AI and speech technology
Assist-Me embeds and integrates the very latest conversational AI and generative AI technology to provide intelligent AI Assistants and voice assistants.
Generative AI and LLMs
Generative AI refers to a class of artificial intelligencethat can create new content — whether it’s text or images. At the heart of manygenerative AI applications in the workplace are Large Language Models (LLMs)like OpenAI's GPT, Google's Gemini, or Meta’s LLaMA. These models are trainedon vast datasets to understand human language and generate responses that arecoherent, helpful, and natural-sounding.
In customer service and employee support, LLMs provide the intelligence behind tools that can automatically draft knowledge base articles, summarise complex policies, answer user questions, or interpret nuanced queries from employees or customers. For example, when a customer types a complicated refund question, an LLM can understand the intent and respond with the right procedure, tone, and level of detail.
LLMs don’t operate alone — they serve as the core engine powering more interactive technologies like AI chatbots, voice assistants, and task-based agents. They give these tools the ability to understand natural language, generate appropriate replies, and adapt to context — making support more efficient and less dependent on static scripts or manual interventions.
Generative AI was introduced to converse360’s platform in2024 and is the technology that enhances the conversational AI intelligence. Itis also the technology that learns your unique content through uploaded contentand provides responses specific to your environment.
Converse360’s platform supports nearly all the LLM providersand Generative AI frameworks including: Google Gemini, Open AI, Anthropic, MetaLlama, Cohere, Amazon Bedrock and Huggingface.
Conversational AI
Conversational AI is the technology that enables machines to engage in dynamic, natural language conversations with people. It combines the understanding power of LLMs with conversational structure, memory, and context tracking to handle ongoing, multi-turn interactions.
In customer service, conversational AI can power intelligent virtual assistants that help customers resolve issues without needing to speak to a human. Conversational AI enables you to offer more structured responses, create workflows that are consistent and provide compliant replies from your content. Assistants using Conversational AI can guide users through troubleshooting steps, collect required details for support tickets, and escalate cases when necessary — all while maintaining a consistent tone and understanding of prior messages.
In employee support, conversational AI can become a digital assistant for HR, IT, or internal service desks. An employee might ask, “How doI reset my email password?” or “What’s our maternity leave policy?” and the AI can respond immediately with the correct, personalised information — saving time for both the employee and the internal support team.
Conversational AI isn’t just about language understanding —it’s about building dialogue systems that feel fluid and helpful, enabling people to get what they need through simple, natural conversations.
Converse360’s platform has been using Conversational AI since 2018 and it is the foundation of the platform. The platform orchestratesAI models from providers such as Google Dialog flow. IBM Watson and AWS.
AI Chatbots and AI Agents
AI Chatbots and AI Agents are tools that interact with users via chat or messaging interfaces, but there’s an important distinction between the two.
AI Chatbots are designed to respond to user queries, often in a structured way. They’re ideal for high-volume, repetitive tasks in customer service like answering FAQs, checking order statuses, or guiding users through standard processes. When powered by LLMs, chatbots become far more flexible and can handle open-ended questions or conversational inputs that would confuse traditional bots.
AI Agents, on the other hand, go beyond conversation.They are action-oriented digital workers that not only chat but also execute tasks on behalf of the user. For instance, an AI agent might help a customer change their subscription plan, initiate a return request, or update billing details by interacting with backend systems through APIs.
For employees, an AI agent might submit a holiday request, file an IT ticket, or gather information from different internal systems — all from a single conversation. These agents combine conversation with automation, enabling them to serve as a bridge between users and complex internal workflows.
Voice Assistants
Voice Assistants are AI systems that allow users to interact using spoken language. They convert speech into text, process the request, generate a response, and speak it back — enabling a hands-free, conversational experience.
In customer service environments, voice assistants can be used in call centres or IVR systems to handle routine inquiries like “Where is my order?”, “How do I return an item?”, or “What are your store hours?” This reduces wait times and offloads work from human agents.
