Adani Ports Quitely Deploying India’s First Fully Automated Container Cranes at Its Indian Ports

Adani Ports & Special Economic Zone (APSEZ) has begun deploying fully automated container cranes at Vizhinjam port, Kerala, operated remotely from climate‑controlled cabins, marking a major leap in India’s port automation and sustainability drive.

ABB is the technology partner behind Adani Ports’ automation at Vizhinjam, providing the control systems and automation solutions for quay and yard cranes, enabling India’s first fully automated container terminal. Their systems allow cranes to be operated remotely from climate‑controlled cabins, doubling productivity and enhancing safety.

The announcement about Adani Ports unveiling India’s first fully automated container cranes at Vizhinjam dates back roughly eight months. Even though the news is eight months old, it remains strategically relevant because Vizhinjam becoming India’s first fully automated container terminal is a milestone in South Asia.

ABB supplied the automation technology that allows cranes to be operated remotely from a centralized control room. Operators now work in climate‑controlled cabins using joysticks and screens, eliminating the need to sit in crane cabins 30–50 meters above ground.

Besides, APSEZ has expanded its partnership with Kaleris, a US-based supply chain execution software company best known for its Navis Terminal Operating System (TOS). Through this partnership APSEZ will deploy an AI-augmented, plug-and-play operating platform across a global network of 15 container terminals spanning 9 ports. The port is central to India’s transshipment strategy, reducing reliance on Colombo and Singapore.

Key Highlights of Vizhinjam Port Automation

• Automated cranes: Quay cranes and yard gantry cranes are now remotely operated from air‑conditioned control rooms, eliminating the need for operators to sit in cabins 30–50 meters above ground.
• Climate‑controlled cabins: Operators use joysticks and multiple screens in shared cabins, ensuring comfort, safety, and consistent productivity.
• Community integration: Women from fishing and coastal communities have been trained to operate these advanced cranes, creating new employment opportunities.
• ABB automation systems: ABB provided the technology for quay and yard crane automation, enabling India’s first fully automated container terminal.
• Digital twin monitoring: IoT‑enabled systems collect real‑time operational data, displayed on large 3D video walls for proactive exception handling.

Benefits of Automation

Feature	Impact
Remote crane operation	Eliminates operator fatigue, improves safety
Climate‑controlled cabins	Consistent productivity, collaborative environment
AI & IoT integration	Real‑time monitoring, faster decision‑making
Automated gantry cranes	No human operator required, 24/7 efficiency
Community training	Employment for local women, social inclusion

Strategic Importance

• India’s first deep‑sea trans-shipment hub: Vizhinjam is designed to handle Megamax containerships and reduce reliance on foreign hubs like Colombo and Singapore.
• Capacity growth: Phase 1 capacity is 1 million TEUs, with expansion planned to 7.2 million TEUs.
• Sustainability: APSEZ is embedding low‑carbon operations, afforestation, and renewable energy adoption into its port strategy.

Risks & Challenges

• High capital costs: Automation requires significant upfront investment in AI, IoT, and digital twin systems.
• Skill transition: Continuous training is needed to upskill local communities for advanced tech roles.
• Cybersecurity risks: Increased reliance on digital systems makes ports vulnerable to cyber threats.

Adani Ports and Special Economic Zone (APSEZ) has expanded its partnership with US-based Kaleris, committing up to $100 million to deploy AI-powered automation across 15 container terminals at nine ports, as part of a broader $850 million investment in technology and decarbonisation by 2031.

Key Details of Adani’s AI Port Automation

• Investment scale: Up to $100 million in two phases, part of a larger $850 million technology and decarbonisation plan.
• Partnership with Kaleris: Deployment of the N4 Terminal Operating System (TOS) and AI-augmented optimisation solutions.
• Coverage: Rollout across 15 container terminals spanning nine domestic and international ports.
• Efficiency gains: Up to 20% improvement in RTG crane productivity and 14% improvement in terminal truck productivity.
• Capacity expansion: Unlocking 91 million metric tonnes (MMT) of additional cargo handling capacity by 2030, supporting APSEZ’s goal of 1 billion tonnes per annum throughput.

Strategic Impact

Focus Area	Details
AI-enabled automation	Defines next frontier of competitiveness in ports and logistics
Unified digital backbone	Seamless integration across yard, gate, and vessel workflows
Decarbonisation	Part of $850M plan to modernise and reduce carbon footprint
Global footprint	Expansion includes hubs in India, Australia, Israel, Tanzania, and Colombo
Customer experience	Faster turnaround, improved planning accuracy, superior service

Why It Matters

• Global competitiveness: AI-driven automation positions APSEZ alongside leading global port operators.
• Sustainability: Integration of AI, IoT, and optimisation aligns with decarbonisation goals.
• Economic impact: Boosts India’s logistics efficiency, reducing costs and enhancing trade flows.
• Technology leadership: Demonstrates India’s capability to deploy AI at scale in critical infrastructure.

The ambitious AI automation plan comes with significant hurdles. High upfront costs of $100 million demand strong returns on investment, while increased reliance on digital systems exposes ports to cybersecurity vulnerabilities. Workforce adaptation is another challenge, as employees must transition to AI-driven operations. Finally, scaling automation across diverse ports introduces execution complexity, requiring robust integration and continuous monitoring.

Global Port Automation Leaders 

The world’s leaders in port automation today are concentrated in Asia and Europe, with China’s Qingdao and Shanghai, Singapore, and Rotterdam consistently ranked at the top for fully automated container handling, AI-driven scheduling, and sustainability integration.

Port	Region	Key Automation Features	Global Significance
Port of Qingdao, China	Asia	Fully automated end-to-end terminal, electric AGVs, AI scheduling	Ranked #1 globally; benchmark for large-scale automation
Port of Shanghai, China	Asia	Automated stacking cranes, digital twin systems	Handles world’s largest container throughput
Port of Singapore	Asia	Autonomous vehicles, AI-driven berth allocation, paperless customs	Global hub for smart logistics and sustainability
Port of Rotterdam	Europe	Automated cranes, IoT integration, hydrogen-powered equipment	Europe’s most advanced smart port
Port of Los Angeles, USA	North America	Semi-automated terminals, AI analytics	Leading US port despite labour constraints
Tanger Med, Morocco	Africa	Automated stacking, smart cargo handling	Africa’s largest and most advanced port
Port of Melbourne, Australia	Oceania	Automated yard cranes, smart energy systems	Regional leader in automation and sustainability

What Sets Them Apart

• China’s dominance: Ports like Qingdao and Shanghai lead due to full-scale automation, electrified equipment, and AI-driven scheduling.
• Singapore’s innovation: Known for autonomous vehicles, predictive analytics, and carbon-neutral goals.
• Rotterdam’s sustainability: Europe’s leader in hydrogen-powered equipment and IoT integration.
• North America’s lag: Despite advanced tech, governance and labour constraints slow full automation adoption.

Challenges

Global leaders face high capital costs, cybersecurity vulnerabilities, and workforce adaptation challenges. North American ports, in particular, struggle with labour union resistance, while Asian hubs must balance rapid scaling with sustainability goals.

US Startup Rovex Launches World’s First Autonomous Patient Transport Robot

Florida, United States-based startup Rovex has unveiled Rovi, the world’s first autonomous in-hospital patient transport robot. Designed to attach to existing stretchers, Rovi navigates hospital corridors independently, aiming to reduce delays in patient transfers and improve hospital efficiency. The launch comes amid rapid growth in the global hospital robotics market, projected to reach $4.6 billion by 2030.

