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AI agent for customer service: Key capabilities, use cases, benefits and implementation

AI agent in customer service
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What is Chainlink VRF

Do you know that 65% of customers switch companies because of a bad customer experience? The cost of such bad experiences is staggering, amounting to $3.7 trillion of global 2024 sales.

Businesses allocate a significant part of their total revenue towards customer service, yet often need help to deliver a flawless customer experience. This discrepancy arises from the vast gap between customer expectations and businesses’ support services.

The emergence of AI agents in customer service offers a transformative solution. These AI-powered entities are more than just automated responders; they are sophisticated digital assistants equipped with advanced natural language processing and machine learning capabilities.

AI agents in customer service transform the traditional support model by offering personalized, round-the-clock assistance to customers. By analyzing vast amounts of data in real-time, these agents can swiftly resolve inquiries, provide accurate information, and even anticipate customer needs before they arise.

Moreover, AI agents excel at automating routine tasks, freeing human agents to focus on more complex issues that require empathy and creativity. By streamlining processes and reducing response times, AI agents enhance the overall customer experience and drive operational efficiency and business cost savings.

AI agents represent the future of customer service, where technology seamlessly augments human capabilities to deliver unparalleled service and satisfaction levels. Embracing these innovative solutions is not just about staying ahead of the curve; it’s about meeting the evolving demands of today’s discerning customers and securing a competitive edge in the market.

What is an AI agent?

An AI agent is a highly efficient, intelligent virtual assistant that autonomously performs tasks. It is designed to perceive its environment, interpret data, make informed decisions, and execute actions to achieve predefined objectives.

AI agents enhance efficiency by automating routine tasks and analyzing complex data, enabling human employees to focus on strategic and creative endeavors. These agents complement human efforts rather than replacing them, fostering a more productive and effective workforce.

Characterized by their proactivity and decision-making capabilities, AI agents actively engage with their environment, making choices and acting to fulfill their goals.

A critical aspect of AI agents is their capacity for learning and adaptation. By integrating technologies such as Large Language Models (LLMs), they continuously improve their performance based on interactions, evolving into more sophisticated and intelligent assistants.

In autonomous AI agents, multiple agents collaborate, each assuming specialized roles akin to a professional team. This collaborative approach allows for a more comprehensive and efficient problem-solving process, as each agent contributes expertise to achieve a common objective.

Understanding AI agents in customer service

AI agents enhance customer service by understanding inquiries, analyzing data, and generating accurate responses. They also provide continuous support, manage high volumes of requests, escalate complex issues, collect feedback, and optimize resources. This systematic approach leads to more efficient and effective customer service operations.

AI customer service agents are equipped to handle various tasks, from simple inquiries to complex problem-solving. The core functions of AI customer service agents include:

Environmental perception: AI customer service agents continuously monitor their environment, detecting and analyzing real-time changes to respond promptly to new data and customer inputs.

Decision-making: AI agents in customer service make informed decisions based on data-driven insights, ensuring their actions align with customer service objectives and provide the best possible responses.

Adaptive learning: These agents refine their strategies from past interactions and outcomes. This continuous learning process enhances their efficiency and effectiveness with each customer interaction.

Problem resolution: AI customer service agents identify and resolve customer issues. They often anticipate problems before they escalate and provide quick, accurate solutions to emerging challenges.

Strategic planning: AI customer service agents can forecast trends and plan accordingly, contributing to long-term customer service strategies and resource allocation, improving overall service quality and customer satisfaction.

Key components of AI agents in customer service

An AI agent relies on several key components to operate effectively in a customer service environment. These elements are crucial for developing intelligent agents capable of performing tasks autonomously, enhancing customer satisfaction and operational efficiency. These components include:

  1. Large Language Model (LLM): LLMs serve as the cognitive core of an AI agent in customer service, akin to a computer’s operating system tailored specifically for language processing. Leveraging advancements in machine learning and natural language processing, these models possess extensive knowledge across various subjects and exceptional contextual understanding, essential for effective customer interactions.
  2. The execution/task creation agent/proxy agent:It is a key component of an AI agent. It functions much like a computer’s Central Processing Unit (CPU), determining the necessary tasks and their sequence within the AI agent. It orchestrates the LLM, integrates it with long-term memory, and coordinates with external tools. This orchestration enables the AI agent to deliver optimal customer service experiences.
  3. Memory: An AI agent’s memory stores relevant data, akin to a mix of a computer’s RAM and hard drive, enabling the agent to recall and utilize information later. Modern vector databases like Pinecone or Chroma help the AI agent remember the context of tasks and customer interactions.
  4. Additional tools: Just as a computer benefits from various peripherals and accessories, AI agents in customer service leverage additional tools to enhance their functionality. These tools enable agents to access the internet, retrieve specialized knowledge, or collaborate with other AI models tailored for specific tasks, enriching the customer service experience.