For employee support, voice assistants can act as on-demand helpdesk tools. Imagine a busy employee asking, “What’s the Wi-Fi password for the guest network?” or “How do I book a meeting room?” — and getting an instant verbal reply. When powered by LLMs, these assistants can understand a wider range of questions, recognise intent, and even maintain context across multiple steps in the conversation.
Voice assistants enhance accessibility and convenience, particularly in environments where typing isn’t practical — like warehouses, retail floors, or while on the go.
Agentic AI
Agentic AI represents a more advanced evolution in AI —where systems behave like autonomous digital employees that can plan, reason, and act over time to achieve goals. Unlike traditional bots that wait for instructions, Agentic AI systems can proactively monitor, decide, and perform actions with minimal human oversight.
In customer service, agentic AI can analyse conversation trends, predict when a customer might churn, and initiate personalised out reach or offer solutions. It can also monitor ongoing tickets and escalate complex cases before a customer becomes frustrated.
For employee support, agentic AI can act like a smart operations assistant — identifying recurring issues (like repeated VPN login problems), auto-generating help content, or even coordinating follow-up tasks across departments.
Agentic AI is especially powerful when it combines generative language models with tools like calendars, ticketing systems, or knowledge bases. These agents can maintain context, follow long-term goals, and take initiative — freeing up human staff for higher-value work and making support systems smarter and more responsive.
Speech technology
As voice interactions become more common in customer and employee support, speech technology plays a critical role in delivering seamless, intelligent experiences. Whether it's understanding a caller’s request or responding in a natural voice, these tools form the bridge between spoken language and digital systems.
Speech-to-Text (STT)
Speech-to-Text, also known as automatic speech recognition (ASR), converts spoken language into written text in real time. This allows customers or employees to speak naturally instead of typing — whether they’re using a virtual helpdesk, a call centre IVR, or a hands-free voice assistant.
High-quality STT systems can handle accents, noise, and fast speech — ensuring accurate transcription even in real-world conditions.
Text-to-Speech (TTS)
Text-to-Speech technology converts written text into spoken words. It enables AI systems to respond to users using natural-sounding voices — making interactions more engaging and accessible.
Modern TTS systems offer:
- Natural-sounding voices with emotional tone, pacing, and intonation.
- Multiple voice options, including male/female, regional accents, and formal or casual tones.
- Real-time rendering, so conversations flow smoothly without noticeable delay.
In practice, this means customers don’t hear robotic responses — they hear a friendly, branded voice that feels human and responsive.
Voice Quality and Control
Voice technology now offers different quality levels based on use case and channel:
- Standard quality is ideal for quick, informative replies in IVRs or internal tools.
- Premium neural voices are used in customer-facing roles for a more lifelike, expressive experience.
- Ultra-natural TTS is suited for applications where brand voice matters — such as luxury services.
Advanced platforms allow you to:
- Control speaking speed, pitch, and emphasis.
- Insert pauses, breathing sounds and laughter for realism.
- Use dynamic responses, blending human-crafted content with generated replies.
Voice Cloning and Custom Voices
Voice cloning enables the creation of custom digital voices based on a real person’s voiceprint — or the design of a completely unique brand voice. This is ideal when consistency and identity matter.
For example:
- A brand can offer the same support voice across phone, mobile app, and smart speakers.
- An executive or team lead could “train” an internal voice assistant to speak in their tone for personalized leadership updates.
Ethical controls are built into most voice cloning platforms to prevent misuse and ensure consent-based voice training.
How all the technologies come together
In a modern AI-driven customer experience, speech technology works hand-in-hand with LLMs, conversational AI, and agents. For example:
Natural Greeting
Customers are welcomed by a lifelike TTS voice on your support line.
Understanding
Speech-to-text instantly converts spoken queries into accurate text
Intelligent Action
AI processes requests, retrieves information, books appointments, or escalates cases.
Conversational
Natural voice output keeps callers engaged and supported throughout the interaction.
This creates an end-to-end experience that feels effortless for the user — while automating key processes behind the scenes.
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