Rovi is essentially a patient transport robot that attaches to stretchers, autonomously moving them around healthcare facilities. The systems include a screen that keeps patients informed of where they are going and why.  Rovi will eventually bring similar functionality to hospital beds and wheelchairs.

Rovi: World’s First Autonomous Patient Transport Robot

Rovi [Image - gorovex.com]

• Universal stretcher fit: Rovi attaches to any brand of stretcher, with future compatibility for beds and wheelchairs.
• Autonomous navigation: Equipped with 360° obstacle detection, computer vision, and elevator/door navigation without major infrastructure changes.
• Pre-programmed simulation: Runs millions of virtual transports to learn hospital layouts and workflows.
• Efficiency analytics: Captures logistics data to identify bottlenecks (e.g., imaging backups at peak hours).
• Deployment scale: 9–10 Rovis can handle transport needs for a large hospital.
• Patient experience: Moves at walking speed, greets patients, announces destinations, and keeps them connected to care teams.
• Safety focus: Designed for low-acuity patients, ensuring dignity and comfort.

Market Context: In-Hospital Robots

• Market size: $2.26 billion in 2025 → $2.59 billion in 2026 (CAGR 14.3%). Expected to reach $4.6 billion by 2030 (CAGR 15.5%).
• Drivers: Staff shortages, rising surgical volumes, infection control needs, and demand for automation in logistics and labs.
• Trends: Deployment of robots for non-clinical tasks (transport, delivery, disinfection); integration of AI-driven navigation and telemedicine capabilities; focus on contactless healthcare solutions post-pandemic.
• Challenges: High upfront costs, regulatory hurdles, and training requirements for staff acceptance.

Comparative Positioning

Robot	Primary Role	Strengths	Limitations
Rovi	Patient transport	Universal stretcher fit, autonomous corridor navigation	Limited to low-acuity patients
TUG (Aethon)	Supply delivery	Proven logistics automation, elevator integration	No patient transport
Moxi (Diligent)	Nurse assistant	Fetches supplies, supports staff	Not designed for patient movement

Key Takeaways

• Rovi is unique: Unlike supply-delivery robots, it directly addresses patient transport bottlenecks.
• Hospitals benefit: Faster transfers, improved bed turnover, and reduced staff workload.
• Market timing: Launch aligns with rising demand for automation in hospital logistics, positioning Rovex as a first mover in patient transport robotics.

Founded in 2024, Rovex is emerging as a first-mover in patient transport robotics, combining AI-driven navigation with hospital workflow integration. With strong VC backing and a niche focus, it is well-positioned to scale globally as hospitals increasingly adopt automation to address staffing shortages and efficiency challenges.


Via ~ Interesting Engineering

World’s First Fully Automated Medicine Lab: All Robots No Humans

Japan has unveiled a world-first fully automated medicine laboratory, operating entirely without human researchers. Located at the Institute of Science Tokyo’s Yushima campus, this facility is staffed exclusively by humanoid robots and autonomous machines, marking a radical shift in medical research.

The facility developed by the Institute of Science Tokyo operates with 10 robots, including the humanoid Maholo LabDroid, and no on-site human staff.

Key Highlights

• Location: Yushima campus, Institute of Science Tokyo
• Robots in operation: 10 autonomous machines, including Maholo LabDroid with dual robotic arms
• Functions: Automated cell culture, reagent transfer, temperature-controlled experiments, and repetitive lab tasks
• Expansion goal: 2,000 robots by 2040, aiming to automate the entire medical research pipeline
• No human staff: Operates 24/7 without on-site researchers

Inside the Robot-Run Lab

• Maholo LabDroid: A humanoid robot capable of performing delicate tasks such as stem cell culture and drug testing.
• Other autonomous systems: Handle repetitive lab work with precision, ensuring consistency across experiments.
• Current scale: 10 robots are already in operation.
• Future vision: Expansion to 2,000 robots by 2040, creating a fully autonomous medical research ecosystem.

Maholo LabDroid was among the earliest humanoid robots specifically built for biomedical research. It was first unveiled in 2017 by Japan’s Robotic Biology Institute (RBI), marking the debut of a humanoid laboratory robot designed to automate complex

biological experiments.  

Why It Matters

• 24/7 operation: Robots can run experiments continuously, accelerating discovery.
• Error reduction: Automation minimizes human mistakes in sensitive procedures.
• Drug development speed: Timelines for testing and discovery are compressed significantly.
• AI integration: Plans include combining robotics with AI for hypothesis generation and experimental validation.

Human vs. Robot Labs

Feature	Human-Staffed Labs	Fully Automated Robot Lab
Staffing	Scientists, technicians	10 robots (scaling to 2,000)
Operation Hours	Limited (8–12 hrs/day)	24/7 continuous
Error Risk	Human error possible	Minimized via automation
Scalability	Workforce-dependent	Expandable via robotics
Research Speed	Weeks/months	Compressed timelines

Challenges Ahead

• Ethical oversight: With no humans on site, accountability for results becomes complex.
• Technical reliability: Robots must adapt to unexpected experimental variables.
• Cost barrier: High investment may limit adoption outside elite institutions.
• Human role shift: Researchers may transition into supervisory, AI-integration, and oversight positions.

This lab represents a paradigm shift in medical research, where robots not only assist but fully replace human presence. If successful, it could redefine the future of drug discovery and biomedical innovation worldwide.

Festo Marks 40 Years in India, Announces New GCC, 600 Jobs, and Strategic Investment in Bengaluru

Festo, a global leader in automation technology and technical education, today marked 40 years in India and inaugurated its new Global Capability Centre in Bengaluru, advancing Industry 4.0, automation, and smart manufacturing, while creating capacity for 600 people and driving strategic investment in the region.

The newly inaugurated 71,000 square feet Global Capability Centre near Electronics City, Bengaluru established and marks a strategic step in Festo’s global growth journey. The GCC, home to highly skilled professionals, will serve as a strategic hub for advanced engineering, digital solutions, software development, data analytics, and process excellence, supporting Festo’s operations worldwide.

Furthermore, the new Bengaluru GCC will build on the skills of existing employees supporting global process optimization and innovation.

Celebrating four decades of innovation and growth built on trust, innovation, and shared progress Ravi Sastry, Managing Director remarked “Our GCC in Bengaluru is aligned with Festo’s vision of automation for a sustainable future, the centre will play a significant role to drive global R&D initiatives while fostering collaboration with India’s rich technology and engineering talent pool.”

India has been a key growth market for Festo for four decades. The company remains focused on empowering industries, enabling skills for tomorrow through technical education and shaping the future of automation through innovation, partnership, and long-term impact. Following this milestone, our team in India will grow in 2X. — said Alok Maheshwari, Head of GCC, Festo India.

Reflecting 40 years of growth and achievement on his visit to India, Sebastian Beck, Member of Management Board HR & Finance, Festo, celebrated the launch of Festo GCC, “Forty years of Festo in India is a powerful reflection of our long-term vision and belief in the country’s industrial and technological potential. What began as a market presence has evolved into a strong partnership built on trust, engineering excellence, and shared values. As we look ahead, India will continue to play a strategic role in shaping Festo’s global innovation, digital capabilities, and sustainable growth.”

Festo entered the Indian market in 1963 and established its incorporated presence in 1986. Over the last four decades, Festo India with over 1,000 employees has played a key role in advancing industrial automation, technical education, and Industry 4.0 readiness, working closely with 25,000 customers, institutions, and industry partners to deliver innovative automation solutions and develop future-ready talent.