By effectively integrating these components, an AI customer service agent can autonomously perform tasks, respond to customer inquiries, and continuously improve its performance, ultimately leading to higher customer satisfaction and operational efficiency.

Elevate Customer Service with AI Agents

Leverage our expertise to deploy AI agents that improve customer service
efficiency and satisfaction.

Types of AI agents in customer service

Various AI agents can be employed in customer service, with some common types listed below:

Types of AI agents in customer service

Virtual Customer Assistants (VCAs)

Virtual Customer Assistants are more advanced AI agents that can handle complex customer service tasks. They integrate multiple capabilities, including chat, voice, sentiment analysis, and predictive analytics, to provide comprehensive support. VCAs can assist with a wide range of queries, automate routine tasks, and offer personalized recommendations.

Automated Follow-Up Agents

Automated follow-up agents ensure that customer concerns are adequately addressed by following up on unresolved issues. These AI agents can send reminders, collect feedback, and provide additional assistance as needed, ensuring a thorough and satisfactory customer service experience.

Fraud Detection Agents

Fraud detection agents monitor customer interactions and transactions for signs of fraudulent activity. These AI agents analyze patterns and behaviors to identify potential fraud, alerting customer service teams and taking preventive actions to protect customers.

Intelligent routing systems

Intelligent routing systems can solve businesses struggling with routing customer concerns. These AI agents analyze and direct customer issues to the appropriate department or support channel, ensuring accurate and timely resolutions.

Sentiment analysis agents

AI agents can be equipped with sentiment analysis capabilities to mitigate customer dissatisfaction. These agents analyze the emotional tone of customer interactions, detect frustration levels, and help prioritize certain concerns for quicker resolution.

Predictive analysis agents

Predictive analysis agents use historical customer data, browsing history, and purchase patterns to forecast future needs and tailor customer service accordingly. This proactive approach helps in anticipating customer requirements and enhancing service quality.

Knowledge management agents

Knowledge management agents can simplify the management of extensive customer service knowledge bases. These AI agents gather and store information like product details, troubleshooting guides, and frequently asked questions, leveraging machine learning and NLP to keep the knowledge base up-to-date and easily accessible.

AI agents in customer service enhance efficiency and customer satisfaction through various specialized applications, from chatbots to intelligent routing and predictive analysis. These AI agents streamline operations, provide personalized service, and ensure timely and accurate resolutions to customer concerns.

Key capabilities of AI agents for customer service: Enhancing efficiency and customer satisfaction

AI agents transform customer service by providing intelligent, efficient, personalized support across various touchpoints. These advanced systems leverage technologies to enhance customer interactions, streamline processes, and drive overall satisfaction. The capabilities of AI customer service agents include:

  1. Perceive dynamic changes in customer behavior:
    • AI agents can detect and interpret shifts in customer behavior and preferences.
    • They track changes in buying patterns, identify trends in inquiries, and recognize sentiment shifts in feedback.
    • This capability provides valuable insights for improving customer interactions and personalizing responses.
  2. Responsive actions:
    • AI agents respond swiftly to customer needs with real-time insights.
    • They can autonomously escalate critical issues, provide instant answers to common queries, and adjust responses based on customer sentiment.
    • This ensures timely and relevant support, improving the overall customer experience.
  3. Reasoning and interpretation:
    • AI agents use advanced algorithms to analyze extensive datasets, extract meaningful patterns, and derive actionable insights.
    • They understand complex customer queries and predict potential issues, offering accurate and context-aware responses.
    • This enhances their ability to make informed, real-time decisions.
  4. Problem-solving skills:
    • AI agents are proficient at resolving a wide range of customer service challenges.
    • They can troubleshoot technical issues, resolve billing disputes, and assist with product information.
    • Their analytical capabilities help navigate obstacles and deliver effective solutions, boosting customer satisfaction.
  5. Inference and learning:
    • AI agents continuously interact with customer data, engaging in inference and learning processes.
    • They analyze past interactions, identify patterns, and anticipate customer needs.
    • This allows them to adapt strategies and evolve their decision-making capabilities, providing proactive support.
  6. Action and outcome analysis:
    • AI agents simulate scenarios and evaluate potential impacts to predict outcomes.
    • They empower customer service teams with insights for strategic planning, risk mitigation, and resource optimization.
    • This foresight enhances the ability to achieve desired customer service objectives.
  7. Autonomy:
    • AI agents operate with a degree of self-governance, autonomously making decisions and managing resources.
    • They handle routine inquiries, escalate complex issues to human agents, and adapt behaviors to evolving customer needs.
    • This reduces the need for constant human intervention and improves operational efficiency.
  8. Objectives:
    • AI agents align their actions with specific customer service goals, such as reducing response times and improving resolution rates.
    • They focus on delivering tangible outcomes and adding value to the customer service process.
    • This alignment ensures that AI agents contribute to overall business objectives.
  9. Integration across touchpoints:
    • AI agents are implemented across multiple channels, ensuring a seamless customer experience.
    • They interact with customers via chatbots on websites, messaging apps, mobile applications, and social media.
    • This consistent engagement strengthens brand perception and customer loyalty.
  10. Accessing information:
    • AI agents connect with knowledge bases, CRM systems, and databases to access relevant information.
    • They retrieve and synthesize data to fulfill customer requests and resolve issues.
    • This empowers customer service teams with timely and accurate insights, enhancing decision-making.
  11. Natural conversations:
    • AI agents use natural language processing capabilities to engage customers in natural, free-flowing conversations.
    • They emulate human-like interactions, fostering meaningful dialogue and building rapport with customers.
    • This enhances the overall user experience across various communication channels.
  12. Processing natural language requests:
    • AI agents rely on sophisticated natural language understanding to interpret and process text or voice inputs.
    • They analyze linguistic patterns, contextual cues, and user intent to decipher customer queries accurately.
    • This ensures seamless interaction and communication between customers and the customer service team.

By leveraging these key capabilities, AI agents significantly enhance the efficiency and effectiveness of customer service operations, leading to improved customer satisfaction and loyalty.

Use cases of AI agents in customer service

Discover how AI agents in customer service can transform your business by enhancing efficiency, personalizing customer interactions, and streamlining operational processes. Let’s explore use cases of AI customer service agents

Use cases of AI agents in customer service

Quick and accurate answering

Customer concerns about products and services can keep human agents occupied, especially considering their limited availability around the clock.

AI customer service agents provide a solution with a fully automated and accurate FAQ answering system. These AI agents quickly synthesize existing information to deliver responses in seconds, ensuring round-the-clock service. The key capabilities include analyzing customer data to identify keywords, efficiently assigning support tickets, and tracking past interactions. Businesses can leverage these capabilities to ensure every customer query receives a prompt and accurate response. This enhances overall customer satisfaction and loyalty, driving business success.

Personalized recommendations

Poor personalization in customer services to a significant net revenue loss of $756 billion annually for US businesses. Generic responses to queries often lead to customer frustration and missed opportunities for upselling and cross-selling.

Personalization is especially critical in customer-centric sectors such as retail and tourism. Investing in AI agents enables businesses in these industries to deliver highly personalized customer services.

AI agents analyze past data, including purchase and browsing history, and combine it with real-time information. These insights are then used to make fully personalized customer recommendations, enhancing their experience and increasing the likelihood of sales conversion.

Troubleshooting

Traditional troubleshooting approaches often need help with repetitive inquiries, limited access to knowledge bases, and inconsistent resolutions.

AI agents offer a solution by providing step-by-step workflows customized to each customer’s needs. These agents leverage intelligent search functionalities within knowledge bases, allowing customers to find relevant troubleshooting resolutions easily. By streamlining the troubleshooting process and delivering consistent and accurate solutions, AI agents enhance customer satisfaction and efficiency in problem resolution.

Analytics support

Gaining insights into scattered customer data and identifying call patterns, volume, and other factors poses a significant challenge for any customer support team.

AI agents offer a solution by efficiently assisting businesses in collecting, processing, and analyzing customer data. These agents extract data from various sources, such as call transcripts, surveys, and chats, enabling them to uncover hidden patterns and predict customer behavior, call trends, and volume spikes. By leveraging AI-driven analytics, businesses can gain valuable insights into customer interactions, improve service delivery, and proactively address customer needs, ultimately enhancing customer satisfaction and loyalty.

