How Localised AI is Set to Revolutionise Real-Time Chatbot Interactions
Driven by Avnet Silica's Scalable Embedded Solutions
The generative AI market is experiencing exponential growth and is projected to surge from $3 billion in 2022 to $108 billion by 2032—that’s an impressive compound annual growth rate (CAGR) of 43%. As industries seek more efficient, responsive, and privacy-preserving AI solutions, Generative AI at the Edge is emerging as a game-changer. Unlike cloud-based AI models, 'Edge GenAI' enables real-time, low-latency interactions while also ensuring data privacy and security.
This article explores the increasing demand for localised AI solutions, particularly in the field of voice chatbots, which leverage Avnet Silica’s modular hardware and software architecture to provide scalable, real-time chatbot interactions across industries. It highlights the technical advancements in Edge AI, the applications of embedded chatbot systems, and how Avnet Silica’s chatbot (running on TRIA System on Modules (SOMs) and other technologies) and software support ecosystem enable the seamless deployment of next-generation AI-powered voice assistants.
The Rise of Generative AI and Market Forecast
Generative AI Market Overview
Generative AI has transitioned from an experimental concept into a pivotal technology reshaping industries ranging from customer service to industrial automation. The advent of Large Language Models (LLMs) and AI-driven natural language processing (NLP) systems has enhanced human-computer interactions, making AI-powered assistants more intuitive and contextually aware. Businesses across various sectors are leveraging generative AI to improve efficiency, optimise operations, and deliver seamless customer experiences.
NEED AI SUPPORT? SPEAK TO OUR EXPERTS
Future Prospects for Generative AI
According to the Bloomberg GenAI Report, the generative AI market is projected to reach a staggering $1.3 trillion by 2032. The conversational AI sector alone is expected to grow exponentially, surging from $3 billion in 2022 to $108 billion by 2032. This growth will be fueled by advancements in AI model efficiency, increased computing power, and widespread business adoption.
Leading AI companies continue to attract substantial investments. In June 2024, Mistral AI secured $645 million in funding, elevating its valuation to $6 billion. Similarly, in October 2024, OpenAI raised $6.6 billion, pushing its valuation to $157 billion. These figures underscore the accelerating momentum of AI-driven solutions and signal the increasing reliance on sophisticated AI technologies in both enterprise and consumer applications.
As AI adoption grows, businesses are shifting their focus toward real-time, scalable AI solutions that can be embedded directly into infrastructure, reducing dependency on cloud-based services. This shift highlights the demand for localised AI processing, which ensures lower latency, greater data privacy, and higher system reliability. Edge GenAI solves these evolving needs, paving the way for more autonomous and intelligent applications across multiple industries.
The Importance of an Edge GenAI Revolution
Cloud AI vs. Edge GenAI
Traditional AI applications have predominantly relied on cloud computing for processing, which introduces challenges such as latency, high data transmission costs, and privacy concerns. Cloud-based AI requires constant internet connectivity, which may not always be possible or reliable. It often involves sending sensitive data off-site raising security and compliance issues. As AI adoption expands across industries, businesses are recognising the need for localised AI solutions that can operate independently of cloud infrastructure.
Generative AI at the Edge
See advantages of Generative AI at the Edge, learn more about Edge GenAI locations, see GenAI at the Edge in Action Edge and access GenAI resources such as articles and case studies.
Edge GenAI offers a transformative alternative by enabling AI processing directly on embedded devices. This approach minimises the need for cloud interactions, allowing businesses to achieve real-time, secure, and efficient AI-driven operations without excessive data transmission.
Key Benefits of Edge GenAI
One of the primary advantages of Edge GenAI is low latency, ensuring real-time responses without depending on cloud-based processing. This is especially crucial for applications such as voice chatbots, where delays can disrupt natural interactions. Additionally, enhanced privacy is a key differentiator; since data is processed locally on the device, sensitive information is not transmitted to external servers, reducing the risk of breaches or unauthorised access.