About Festo

Festo is an independent family-owned company and a global player in automation technology and technical education, with headquarters in Esslingen a.N. (Germany) - with over 20,000 employees at around 250 locations worldwide, a turnover of around 3.5 billion euros and an R&D rate of over 8%. As a partner in motion, Festo offers integrated and seamless pneumatic, electric and digital drive technologies across all industries - including software and AI solutions as well as customized training concepts - for 300,000 customers in over 35 industries in automation and 56,000 education customers worldwide.

Amazon Unveils Blue Jay and Project Eluna to Revolutionize Warehouse Robotics and AI

Amazon has just unveiled two cutting-edge technologies—Blue Jay and Project Eluna—designed to transform its operations network by enhancing safety, efficiency, and decision-making for front-line employees.

Blue Jay: Multi-Arm Robotics System

• Functionality: Coordinates multiple robotic arms in a single station to perform picking, stowing, and consolidating tasks simultaneously.
• Efficiency Boost: Replaces three separate robotic stations with one streamlined unit, handling ~75% of item types stored at Amazon sites.
• Design: Ceiling-mounted system that moves packages at high speeds, already deployed in select fulfillment centers.

Project Eluna: Agentic AI for Smarter Decisions

Project Eluna – An Agentic AI system

• Project Eluna will be piloted at a fulfillment center in Tennessee to assist operators this holiday season, working initially on sortation optimization. Operators can ask questions like, “Where should we shift people to avoid a bottleneck?” and receive clear, data-backed recommendations. The goal: less putting out fires, more foresight.
• Purpose: Supports front-line employees by simplifying complex decisions and optimizing workflows.
• Agentic AI: Goes beyond traditional automation by acting as a collaborative decision-making partner, not just a tool.
• Impact: Helps reduce repetitive tasks, improve safety, and open new career pathways for employees.

Blue Jay and Project Eluna join other new robotics and AI systems we launched this year, including Vulcan, Amazon’s first robot with a sense of touch designed to assist with ergonomically challenging tasks, and DeepFleet, an AI foundation model that coordinates large fleets of mobile robots across facilities.

IBM's HashiCorp Debuts Real-Time Infrastructure Graph and Lifecycle Enhancements for Hybrid Cloud Automation

At HashiConf 2025, HashiCorp marked its 10th global conference—and its first as an IBM company—with a bold vision for the future of infrastructure automation. The company introduced a suite of Infrastructure and Security Lifecycle Management (ILM and SLM) capabilities and previewed Project infragraph, a strategic investment designed to enable agentic infrastructure across hybrid environments.

Project infragraph: A Real-Time Infrastructure Graph for AI-Ready Operations

• Relational visibility across provisioning workflows and production environments
• Tailored insights for platform and infrastructure teams to accelerate decision-making
• Unified context for automation and policy enforcement
• Agentic workflow readiness, enabling AI to reason about infrastructure state and propose remediation or optimization actions

Infrastructure and Security Lifecycle Enhancements

Infrastructure Lifecycle Management (ILM)

• HCP Terraform Stacks (GA): Simplifies multi-component deployments
• Terraform Search & Actions (Beta): Accelerates onboarding and automates Day 2 operations
• MCP Server (Beta): Enables natural language interaction with Terraform registries
• SBOM Storage & Image Provenance: Enhances supply chain security

Security Lifecycle Management (SLM)

• HCP Boundary RDP Credential Injection (Beta): Secures remote access without exposing secrets
• Vault Radar Jira Scanning & IDE Plugin (GA/Beta): Detects secrets earlier in the development cycle
• Vault Dedicated Enhancements: Includes AWS PrivateLink, Azure DNS, and secrets inventory reporting
• Vault MCP Server (Beta): Natural language interface for managing secrets

A Platform for Intelligent Infrastructure

“HashiCorp’s latest product updates and the introduction of Project infragraph signal more than product momentum—they represent the evolution of a platform that can unify infrastructure and security data, and accelerate intelligent decision-making,” said Armon Dadgar, CTO and co-founder of HashiCorp.

IBM’s Dinesh Nirmal added, “Project infragraph is a major step toward infrastructure that can observe, reason, and act. By combining automation with real-time infrastructure intelligence, we are creating the control layer that unlocks the next era of AI-powered operations.”

GenAI Meets SDLC: Tata Elxsi Joins Forces with KAVIA AI to Automate Millions of Lines of Code

Tata Elxsi, a global design and technology services company, today announced a strategic partnership with KAVIA AI, San Francisco based software 3.0 AI-powered platform, redefining software development with enterprise grade AI. Built to handle millions of lines of code and complex backend systems, KAVIA AI automates the entire development lifecycle, from planning and architecture to development, quality assurance, deployment and maintenance.

This collaboration will deploy GenAI-assisted automation across Tata Elxsi’s internal platforms and customer-facing programs, aiming to transform software quality and time-to-market. This joint go-to-market will deliver the power of GenAI for Software Development Lifecycle (SDLC) to enterprises across transportation, media, communications, and healthcare where engineering reliability is paramount.

By combining Tata Elxsi’s deep expertise in domain-led engineering from concept to deployment, with KAVIA AI’s cloud-native Workflow Manager Platform, the partnership will enable intelligent automation across every key phase of the SDLC—from requirement planning and architecture design to code creation, testing and deployment.

Nitin Pai, Chief Strategy Officer at Tata Elxsi, said, “GenAI adoption demands more than tools—it requires a trusted partner to pilot, productise and scale development and deployment workflows. Tata Elxsi brings that trust, backed by 25+ years of proprietary expertise in software engineering across complex, regulated industries, and a deep understanding of deploying GenAI with the appropriate industry-specific guardrails. We deliver not just AI automation, but real outcomes that go beyond just efficiency to effectiveness and the ‘shift left’ paradigm that enterprises need to scale GenAI in mission-critical environments.”

Labeeb Ismail, CEO of KAVIA AI, said, “We’re excited to partner with Tata Elxsi, a company that brings the scale, credibility and delivery discipline needed to realise real-world AI adoption in large-scale delivery environments. Our platform is built to be enterprise-ready, and Tata Elxsi’s proven delivery record ensures this technology delivers real outcomes to customers.”

Early deployments are already underway across multiple programs, including SaaS platforms, middleware, embedded systems and device development. These early outcomes validate the potential of GenAI-powered SDLC automation—accelerating software delivery without compromising on quality or compliance.

NTT DATA Unveils Smart AI Agent™ Ecosystem, Revolutionizing Industry Solutions with Intelligent Automation and Strategic Alliances

NTT DATA, a global leader in digital business and technology services, today announced a comprehensive enterprise-grade Smart AI AgentTM Ecosystem with industry-specific solutions to help clients transform their business. The company also announced a patented plug-in solution that turns legacy bots into autonomous intelligent agents, and an expanded key alliance network for providing best-fit solutions.

"The rapid evolution of AI presents both immense opportunities and challenges for businesses," said Yutaka Sasaki, President and Chief Executive Officer, NTT DATA Group. "At NTT DATA, we have developed the comprehensive capabilities needed to guide our clients through these transformative times and empower them to shape their future with the power of AI."