Automated follow-up

Automated follow-up agents ensure that customer concerns are adequately addressed by following up on unresolved issues. These AI agents can send reminders, collect feedback, and provide additional assistance as needed, ensuring a thorough and satisfactory customer service experience.

Fraud detection

Fraud detection agents monitor customer interactions and transactions for signs of fraudulent activity. These AI agents analyze patterns and behaviors to identify potential fraud, alert customer service teams and take preventive actions to protect customers.

AI in customer service streamlines processes, enhances personalization, improves troubleshooting capabilities, provides valuable analytics insights, optimizes resource allocation, breaks language barriers, and supports knowledge management, ultimately leading to improved customer satisfaction and business success.

Resource allocations

Call centers often need help optimizing the utilization of human agents due to inaccurate demand forecasting or rigid scheduling practices. This can result in agent underutilization or burnout, impacting overall efficiency and customer service quality.

AI agents facilitate real-time monitoring of human resource workloads and dynamically allocate resources to meet fluctuating demand. By leveraging predictive analytics, AI agents can proactively schedule human agents during peak hours and dynamically route inquiries based on the skill sets of available agents. This improves efficiency and enhances customer satisfaction by ensuring timely and effective resolution of inquiries. AI-driven agents empower call centers to optimize workforce management and deliver superior customer service, ultimately leading to better operational performance and increased customer loyalty.

Language translation

AI agents are transforming businesses’ ability to provide multilingual customer support seamlessly. By harnessing Natural Language Processing (NLP) capabilities, AI agents can effortlessly translate customer inquiries into any targeted language and deliver appropriate responses. This innovative approach breaks down language barriers in customer support delivery, enabling businesses to cater to diverse customer bases effectively. By leveraging AI-powered multilingual support, businesses can enhance customer satisfaction, improve communication, and expand their global reach. AI agents make customer support more accessible and inclusive across linguistic boundaries.

Knowledge support

Live customer agents often encounter challenges navigating complex knowledge bases and internal resources to resolve issues efficiently. This process can be time-consuming as agents must scan vast business domain knowledge to collect relevant information during a support or troubleshooting session.

AI agents offer a solution by leveraging advanced Natural Language Processing (NLP) capabilities. These agents can parse through written or spoken words, extract keywords, and identify underlying issues quickly and accurately. Based on this understanding, AI agents can expedite issue resolution by recommending relevant knowledge base articles, troubleshooting guides, or internal policies to live agents. By streamlining access to information and providing real-time assistance, AI agents empower live agents to resolve customer issues more efficiently, ultimately improving customer satisfaction and reducing support costs.

Complex reasoning

AI agents employ sophisticated reasoning techniques to analyze customer queries and provide logical solutions. They can follow complex chains of thought, draw connections between different pieces of information, and infer potential solutions to customer problems. By applying advanced reasoning capabilities, they enhance problem-solving abilities and deliver more effective support to customers, even in challenging or ambiguous situations.

Customized text generation

AI agents can generate customized text tailored to specific purposes and contexts. They can produce personalized responses, emails, reports, and marketing content by integrating contextual information and objectives into their language generation models. This capability enables them to communicate effectively with customers, conveying information clearly, concisely, and engagingly, thereby enhancing the overall customer experience.

AI in customer service streamlines processes, enhances personalization, improves troubleshooting capabilities, provides valuable analytics insights, optimizes resource allocation, breaks language barriers, and supports knowledge management, ultimately leading to improved customer satisfaction and business success.

Elevate Customer Service with AI Agents

Leverage our expertise to deploy AI agents that improve customer service
efficiency and satisfaction.

Benefits of AI agents in customer service

AI agents are transforming customer service by offering numerous benefits, from reducing operational costs to enhancing customer satisfaction and employee productivity. Here’s how they make a difference:

Automating routine tasks: Human customer care executives spend much time on mundane tasks like answering emails, handling query calls, and managing tickets. These repetitive tasks can cause delays and inconsistencies in support. AI agents use machine learning, AI algorithms, NLP, and decision trees to automate these tasks, improving efficiency and consistency.

Handling large volumes of data: Effective first contact resolution (FCR) prevents customer churn. AI agents excel at swiftly analyzing vast amounts of data to identify patterns and root causes of issues, enabling them to provide timely and relevant resolutions.