Beyond privacy and speed, reduced bandwidth costs are another notable benefit. As AI models become increasingly complex, cloud processing costs can escalate, making Generative AI at the Edge a cost-effective solution by significantly decreasing the reliance on internet connectivity. Furthermore, higher reliability is achieved as this technology enables continuous functionality even in offline environments, giving operational stability in critical applications such as industrial automation and autonomous systems.
By embedding AI models directly into local devices, industries can personalise interactions, ensure regulatory compliance, and reduce operational risks while maintaining full control over their data. As the demand for AI-driven solutions grows, Edge GenAI represents a pivotal shift towards efficient, scalable, and privacy-conscious AI applications across multiple industries.
Practical Applications of Edge Chatbots
Michael Uyttersprot walks through all of the Edge GenAI demonstrations on show at embedded world 2025
Transforming Industries with Edge AI Chatbots
Edge AI chatbots are driving transformation across multiple industries by enabling real-time, localised interactions. By integrating AI-powered voice assistants into various operational environments, businesses can improve efficiency, enhance user experience, and maintain continuity even in offline conditions.
Hospitality – AI Brings Automated Check-Ins & Virtual Concierge
The hospitality industry is increasingly adopting AI chatbots to streamline guest interactions. Automated check-in and check-out systems ensure seamless guest experiences even during internet outages. These chatbots function as ‘virtual concierges’, answering guest queries, managing room service requests, and assisting with reservations. An example of this implementation can be seen in some late-night hotel receptions, where AI-driven check-ins reduce wait times and improve customer satisfaction. By minimising the need for front desk staff during off-peak hours, hotels can enhance operational efficiency while maintaining high service standards.
Transportation – Smart Bus Stops Increase Accessibility
In the transportation sector, Edge AI chatbots are being leveraged to provide dynamic, real-time bus information to passengers, including those with visual impairments. These chatbots integrate with existing timetable databases, allowing travelers to access schedules, route details, and estimated arrival times through voice commands. Additionally, their compliance with the European Accessibility Act (EAA) ensures that they cater to the needs of all users, improving accessibility and inclusivity in public transport. Hands-free interaction capabilities allow passengers to navigate transportation systems effortlessly, even in challenging or noisy environments.
Industrial Automation – AI Chatbots Become Smart Equipment Assistants
AI chatbots enhance operational efficiency in industrial environments by enabling voice interaction with industrial equipment. Whether integrated into industrial ovens, Human-Machine Interfaces (HMI) systems, or robotics, these chatbots support a range of functionalities, from monitoring machine status to providing automated troubleshooting. They assist operators by answering queries like error diagnostics, recipe recommendations, and workflow optimisations, reducing downtime and ensuring that production processes remain smooth and efficient. By embedding AI-driven assistants into industrial systems, companies benefit from improved equipment utilisation, enhanced safety measures, and minimised operational disruptions.
Edge AI-powered chatbots are redefining how businesses interact with customers and manage operations. They offer real-time intelligence, accessibility improvements, and enhanced automation across multiple industries.
Avnet Silica's Edge GenAI-Powered Ecosystem
Avnet Silica’s Vision for Edge AI
Avnet Silica has established itself as a leader in Edge AI solutions by offering a robust ecosystem of hardware, software, and technical support designed to meet the needs of industries that demand real-time, localised AI processing. The goal is to provide businesses with the tools to integrate Edge AI seamlessly into their operations, ensuring performance, adaptability, and efficiency while reducing dependence on cloud-based systems.
Innovations in Hardware and Software Architecture: The "Phone Box" Chatbot – A Case Study in Edge AI
One of Avnet Silica’s flagship innovations in Edge AI is the "Edge GenAI Phone Box," an AI-powered voice chatbot designed to demonstrate the effectiveness of localised, real-time AI processing. This solution showcases how embedded AI can drive efficiency, enhance customer interactions, and provide automation across various industries without relying on cloud infrastructure.