Assured outcome solutions with embedded Smart AI Agent

NTT DATA has deployed hundreds of Smart AI Agent instances in support of sophisticated processes and decision-making at clients. The company’s roadmap encompasses a continuous stream of new agents to support more complex use cases from a range of industries as well as shared functions. For example:

• Healthcare: Current agents are autonomously classifying, prioritizing and summarizing insurance appeals and making decisions about medical necessity among other responsibilities. The near-term roadmap includes agents that specialize in early interventions, medication compliance, payer validation, and preventing fraud, waste and abuse.
• Automotive manufacturing: Agents already are analyzing regulatory warning letters and citations. The company is now developing agents that specialize in root-cause analysis of defects; initiate corrective actions, recalls or fixes; and launch compliance reviews as needed.
• Finance: Agentic AI solutions are assisting banks, partners and consumers in the continuous pursuit of client and engagement validation requirements, including Know Your Customer and other fraud detection and anti-crime capabilities, minimizing transaction and payment vulnerability.
• Supply chain and logistics: Agents are helping clients select and securely do business with AI startup partners, while also building AI agent prototypes to help businesses deploy and integrate pilots with purchasing workflows and processes, and monitoring adoption, performance and return on investment. Next up are domain-specific steps including agents that intelligently manage procurement services.
• Marketing: In one of many examples, a multi-agent system integrates with a hyperscaler platform to autonomously analyze and categorize user profiles and build psychographic profiles for hyper-personalized ad recommendations. This system continuously learns and adapts, delivering boosted sales and revenue to clients in many industries.

Based on the company’s comprehensive approach to agentic AI, NTT DATA can offer assured outcomes that help clients heighten performance, improve security and cyber resilience, and ignite innovation for profitable growth and superior stakeholder experiences.

“Agentic AI is the next transformative wave that will impact every sector, far more than what we have seen with Generative AI so far,” said Abhijit Dubey, CEO of NTT DATA, Inc. “It’s not just about boosting creativity or productivity. It’s about unlocking new capabilities that can take initiative, make decisions and collaborate with humans in entirely new ways. With our deep expertise in responsible innovation, trailblazing alliances, and visionary clients, we’re excited to lead this future — building the foundation for a reimagined human-machine hybrid workplace and a bold new business landscape.”

Comprehensive Smart AI Agent Ecosystem guides clients through AI adoption

NTT DATA’s Smart AI Agent Ecosystem builds on previous developments to scale the breadth and agility of composable agentic AI solutioning. Key components include:

• Managed agentic services that help clients build, adopt, manage and scale transformative solutions.
• Solutions with embedded Smart AI Agents that offer assured outcomes for clients, including solutions for specific industries and horizontal functions.
• Additional Smart AI Agents targeting industry and horizontal needs.
• Smart AI Agent platform that incorporates integrated tools, utilities, accelerators and best practices; and access to a marketplace with additional agents, large language models (LLMs) and small language models (SLMs).
• AI-ready infrastructure backed by services that leverage public cloud, private cloud, network and cybersecurity.
• Alliances with world-leading technology providers and world-class startups.
• Responsible by design including security, governance and compliance.

The expanded ecosystem empowers clients to envision new ways of operating with smarter automation, resolve global skills shortages and maximize return on investments. Clients also benefit from the assurance of working with a trusted, full-service provider with global scale, scope and expertise.

The Smart AI Agent Ecosystem is complemented by an array of proven NTT DATA services including structured readiness and risk assessments, managed services tailored to hyperscaler AI offerings, and multi-agent management services in hybrid vendor environments. Every aspect of the ecosystem is grounded in the company’s commitment to responsible AI – ensuring it is trustworthy, ethical and secure by design.

“We’ve been leveraging NTT DATA’s end-to-end Agentic AI Services for Hyperscaler AI Technologies to explore both pro-code and low-code agentic AI experiences,” said Pankaj Shah, VP, Chief Information and Digital Officer, Hyster-Yale Materials Handling, Inc. “With their step-by-step advisory approach and outcome-focused strategy, we’re now exploring powerful multi-agent models and identifying new use cases to align with our business objectives and to reimagine how we operate.”

Industry-leading alliances and partnerships offer deep choice

NTT DATA recently announced a strategic collaboration agreement with OpenAI to drive innovation in generative AI. As part of this agreement, NTT DATA will establish an OpenAI CoE (Center of Excellence) to accelerate the development and deployment of new generative AI services powered by the OpenAI APIs. These services will be tailored to specific industries and business functions, and will be introduced globally to deliver enhanced value to clients.

In addition to formal collaborations with world-leading technology providers, NTT DATA also has established alliances with world-class innovative startups including, for example:

• Rafay Systems: Rafay’s platform supports NTT DATA’s delivery of a scalable, secure and developer-friendly Platform-as-a-Service experience on top of AI infrastructure (GPU PaaS), enabling enterprises to streamline GenAI adoption, reduce operational complexity and accelerate the deployment of production-grade AI workloads.
• Kore.ai: The enterprise-grade Kore.ai Agent Platform integrates LLMs to enhance NTT DATA’s Digital Workplace Services. This GenAI-powered automation enables NTT DATA to enhance Service Desk operations, reduce costs and deliver personalized context-aware support to various clients.

Agentic AI services portfolio meets clients where they are with end-to-end ecosystem

The company’s previously announced Agentic AI Services for Hyperscaler AI Technologies offers a comprehensive suite of cloud-managed services to help organizations harness the full potential of agentic AI by leveraging hyperscaler AI technologies.

NTT DATA is rapidly scaling their Agentic AI Services for Hyperscaler AI Technologies to deliver greater value as organizations increasingly mature on agentic AI and adopt multi-AI agent models. For example, leveraging Azure AI Agent Service on Azure AI Foundry, NTT DATA can build, manage and orchestrate multi-agent workflows across multiple platforms. This approach simplifies complex multi-agent deployments.

Additionally, NTT DATA is helping clients work across the agentic AI spectrum by making its tooling available across clients’ cloud platforms. This means that any agent NTT DATA builds can easily be transferred to a clients’ cloud environment across Microsoft Azure, AWS and Google Cloud Platform.

Patented solution transforms bots into autonomous intelligent agents

NTT DATA also announced a patented solution that transforms legacy bots into intelligent agent assets. This plug-in capability is especially important to companies that want to adopt AI but are constrained by technological debt. Millions of Robotic Process Automation (RPA) bots have been deployed by businesses worldwide for rules-based automation. Similar to a plug-in module that turns a basic television into a smart TV, NTT DATA’s new solution can transform bots into intelligent agents that operate autonomously while complying with governance and policies for security and privacy.

“AI is causing a massive shift similar to the early days of the internet — reshaping how we work, solve problems and create value,” Dubey said. “We’re not just watching this future unfold — we’re driving it. At NTT DATA, we’re delivering clients real, measurable impact from AI solutions already, and this patented, transformative plug-in is just one more proof point of what’s possible when innovation meets execution.”

Salesforce's New Revenue Lifecycle Management Allows Businesses to Scale, Automate the Entire Quote-To-Cash Sales Process

Salesforce has recently announced new capabilities for Revenue Lifecycle Management that can significantly enhance the quote-to-cash sales process.

Revenue Lifecycle Management is for direct sales users who require quoting. In addition, it is for users who manage and administer the Revenue Lifecycle Management environment, including building products and defining pricing.

A flexible metadata model allows businesses to deploy the precise product capabilities they need, empowering them to automate processes anywhere they transact, including third-party integrations. Capabilities include Product Catalog Management, Price Management, Transaction Management & CPQ, Contract Lifecycle Management, and Dynamic Revenue Orchestration.