Reducing Average Handling Times (AHT): Businesses with high customer satisfaction often have low wait times. AI agents provide immediate responses, especially in live chat, reducing AHT and enhancing customer satisfaction.

Consistent support: Customers expect consistent interactions across all touchpoints. AI agents ensure uniformity in responses across different platforms and departments by recording every interaction and using the same data to provide answers.

Multilingual support: Global businesses need to offer support in multiple languages. AI agents use conversational AI and natural language understanding to automatically translate customer inquiries, providing seamless multilingual support without additional costs.

Saving operational costs: AI agents can save annual costs as they don’t require ongoing training and can handle mundane tasks, allowing human agents to focus on higher-value tasks. AI agents can operate around the clock, eliminating the need for costly after-hours support and reducing reliance on third-party providers.

Easy scalability: AI agents can be scaled instantly with minimal programming adjustments. Unlike human agents, they can handle sudden increases in call volumes or seasonal fluctuations without requiring extensive hiring and training.

Eliminating repetitive explanations: Customers dislike having to explain their issues multiple times. AI agents have instant access to past interactions, allowing them to provide immediate and informed responses without requiring customers to repeat themselves.

Personalized interactions: AI agents personalize customer interactions by processing real-time data, referencing past assistance, and adding crucial insights. This personalized approach makes customers feel valued and heard, reducing churn and increasing satisfaction.

Easy data availability: Finding relevant customer information quickly is challenging for human agents. AI agents provide instant access to crucial data, helping human agents understand the context of the issue and respond more effectively.

AI agents in customer service streamline operations, reduce costs, enhance customer satisfaction, and boost employee productivity by automating routine tasks, providing consistent and personalized support, and enabling easy scalability and multilingual capabilities.

How to implement AI agents in customer service workflow?

Integrating AI agents into customer service can significantly enhance efficiency, response time, and customer satisfaction. Here’s a structured approach to implementing AI agents in your customer service operations:

Define clear objectives

  • Identify goals: Define specific goals for integrating AI into customer service. These include reducing response times, improving customer satisfaction, automating routine inquiries, and providing 24/7 support.
  • Prioritize use cases: Focus on high-impact use cases such as handling frequently asked questions, triaging customer issues, and providing personalized recommendations.

Assess current systems

  • Evaluate infrastructure: Assess your existing customer service infrastructure to determine compatibility with AI technologies. Consider the systems in place for customer relationship management (CRM), ticketing, and communication channels.
  • Data readiness: Ensure you can access clean, structured data on customer interactions, including historical data from emails, chats, and calls.

Choose the right AI technology

  • Select appropriate tools: Choose AI technologies that align with your customer service goals. Natural Language Processing (NLP) for chatbots, sentiment analysis for understanding customer emotions, and machine learning for predicting customer needs are essential tools. Tools like CrewAI and AutoGen Studio facilitate rapid prototyping and integration of AI capabilities, ideal for deploying sophisticated marketing solutions.
  • Vendor selection: Evaluate and select vendors or platforms that offer robust AI solutions tailored for customer service.

Assemble a skilled team

  • Multidisciplinary team: Form a team that includes experts in AI, data science, software development, and customer service operations.
  • Collaborative approach: Foster collaboration between IT, customer service, and business units to ensure the AI solution meets operational needs and enhances customer experiences.

Develop and train AI agents

  • Custom development: Build AI agents tailored to your specific requirements. Develop chatbots for handling common queries and virtual assistants for more complex tasks. For custom model building, utilize specialized tools and environments provided by tools like CrewAI and AutoGen Studio.
  • Training: Train your AI agents using historical customer service data to understand common inquiries and appropriate responses.

Test the agent
Conduct thorough testing to validate the functionality, performance, and security of your AI agent. Perform tests such as performance testing, security testing, and user acceptance testing to ensure the agent meets technical specifications and user expectations.

Integrate with existing systems

  • Seamless integration: Integrate AI agents with your existing CRM, ticketing, and communication systems to ensure a seamless flow of information.
  • APIs and plugins: Use APIs and plugins to facilitate easy integration and ensure the AI agents can access and update customer information in real-time.

Implement necessary infrastructure and tools

  • Cloud services: Leverage cloud services for scalability and flexibility in managing AI workloads.
  • Analytics tools: Implement data analytics tools to monitor AI agent performance and gather insights on customer interactions.