The Edge GenAI Phone Box leverages multiple AI-driven components, each contributing to its ability to process and generate natural and context-aware speech..
Several advanced AI technologies are at the core of this system that ensure high performance and seamless user interactions:
The Whisper Speech-to-Text (STT) engine is a robust automatic speech recognition (ASR) system designed to transcribe spoken language into text accurately. It is adept at handling multiple languages, diverse accents, and noisy environments, making it ideal for precise voice recognition applications. This capability ensures that the Phone Box can accurately capture user commands and interpret requests without errors, even in challenging conditions.
Complementing Whisper is the Piper Text-to-Speech (TTS) engine, which generates high-quality, natural-sounding voice outputs. Piper’s strength lies in its ability to produce human-like speech patterns that enhance the conversational experience, making interactions with the chatbot feel fluid and intuitive. Combining Whisper’s accurate transcription and Piper’s expressive speech synthesis allows for real-time, smooth, two-way communication.
To enhance multilingual support and improve responsiveness, the Phone Box incorporates local language models that allow for fast, on-device processing of AI-generated responses. Unlike cloud-based solutions that require constant data transmission, these local models enable instant replies, making the chatbot highly effective in applications where speed and security are critical.
Additionally, the MQTT broker facilitates efficient message handling within the system, ensuring smooth and structured interactions between various components of the chatbot. This enables real-time coordination between speech recognition, response generation, and audio playback, creating a seamless user experience.
By integrating these elements, the Phone Box chatbot serves as a prime example of how Edge AI can optimise efficiency, reduce operational costs, and provide robust automation while maintaining data privacy and independence from cloud-based infrastructures.
TRIA System on Modules (SOMs) – Modular Hardware for Scalable AI
TRIA System on Modules (SOMs) are the foundation of Avnet Silica’s hardware ecosystem that provide a versatile and modular platform to facilitate scalable AI deployment. The modules allow businesses to customise AI solutions for different industry applications while ensuring high performance and energy efficiency.
The TRIA SOMs offer multiple benefits, including:
- Flexibility – Various configurations are available to meet the diverse needs of industries, from automotive to industrial automation.
- Optimised Performance – AI workloads are handled with low power consumption, enabling sustainable and efficient embedded processing.
- Scalability – The modular approach ensures easy integration into a wide range of applications, allowing businesses to expand their AI capabilities as needed.
TRIA SOMs empower businesses to build custom AI-driven systems without the complexity of designing hardware from scratch. This streamlined approach reduces design iterations and accelerates time-to-market for AI-powered applications.
Comprehensive Support for Scalable Solutions
Avnet Silica offers more than hardware and software solutions with a complete ecosystem of support services to ensure successful AI deployment. The company’s TRIA software team is dedicated to helping businesses customise and optimise their AI integrations, tailoring solutions to meet specific operational needs. Whether businesses require language model adaptations, integration with existing systems, or additional AI functionalities, Avnet Silica provides hands-on assistance to streamline implementation.
Furthermore, the Field Application Engineer (FAE) team is crucial in supporting and guiding businesses through development and deployment. FAEs provide technical expertise, helping customers configure, test, and optimise their AI solutions for peak performance. From proof-of-concept development to full-scale deployment, Avnet Silica offers comprehensive end-to-end resources to ensure smooth adoption of AI-powered automation.
Avnet Silica delivers modular, scalable, and fully supported AI solutions that ensure businesses can confidently adopt AI-driven automation. The Phone Box chatbot and TRIA SOM ecosystem illustrate the company’s commitment to innovation, offering businesses the tools they need to enhance efficiency, improve automation, and stay competitive in an increasingly AI-driven world.