Enhancing Salesforce’s quote-to-cash portfolio, which includes Salesforce CPQ and Salesforce Billing, this full-lifecycle solution offers numerous capabilities, including:

• Unified Platform: Businesses can now scale and automate the entire quote-to-cash process, from quoting and contracting to fulfilling orders, all on a unified platform. This platform integrates sales, finance, and legal teams.
• AI Integration: Salesforce's Einstein AI capabilities play a crucial role in automating processes and guiding quoting decisions throughout the revenue lifecycle. For instance, Contracts AI uses generative AI to recommend the right contract clauses, speeding up contract cycles and improving accuracy.
• Omni-Channel Selling: Through a unified product catalog, businesses can sell via direct sellers, partner channels, or self-service channels (such as storefronts and in-app user flows). Modular features empower seamless buying experiences across any channel and Salesforce application.
• Monetization Flexibility: As products-as-a-service become more common, subscription management functionality automates processes from amendment to renewal, ensuring a smooth experience for both customers and sales teams.

In summary, Salesforce's Revenue Lifecycle Management aims to transform seller experiences and monetization strategies, making them deployable across direct, indirect, and self-service channels.

Amazon's Global Robotic Workforce of 750,000 Robots, Job Losses and How Amazon Addressing It

Amazon recently informed that it employs over 750,000 robots in its operations and, out of these number 400,000 robots were added in the last two years. These robots work collaboratively with employees, handling highly repetitive tasks to improve efficiency, safety, and delivery speed. Amazon's continued investment in robotics technology indicates a significant shift towards automated processes in the company's operations.

Amazon's robots perform a variety of tasks aimed at improving efficiency and safety within their operations which include moving and organizing products within Amazon's fulfillment centers, picking and packing items to fulfill customer orders, sorting packages for delivery, and to transport oversized and unwieldy items through the fulfillment center, navigating around obstacles and working alongside human associate.

Amazon has been at the forefront of incorporating robotics into its operations, and here's a brief overview of the latest advancements:

An image of the new robotic solution —Sequoia — that will support workplace safety and help Amazon deliver to customers faster

Sequoia and Digit: These are new robotic solutions introduced to assist employees and expedite deliveries. Sequoia is designed to improve inventory management, allowing Amazon to store and process inventory up to 75% faster.

An image of the bi-pedal robot — Digit — working alongside an Amazon employee

An image of Amazon's new Titan robot. It's blue, plate-like robot with black details, including a camera on the front, a name plate that says "T333333" and a large, circular plate on top.

Titan: A new mobile robot capable of lifting up to 2,500 pounds, Titan is used for moving heavy and bulky items within fulfillment centers, enhancing safety and operational efficiency.

Proteus: Amazon's first autonomous mobile robot, which can navigate through facilities using advanced safety, perception, and navigation technology.

These robots are part of Amazon's ongoing efforts to improve workplace safety and efficiency while also ensuring faster delivery for customers.

Job Displacement Due to Robots & Automation

Regarding job displacement, Amazon recently announced the elimination of over 18,000 jobs, which is the largest layoff in the company's history. These layoffs mostly affected administrative roles and are part of a broader trend of job cuts across the tech industry. While Amazon maintains that its investment in robotics and automation has not impacted its human workforce negatively, and claims to have increased both hourly pay and the number of people working for the company in addition to the robots, there are concerns about the long-term implications of automation on employment.

An analysis suggests that despite Amazon's growth and hiring numbers, the overall retail job losses that it helped cause will still result in a net decline of 24,000 jobs at Amazon and related retail companies. This reflects the complex relationship between automation, job creation, and job displacement, highlighting the need for strategies to manage the transition for workers whose jobs are at risk due to automation.

How Amazon is addressing the impact of automation on its workforce?

Amazon's "Hands off the Wheel" program aims to automate repetitive jobs and reassign employees to more creative roles where they can add more value. This approach helps retain workers and move them into new roles, allowing the company to be more nimble and find new ways to stay ahead of competitors.

Amazon has partnered with the Massachusetts Institute of Technology (MIT) to study the impact of automation on work. This partnership supports MIT's automation clinic and involves research to understand how employees and organizations are affected by emerging technologies like robots and Al.

In addition, Amazon is also teaming up with polling firm Ipsos to study public sentiment around the impact of robotics and Al in industrial settings. This research will inform both MIT and Amazon as they develop collaborative technologies that support employees.

IBM Acquiring HashiCorp for $6.4 Bn in An All-Cash Deal

IBM has announced its intention to acquire HashiCorp Inc., a leading multi-cloud infrastructure automation company. The acquisition is valued at $6.4 billion and will be an all-cash deal. Under the terms of the agreement, IBM will acquire HashiCorp for $35 per share in cash, representing the enterprise value.

HashiCorp's suite of products provides extensive Infrastructure Lifecycle Management and Security Lifecycle Management capabilities, enabling organizations to automate their hybrid and multi-cloud environments. This move aligns with IBM's focus on hybrid cloud and AI, which are considered the most transformational technologies for clients today. The transaction is expected to close by the end of 2024.

HashiCorp boasts a roster of more than 4,400 clients, including Bloomberg, Comcast, Deutsche Bank, GitHub, J.P Morgan Chase, Starbucks and Vodafone. HashiCorp's offerings have widescale adoption in the developer community and are used by 85% of the Fortune 500.

HashiCorp's suite of products provides enterprises with extensive Infrastructure Lifecycle Management and Security Lifecycle Management capabilities. These tools enable organizations to automate their hybrid and multi-cloud environments.

HashiCorp's Terraform is the industry standard for infrastructure provisioning in these environments.

The acquisition of HashiCorp by IBM creates a comprehensive end-to-end hybrid cloud platform built for AI-driven complexity. The combination of each company's portfolio and talent will deliver clients extensive application, infrastructure and security lifecycle management capabilities.

Post acquisition, HashiCorp is expected to drive significant synergies for IBM, including across multiple strategic growth areas like Red Hat, watsonx, data security, IT automation and Consulting. For example, the powerful combination of Red Hat's Ansible Automation Platform's configuration management and Terraform's automation will simplify provisioning and configuration of applications across hybrid cloud environments.

The two companies also anticipate an acceleration of HashiCorp's growth initiatives by leveraging IBM's world-class go-to-market strategy, scale, and reach, operating in more than 175 countries across the globe.

The acquisition will create the opportunity to deliver more comprehensive hybrid and multi-cloud offerings to enterprise clients. HashiCorp's offerings, combined with IBM and Red Hat, will give clients a platform to automate the deployment and orchestration of workloads across evolving infrastructure including hyperscale cloud service providers, private clouds and on-prem environments. This will enhance IBM's ability to address the total cloud opportunity, which according to IDC had a TAM of $1.1 trillion in 2023, with a compound annual growth rate in the high teens through 2027.

Robotization Can Lead to Decline of Work Meaningfulness and Autonomy

The impact of robotization on work meaningfulness is a topic of current research and debate. A recent study has found that increasing robotization in the workplace correlates with a decrease in perceived work meaningfulness and autonomy.

Specifically, the study suggests that doubling robotization could lead to a 0.9% decrease in work meaningfulness and a 1% decrease in autonomy. If the robotization intensity of certain industries were to align with the leading industry's level, it could result in a 6.8% reduction in work meaningfulness and a 7.5% decrease in autonomy.

This reflects a significant concern, as meaningful work is closely linked to job satisfaction and worker well-being. The introduction of robots can affect various aspects of meaningful work, such as pursuing a purpose, social relationships, exercising skills and self-development, self-esteem and recognition, and autonomy. While there are potential negative impacts, it's also possible for robotization to enhance the meaningfulness of work by relieving workers from repetitive and physically demanding tasks, thereby allowing them to engage in more complex and fulfilling roles.

