergoing yet another significant change. The COVID-19 pandemic catalyzed a shift in how consumers engage with retailers with long-term implications. Consumer migration to digital is no longer limited to a narrow group. Flexibility and convenience are now driving the consumer experience more than ever. The future of this industry is expected to be defined by multichannel retail models where sellers offer customers more ways to shop—brick and mortar, social media, online marketplaces, direct-to-consumer e-commerce, and more.
In our new post-pandemic reality, resiliency in retail requires strategic implementation of advanced technologies such as artificial intelligence, IoT, and hyperautomation. So far, a combination of these technologies has enabled contactless checkouts at physical stores, data-driven demand forecasting, hyper personalization in marketing, and intelligent supply chain management.
E-commerce with targeted recommendations
Brand loyalty with behavioral insights
Data streams from sensors and loT
From in-store video streams
Pricing of products using multi-channel data for demand, supply, and seasonal trends
Customer service and communication
Delivery and logistics, inventory levels, costs, and other aspects of supply chain management
Customers advanced search capabilities to boost upselling and cross-selling opportunities
Operations and decision-making with data-driven insights as well as intelligent process automation
Connecting our world in faster and smarter ways
Our society’s reliance on telecommunications cannot be overstated. Today, a large number of wired and wireless telephone operators, Internet service providers, as well as cable and satellite companies manage the highly complex global infrastructure that makes information sharing possible for consumers and businesses alike. To progress, we all rely on fast and cost-effective transmission of data in multiple formats including voice, text, audio, images, videos, and logs.
As we enter humanity’s 10th major s-curve of information exchange, multisensory artificial intelligence and hyperautomation is ushering a new era for interaction between people, machines, and services. Machine intelligence is helping telecommunications operators optimize network traffic, open new revenue channels, enhance security, cut costs, maximize uptime, and enable personalization and higher quality of data transmission.
Peak loads at the grid or tower level
Customer support with virtual agents and AI-powered search capabilities
Sensor data at the edge, centrally, or both
System and service uptime
Processes, workflows, and tasks for and between teams, systems, and partners
Networks and customer data with autonomous cyber
Hyper personalization based on changing data patterns and trends
Resiliency and save costs with AI-enabled diagnostics and predictive maintenance
Rapidly growing fleets of loT sensors and smart machines
Moving from point A to point B with increased speed and efficiency
What does modernization mean for the highly competitive transportation and logistics industry? How do disruptions in markets and technology impact what ultimately links producers to consumers? Today, the world’s complex and interdependent supply chain networks consist of local and global providers that are challenged by fierce competition and new business models. Fast-changing customer expectations are putting pressure on these providers to either evolve and grow or resist change and lose relevance.
Advanced AI and automation are helping companies in the transportation and logistics industry truly accelerate their technological transformation. Providers in this industry are using machine learning, edge computing, hybrid cloud, and IoT to optimize operational efficiency and fleet performance, minimize downtime and delivery delays, improve supply chain management processes, enhance safety, and enrich customer experience.
Maintenance needs and predict equipment failures
Safety with AI-powered monitoring and notifications
Business processes and workflows
Fleet performance with actionable data insights
Performance and asset health
Visibility across supply and value chains
Orders and customer deliveries
Operational and service delivery costs
Communication and collaboration among internal and external teams
Our customers get results
Here are a few examples:
AI-powered analysis of daily workforce activity data across international operationsLearn more
GLOBAL EQUIPMENT MANUFACTURER
Smart search, discovery, and recommendations for a vast technical knowledge baseLearn more
GLOBAL PHARMA CO.
Advanced analysis for complex manufacturing problem reportsLearn More
AI-powered analysis of cryptocurrency activity and market news to forecast prices and manage portfolio riskLearn more
GLOBAL RETAILER & MANUFACTURER
Intelligent product cost & sourcing optimizationLearn more
Automated loan application processing and underwritingLearn more
SEMICONDUCTOR SERVICES CO.
Semiconductor die yield and wafer defect analysisLearn more
MEDIA & ENTERTAINMENT CONGLOMERATE
AI video analysis for search and digital asset managementLearn more
GLOBAL DATA CENTER PROVIDER
AI root cause analysis for interconnection and network reliabilityLearn more