Conclusion & Future Outlook
The Road Ahead for Edge GenAI
As industries continue to embrace AI-driven solutions, Edge GenAI is set to play a pivotal role in enabling real-time, efficient, and privacy-conscious applications. The future of AI is shifting toward localised processing, reducing the dependence on cloud infrastructures while enhancing security and responsiveness. Several key trends are expected to shape the future of Edge GenAI:
The expansion of localised AI models will drive broader adoption across industries. Companies can deploy AI chatbots and automation tools customised to specific operational needs. This evolution will support sectors such as hospitality, industrial automation, and transportation, where immediate response times and data privacy are critical.
Another transformative factor is the adoption of energy-efficient AI hardware, which will facilitate Edge AI integration into embedded systems with minimal power consumption. As industries move toward sustainable AI solutions, advancements in hardware efficiency will enable widespread deployment, ensuring that businesses can harness the benefits of AI without significantly increasing energy use.
Additionally, as AI privacy and security regulations continue to evolve, businesses must prioritise compliance with global standards. Edge GenAI’s inherent ability to process data locally provides a competitive advantage by mitigating concerns over data exposure, making it a preferred choice for industries with strict privacy mandates.
Avnet Silica’s Commitment to the Future
Recognising the growing importance of Edge AI solutions, Avnet Silica remains at the forefront of innovation. It provides businesses with modular, scalable chatbot platforms that enable real-time AI processing. Through its Phone Box and TRIA SOM ecosystem, Avnet Silica offers industry-leading solutions designed to meet the demands of modern businesses. Avnet Silica is poised to help companies navigate the future of AI-driven automation by ensuring that AI applications remain adaptive, scalable, and privacy-focused.
At Avnet Silica, we believe the future of AI is not just about innovation—it’s about making technology work for you in real-time, where you need it most. Whether you're looking to enhance customer interactions, improve operational efficiency, or build a more responsive and privacy-conscious AI system, we’re here to help.
Let's explore how Edge GenAI can transform your business:
- Want to see it in action? Keep up with our upcoming events and look out for a hands-on demo of the "Phone Box" chatbot.
- Need a tailored solution? Our experts are ready to work with you on customised AI integration strategies.
- Are you looking for a scalable AI foundation? Discover how our TRIA SOM hardware and software ecosystem can meet your specific needs.
We're here to help you take the next step toward the future of AI. Reach out today, and let’s start building something incredible together.
Working on an Artificial Intelligence project?
Our experts bring insights that extend beyond the datasheet, availability and price. The combined experience contained within our network covers thousands of projects across different customers, markets, regions and technologies. We will pull together the right team from our collective expertise to focus on your application, providing valuable ideas and recommendations to improve your product and accelerate its journey from the initial concept out into the world.
Sources:
Market Data and Industry Forecasts:
- Bloomberg Report GenAI - Market projection for Generative AI reaching $1.3 trillion by 2032.
- Conversational AI Market Growth - Expected increase from $3 billion in 2022 to $108 billion by 2032.
AI Investment and Industry Leaders:
- Mistral AI Raises $645 Million at $6 Billion Valuation - Funding secured in June 2024.
- OpenAI Raises $6.6 Billion, Valuation at $157 Billion - Funding secured in October 2024.
Edge AI Technologies and Innovations:
- Whisper Speech-to-Text Engine - OpenAI’s automatic speech recognition (ASR) system supporting multiple languages.
- Piper Text-to-Speech Engine - Open-source TTS engine optimised for low-power embedded applications.
- MQTT Protocol for IoT and AI Messaging - Efficient message brokering system for real-time applications.
Edge AI Use Cases:
- European Accessibility Act (EAA) Compliance - Regulations ensuring AI-based accessibility in public services.
- AI in Industrial Automation - Applications in robotics, HMI systems, and predictive maintenance.
- Edge AI in Smart Transportation - Enhancing real-time information access and improving accessibility.
Overview
Generative AI Overview
Head over to our Generative AI overview page for more Generative AI articles, applications and resources.