It's a complex issue with both challenges and opportunities, and the ethical implications of how robots are implemented in workplaces are crucial to consider.

The research paper released is the first to examine the impact of robotization on work meaningfulness, autonomy, competence, and relatedness, which are essential to motivation and well-being at work. Using surveys of workers and robotization data for 14 industries in 20 European countries spanning 2005–2021.

The statement that robotization can lead to a decline in work meaningfulness is a concern that has been raised in the context of increasing automation. The introduction of robots in the workplace can indeed change the nature of work, potentially reducing the opportunities for employees to engage in tasks that they find meaningful.

When robots take over routine, repetitive tasks, it can lead to a reduction in autonomy and a sense of accomplishment for workers, as they may have fewer opportunities to use their skills and creativity. This can affect their perception of the value and significance of their work, leading to a decline in work meaningfulness.

However, it's also important to consider that robotization can have positive effects on work meaningfulness when implemented thoughtfully. By automating mundane tasks, robots can free up human workers to focus on more complex, engaging, and fulfilling aspects of their jobs. This can enhance their sense of purpose and contribution, potentially increasing the meaningfulness of work.

The key is to find a balance where robotization supports human workers, allowing them to grow and find satisfaction in their roles, rather than replacing or diminishing the human aspect of work. It's a nuanced topic that requires careful consideration of the social, psychological, and economic impacts of automation on the workforce.

Zendesk Acquiring Ultimate, An AI-powered Customer Support Automation Platform

Late last week, Zendesk announced that it will acquire Ultimate, a customer support automation platform that uses AI, to provide a more complete AI offering for customer experience (CX). The acquisition is expected to close this month after the customary closing conditions are met.

The acquisition will allow companies to offer customer support using fully autonomous AI agents, workflow automation, or human touch. With this acquisition, Zendesk will be able to provide AI agents that can help resolve customer issues with personalization, speed, and dynamic responsiveness. This acquisition will also allow human agents to focus on building relationships, resolving complex challenges, and applying innovation and creativity to move businesses forward.

The acquisition builds on the launch of Zendesk AI, which was the company's fastest-adopted product in history.
"AI is the future of CX and the next generation of AI agents are not just a tool, but a necessary and fundamental shift in how businesses will engage with their customers,” said Tom Eggemeier, CEO of Zendesk. “With Ultimate, we will help our customers set a new standard, with AI agents giving customers the support they need quickly and effortlessly. This means human agents can focus on what they do best: building relationships, resolving complex challenges, and applying innovation and creativity to move businesses forward.”

“Our mission has always been to help businesses use AI to deliver joyful support experiences. We’ve seen 99 percent of CX organizations who adopt AI shift permanently to a hybrid human and AI agent approach,” said Reetu Kainulainen, CEO and co-founder of Ultimate. “As part of Zendesk, we now have the scale to drive this transformation for every business.”

Ultimate’s AI agents automate up to 80 percent of support requests. They leverage any knowledge source and offer full customization to resolve even the most sophisticated use cases. Its automation platform integrates with any backend system and provides robust analytics and reporting. Together, Zendesk and Ultimate will offer companies the flexibility and control to deliver customer support their way – be it fully autonomous AI agents, workflow automation or human touch.

“In the era of AI, the challenge of delivering exceptional customer service has never been more demanding. It’s not just about streamlining operations or leveraging new technology; it’s about redefining excellence in customer service,” said Kelsey Hales, senior Zendesk lead at Taskrabbit. “With Zendesk and Ultimate, we will not only meet but exceed our customers’ expectations, all while keeping an eye on efficiency and cost-effectiveness.”

“Traditional chatbots are great in meeting basic CX needs. AI agents can be smarter, more reliable and provide precision support,” said Daniel Newman, CEO of The Futurum Group. “With Ultimate, Zendesk is well positioned to offer AI agents that can tackle sophisticated and complex service use cases, helping resolve customer issues with personalization, speed and dynamic responsiveness.”

This acquisition builds on the launch of Zendesk AI, the fastest-adopted product in the company’s history. With Zendesk AI, Ultimate and the company’s AI-powered Workforce Engagement Management solutions, Zendesk offers the only complete CX platform that elevates customer experiences, manages service quality and accelerates business growth.

PwC India and Workiva Announce Strategic Alliance to Help Indian Enterprises for Automating Risk and Compliance Functions

PwC India today announced a strategic partnership with Workiva (NYSE:WK), a leading cloud platform for assured integrated reporting to meet increasing demands in India for accurate and transparent disclosures and Governance, Risk and Compliance (GRC).

Enhancing customer experience is at the heart of this alliance. Combining PwC India’s subject matter knowledge and experience in reporting as well as GRC with Workiva’s fit-for-purpose solution, can help Indian enterprises enhance stakeholder confidence through greater consistency, accuracy, timeliness and ownership over their reports and operations covering financials, ESG, audit, risk, controls, policy and other local regulatory compliances. This will be achieved by connecting people, processes, and data within Workiva’s unified SaaS platform for reduced risk, increased control, enhanced collaboration, and ultimately giving time back to the teams for more rewarding work.

Sivarama Krishnan, Partner & Leader - Risk Consulting, PwC India said, “A strong GRC strategy can be a strategic asset that drives business performance. By embedding management mechanisms that proactively identify, measure, prioritise and manage risk, leaders can gain valuable insights they need to make informed decisions. Workiva’s technology solutions will complement our full range of integrated control, compliance and certification capabilities across all sectors.”

Erik Saito, SVP & General Manager, EMEA & APAC of Workiva said, "Our strong partnership with PwC goes a long way. Our expanded alliance with PwC India brings great synergy into the India market as we help organisations navigate reporting challenges and implement best practices for an optimised and sustainable result. Technology can help financial reporting, ESG and GRC teams work together more efficiently to produce assured integrated reports on the timelines that stakeholders are demanding. Rather than choosing software that addresses only financial reporting, ESG or GRC, Workiva is a platform that all three teams can use. Through PwC India, we bring this integrated ecosystem to life."

Speaking on the partnership, Vivek Belgavi, Partner & Leader - Alliances & Ecosystems, PwC India said, “Workiva is a great addition to PwC India’s expanding alliance ecosystem to help empower businesses in their decision making process by delivering complete control over data across outputs with a visibility into the entire GRC process, from early risk identification to final reports.”

About Workiva

Workiva Inc. (NYSE:WK) is on a mission to power transparent reporting for a better world. We build and deliver the world’s leading cloud platform for assured integrated reporting to meet stakeholder demands for action, transparency, and disclosure of financial and non-financial data. Workiva offers the only unified SaaS platform that brings customers’ financial reporting, Environmental, Social, and Governance (ESG), and Governance, Risk, and Compliance (GRC) together in a controlled, secure, audit-ready platform. Our platform simplifies the most complex reporting and disclosure challenges by streamlining processes, connecting data and teams, and ensuring consistency. Learn more at https://www.workiva.com.

IIT Graduates Founded Gushwork.ai Gets $2 Mn in Pre-Seed Funding Led By Lightspeed

On-demand AI-augmented remote workforce platform, Gushwork.ai, has raised $2.1 million in pre-seed funding round led by Lightspeed Ventures, announced the company on its official blog post.

Other investors who also participated in the round include B Capital, Sparrow Capital, Seaborne Capital and Beenext.