Monitor and optimize

  • Continuous monitoring: Regularly monitor the performance of AI agents using key metrics such as response time, resolution rate, and customer satisfaction scores.
  • Feedback loop: Establish a feedback loop where customer service representatives and customers can provide input on AI agent interactions.
  • Iterate and improve: Use feedback and performance data to continuously iterate and improve the AI algorithms and workflows, ensuring they adapt to changing customer needs and behaviors.

Ensure compliance and security

  • Data privacy: Implement stringent data privacy and security measures to protect customer information.
  • Regulatory compliance: Ensure your AI solutions comply with relevant regulations and industry standards.

Following these steps, you can seamlessly integrate AI agents into your customer service operations, enhancing efficiency, improving customer satisfaction, and enabling your team to focus on more strategic tasks.

How can LeewayHertz help you build AI agents for customer service?

LeewayHertz recognizes the pivotal role of AI agents in transforming customer service. These AI-driven technologies are reshaping the future of customer service in an increasingly digital world. Here’s how LeewayHertz can assist your organization in leveraging AI agents for customer service:

Strategic consultation

LeewayHertz offers strategic consultation to help businesses understand the potential of AI agents in enhancing customer service. Our experts work closely with you to identify key areas where AI can provide significant advantages, developing tailored strategies for digital transformation that align with your customer service objectives.

Custom AI agent development

We specialize in developing custom AI agents tailored to unique customer service needs. Leveraging advanced tools and technologies like AutoGen Studio, Crew AI, and TaskWeaver, we ensure that the AI agents are well-equipped to handle specific customer service tasks, such as inquiry handling, issue resolution, and personalized assistance.

Seamless integration

Our team seamlessly integrates AI agents into your existing customer service systems and platforms. Leveraging advanced integration tools and methodologies ensures these intelligent systems work seamlessly with your current IT infrastructure, enhancing data interoperability and operational efficiency.

Continuous support and optimization

LeewayHertz provides continuous support, monitoring, and optimization services to ensure your AI agent adapts to evolving customer needs and challenges. We are committed to ensuring that your AI agents deliver high performance consistently, driving customer satisfaction and loyalty.

Driving innovation in customer service

Our AI agents are designed to optimize customer service operations, improve response times, enhance customer interactions, and deliver personalized experiences that exceed customer expectations. By partnering with LeewayHertz, businesses can stay ahead of the curve and drive innovation in customer service.

LeewayHertz offers the expertise, technology, and support necessary to develop and integrate AI agents that will transform customer service operations. By leveraging AI-driven technologies, businesses can enhance customer experiences, drive operational efficiency, and gain a competitive edge in the market

Endnote

AI customer service agents significantly shift how businesses interact with their customers. These advanced assistants offer practical solutions rather than merely embodying futuristic ideals. They streamline processes, automate tasks, and provide personalized support, all while operating seamlessly around the clock.

What sets AI agents apart is their ability to process and interpret vast amounts of data in real time. This empowers businesses to derive actionable insights and make informed decisions, leading to more proactive and customer-centric strategies.

Moreover, AI agents contribute directly to a company’s bottom line by optimizing resource allocation, reducing response times, and boosting overall productivity. Their impact extends beyond operational efficiency, fostering deeper customer connections and driving sustainable growth in today’s competitive landscape.

AI customer service agents represent not just a technological advancement but a practical solution to the ever-evolving demands of modern business. By embracing their capabilities, companies can position themselves for success in the digital age, delivering superior experiences and staying ahead of the curve.

Transform your customer service with the power of AI agents! Discover how LeewayHertz’s AI agent development services can streamline your operations, enhance customer interactions, and boost efficiency.

Listen to the article
What is Chainlink VRF

Author’s Bio

 

Akash Takyar

Akash Takyar LinkedIn
CEO LeewayHertz
Akash Takyar is the founder and CEO of LeewayHertz. With a proven track record of conceptualizing and architecting 100+ user-centric and scalable solutions for startups and enterprises, he brings a deep understanding of both technical and user experience aspects.
Akash's ability to build enterprise-grade technology solutions has garnered the trust of over 30 Fortune 500 companies, including Siemens, 3M, P&G, and Hershey's. Akash is an early adopter of new technology, a passionate technology enthusiast, and an investor in AI and IoT startups.

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