The New York-based startup plans to utilize the freshly raised funds to drive its next phase of growth and build out new product features while keeping the core team lean & agile.

Founded this year, by IIT graduates — Nayrhit Bhattacharya (IIT Kharagpur) and Adithya Venkatesh (IIT Bombay) —Gushwork.ai is an AI-powered global platform designed for enterprises to outsource highly complex operational workflows.

The startup is building a curated marketplace of an AI-trained human task force which can execute complex business processes seamlessly. This allows businesses to focus on strategic tasks while entrusting routine operations to Gush.

Gushwork.ai’s offering is to provide businesses with a reliable solution to delegate critical operational tasks by bringing the best of humans and AI together.

“Our vision is to make it extremely easy for any business to reliably delegate critical yet process-oriented business tasks. Getting expensive in-house employees to work on recurring, manual tasks or spending months trying to imperfectly automate these processes is really suboptimal. The complexity of these tasks is such that most companies do not trust AI to execute them without human oversight. We want to embed AI in the very core of business operations by bringing in a reliable human touch on top of AI to solve the lack of trust,” said Nayrhit Bhattacharya, Co-founder & CEO of Gushwork.ai.

Initially, Gushwork.ai is primarily focusing on sales and marketing operations workflows, encompassing tasks such as lead prospecting, email marketing, ad management, lead engagement on social media platforms, webinar moderation & marketing, social media management for SMBs, responding to inbound leads, CRM setup, social media analytics data scraping, prospect outreach, and ad campaign management, among others. The company plans to expand into more specialized roles in future.

Infosys Inks $2 Bn Deal with Existing Client for AI and Automotion Development

Indian IT giant, Infosys, said that it has signed a deal with an undisclosed existing client to provide artificial intelligence (AI) and automation development services. 

In an exchange filing, Infosys said that it has entered into framework agreement with one of its existing strategic clients to provide AI and automation led development, modernization and maintenance services. The total client target spend over 5 years is estimated at USD 2 Billion.

The announcement comes days before Infosys is set to report its first-quarter earnings. Infosys did not share details on the client or the agreement.

In last few months, Infosys has also signed other major deals such as — British oil & gas company BP's deal worth $1.5 billion and a $454 million deal with Danske Bank.

Infosys, which is India's second-largest software services exporter, has its flagship product "Infosys Topaz" - An AI-first offering to accelerate business value for global enterprises using generative AI, which was launched in May this year.

Infosys will announce results for the first quarter ended June 30, 2023 on Thursday, July 20, 2023 around 3.45 p.m (IST).

HyperAutomation Co. Zvolv Launches Generative-AI Orchestration Engine Z-wall for Building Intelligent Apps Faster

• Z-wall enables building intelligent AI Apps faster, with enterprise grade security and compliance
• Announces the release of the 3.0 version of its Low-Code No-Code Platform with several new Hyperautomation Microservices

The Z-wall AI Orchestration engine expands Zvolv’s already extensive hyper automation microservices functionality, enabling enterprises to build a new breed of AI apps that go beyond traditional web and mobile applications by leveraging generative AI capabilities. They drive higher intelligence, massive efficiency gains, and faster time to value with underlying low-code/no-code and AI-assist builder capabilities.

Zvolv, a leading global enterprise hyperautomation company has announced new generative AI capabilities along with the launch of the 3.0 version of its micro-services Low-Code No-Code (LCNC) platform. The new middleware – Z-wall - expands Zvolv’s already extensive enterprise automation and app-building functionality with built-in capabilities that enable leveraging the power of generative AI in next generation enterprise AI apps.

The unveiling of these new Zvolv capabilities was done at Zvolv’s annual CXO meet held this month at the glitzy JIO world convention centre in Mumbai, attended by 50+ CIOs and CEOs from leading enterprises across industry verticals like retail, aviation and logistics, and several of the Zvolv ecosystem partners.

Enterprises today are rushing to adopt generative AI in every possible area, whether to increase productivity, enhance decision-making powered by data-driven insights, or to improve customer and employee experience. However, privacy and scalability concerns hinder organizations from fully embracing AI into their applications. The risk of sensitive data leak is high, the time and cost it takes for deploying private GPT models with adequate controls on usage, reliability and compliance is significant. With rapid evolution of generative AI technology coupled with a scarcity of developer resources, platform approaches to developing new AI applications give fast Time to Market (TTM), low Total Cost of Ownership (TCO) and eliminate risk.

Zvolv’s hyperautomation microservices platform combined with the Z-wall AI orchestration engine will empower businesses to rapidly deploy the world’s best AI and automation capabilities in their products and services, enabling its customers to realize the promise of generative AI in a secure, trusted way.

“The age of web/mobile apps is now evolving into an age of AI apps, which will dominate the vast majority of the 500M+ enterprise applications to be developed in the next 3-4 years. From a point and click based DIY (Do it Yourself) capabilities of today’s apps, we will see a lot more conversation based GID (Get it Done) capabilities in future AI apps. Today’s new workforce is already getting accustomed to leveraging generative AI in many aspects of their life outside work, and the same level of intelligence and experience will be expected from workplace applications. By leveraging a combination of generic and fine-tuned intelligence in LLM (Large Language Model) models, AI apps will be inherently smarter, more efficient with advanced automation and above all offer a human-like conversational user experience.” said Hardik Gandhi, Chief Executive Officer, Zvolv.

The integration of generative AI in the Zvolv microservices platform will enable enterprises to build AI apps in hours with little to no developer dependence, driving an overall enterprise AI strategy with privacy, security and ethics at the core of the transformation.

• Integrate new human-like conversational and logical reasoning capabilities into the application interfaces, beyond traditional graphical interfaces
• Enable business users to converse with their data, to get faster and more contextual access to organizational knowledge and deeper AI driven insights
• AI-assisted app-building journeys with citizen developers being able to develop more intelligent and deeper automation compared to traditional LCNC builders

“We are averaging 100 hours to build a traditional enterprise app today, with business technologists driving 60-80% of the build process with basic training from the Zvolv Academy. The integration of generative AI into our LCNC builders drives an assisted build journey, which will now enable citizen developers to build end to end, and integrate more advanced AI driven automation into their applications, in under 10-20 hours,” said Sujoy Chakravarty, Chief Operations Officer, Zvolv.

The newly announced Z-wall AI orchestration engine is an integral component to enable the Enterprise AI future, not only isolating the enterprise’s private data from public LLM models, but also governing the usage of generative AI in the variety of new enterprise AI apps.

• Acts as a conduit between the enterprise systems of records and engagements, accessed via the Zvolv microservices layer, and a variety of supported LLM models, private or public, governing access, ethics and optimizing cost.
• Maps the enterprise people, data and process knowledge, enables embeddings, chunking, summarization, semantic search, masking, logging and other necessary data operations to enable effective generative AI usage
• Will improve user experience multifold by reducing app fatigue amongst end users by combining a multitude of AI and traditional apps into a unified enterprise-AI ‘Super App’ that orchestrates information and actions across the enterprise

Sri Srinivasan, Chief Revenue Officer, Zvolv, said, “This new world of Generative AI apps will enable organizations to become leaner and more efficient, while adapting to changes much faster. Re-training an AI app to adapt to a newer process will be much faster and less error prone compared to re-training or re-skilling human resources. While employees focus on more strategic activities, they can get a lot of their more tactical work done with the help of AI. The rate at which technology is changing has changed significantly, and depending on us humans to do it all ourselves is no longer viable.”

Leaders across industry verticals who were given early access to Zvolv’s new capabilities were unanimous in espousing the benefits they see with new generative AI integrations, while drawing comfort that Z-wall enables them to drive responsible AI innovation in their enterprises. “The future of Generative AI would drive business transformation across every function, from retail expansion to provide better insights and planning, to procurement for better managing on-boarding, evaluation and contract automation, to HR and finance to improve employee and partner engagement experience, to logistics for automating tracking and proactively identifying and reacting to bottlenecks,” said Varun Juneja, Assistant Vice President at Lenskart, a multinational optical eyewear retail chain with more than 2,000 stores, who is driving initiatives with early access to this new Zvolv functionality.

The explosive popularity of generative AI has created a watershed moment for Industry leaders who are rapidly looking to leverage hyperautomation and AI to drive productivity across every business function. The market for hyperautomation as an enabler for the enterprise AI vision is expected to reach $50 billion by 2025 and Zvolv is a key industry leader with many Fortune-10 and several Fortune-500 companies already driving transformative change using its platform. Generative AI will usher in a new era of innovation and agility, enabling customers to accelerate growth, improve satisfaction, and drive innovation using Zvolv’s unified hyperautomation microservices and AI orchestration platform.

Zvolv’s (https://www.zvolv.com/) unified LCNC platform combines AI orchestration and hyperautomation microservices to enable organizations to build AI-apps in a matter of weeks. Zvolv no-code platform enables not only building AI apps with no developers involved, it also helps drive an overall enterprise AI strategy with privacy, security and ethics at the core of the transformation. Zvolv is increasing its presence and operations across geographies of India, US, Europe, Africa, Middle East, Australia and Asia Pacific

Yellow.ai Launches Dynamic Automation Platform (DAP) with Generative AI, Unveils New Logo

The rebranding underscores Yellow.ai’s vision of delivering autonomous, human-like experiences for customers and employees, powered by generative AI, to accelerate enterprise growth.

Yellow.ai, a global leader in Conversational AI, today announced the launch of its Dynamic Automation Platform (DAP), powered by generative AI, that enables enterprises to automate customer and employee experiences at scale with 60% reduction in their operational costs. The company also revealed a new logo as part of a rebranding strategy that reflects its vision of delivering human-like conversational experiences to accelerate enterprise growth.

With a 4X growth rate in North America and an established market presence in the Asia-Pacific and Middle East markets, Yellow.ai has emerged as an industry leader since its inception in 2016. The rebranding marks a crucial milestone in the company’s growth journey and reinforces its commitment to using technology, such as generative AI, to fuel innovative solutions for enterprises across its Conversational Service Cloud, Conversational Commerce Cloud, and Conversational EX Cloud product suites.

Talking about generative AI integration, Raghu Ravinutala, Co-founder and CEO, Yellow.ai said, “At Yellow.ai, we strongly believe in the potential of generative AI to enhance our capabilities, foster innovation, and drive business growth. We are investing heavily in domain-specific LLMs to facilitate dynamic content creation, providing our customers with a comprehensive experience through our enterprise-grade Dynamic AI agents. Our customer-centric approach and our strong focus on generative AI are reflected in our rebranding efforts, as we remain committed to delivering the best next-generation Conversational AI solutions.”

The company is combining generative AI technology with DAP which runs on its proprietary and multi-Large Language Model (LLM) AI engine, DynamicNLP™. With 100+ integrations, 150+ pre-built marketplace templates, and the recently launched Dynamic Conversation Designer, businesses leveraging DAP for Yellow.ai’s suite of solutions can go live with their deployments 2X faster.

Jaya Kishore Reddy, Co-founder and CTO, Yellow.ai, said, “By leveraging a multi-LLM architecture, our DAP provides human agents with generative AI-powered assistance while also enabling brands to not just engage with customers but also achieve goal-oriented outcomes and increase conversion rates. Our robust generative AI roadmap underscores our dedication to remaining at the forefront of conversational workflow automation, delivering exceptional human-like experiences anytime, anywhere.”

Symbolizing interactions across 35+ chat and voice channels, Yellow.ai's new logo includes a conversation icon that embodies its proficiency in delivering moments of trust in 135+ languages. As part of its rebranding, Yellow.ai has also revamped its website with a minimalist yellow and purple design and user-friendly interface to cater to a global audience. The purple tones convey a modern, enterprise-focused look, while the warm yellow represents the company's dedication to delivering happiness to its customers and employees.

Yellow.ai Logo

Commenting on the rebrand, Surbhi Agarwal, SVP, Global Marketing, Yellow.ai said, “I am immensely proud of Yellow.ai's rebranding, which showcases our unwavering focus on continuous innovation. Our new logo spotlights our dynamic approach and integration of generative AI in our offerings, with the introduction of two new enterprise-grade CX solutions: the Conversational Service Cloud and the Conversational Commerce Cloud. Our rebranded identity is a testament to our evolution over the past seven years, demonstrating our expertise in managing billions of enterprise conversations.”

DAP’s generative AI-powered features include

1. Generative AI-powered Dynamic Chat: Enabling goal-driven conversations, Dynamic Chat, integrated with Yellow.ai Dynamic Conversation Designer and Engage is able to generate conversation flows on the fly.
• Enterprises can create a lead generation goal for website visitors and configure mandatory and optional inputs (e.g., keeping the phone number and email mandatory and the name and size of the company optional).
• Dynamic Chat is capable of generating a conversation in real time using these inputs, generating the lead, and storing it in the CRM.
2. Generative AI-powered Inbox: Yellow.ai’s omni-channel customer support help desk, Inbox, now empowers support agents with generative AI-enabled
• Ticket summarizations without the customer having to explain the issue multiple times
• Response and tone suggestions that best suit the context of the customer's query
• Multilingual agent interface translating queries into the agent’s preferred languages in real time
• Coaching insights and recommendations on agent conversations for increased productivity
3. Dynamic Workflow Generator: Enables auto-generation of workflows for both marketing and customer support use cases.
• Marketers can define more nuanced goals, such as promoting special discounts on products, to create a dynamic campaign strategy that leads to successful conversions.
• Dynamically create workflows to resolve customer issues without depending on if-else loops. It increases the scope and speed at which queries can be resolved.
4. AI Content Engine for Marketers: Delivering increased efficiency and results through the most engaging messaging templates powered by genderative AI
• Template Generator enables auto generation of contextual templates based on campaign goal and user segment.
• Template Tone Configurator assists in getting templates as per the tone, which aligns with the brand’s image.

Don't miss out on our new website! Visit now to learn how Yellow.ai can accelerate your enterprise growth.

About Yellow.ai

Headquartered in San Mateo, Yellow.ai is a global leader in Conversational AI, delivering autonomous, human-like experiences for customers and employees to accelerate enterprise growth. We believe that memorable conversations are at the heart of every meaningful brand engagement. Over 1100 enterprises, including Sony, Domino's, Hyundai, Sephora, Waste Connections, Ferrellgas, and Randstad, trust our generative AI-powered, no-code Dynamic Automation Platform (DAP).

DAP’s proprietary multi-LLM AI engine, DynamicNLP™, empowers us to handle 2Bn conversations every quarter across 35+ channels in 135+ languages. We're passionate about delivering conversational experiences via our Dynamic AI agents that help enterprises achieve higher customer satisfaction and employee engagement. We were recently recognized as a Challenger in the 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms and have raised more than $102M from blue-chip investors with offices across six countries.