Ifeoluwa Oduwaiye
May 16, 2025
Agentic AI has been saving lives since… well, since the launch of IBM Watson. Taking a walk down memory lane, we first saw the rise of supervised machine learning and forecasting models and how they transformed finance firms into fintech giants. Then came generative AI and everyone's best buddy, ChatGPT.
And now, there’s a new big boy in town and he goes by the name Agentic AI. We have transitioned from simple FAQ chatbots to fully autonomous agents that kick crime like CIA agents. With accessibility being the new industry standard, most agentic AI services are now voice-operated.
If you’re looking to build an agentic AI service for your business in this age, speech generation would be one of the key processes to make or break the service. In this blog, we will focus on the need for effective speech generation models in today’s agentic AI services, the top speech generation models worth using right now, as well as a preview of Spitch Agents; our new agentic AI product for businesses looking to reach customers in their native languages.
What Is Agentic AI?
According to Harvard Business Review, Agentic AI refers to AI systems and models that can act autonomously to achieve goals without the need for constant human guidance. These agents perceive, decide, and act on their own. What does this mean for businesses? That means we can now build and deploy services that transcend from information retrieval to being able to take action on user queries.
These actions could be making bookings, financial transactions, or even troubleshooting IT issues. Some of the key capabilities of Agentic AI are:
Autonomy & Goal‑Oriented Planning: Agentic AI systems set and pursue their objectives, breaking high‑level goals into actionable sub‑tasks using hierarchical reasoning and planning algorithms. This level of autonomy allows them to manage complex workflows with minimal human intervention, reducing operational costs and accelerating response times.
Situational Awareness: Agents continuously ingest multimodal inputs from environmental sensors, user actions, and internal performance metrics to maintain a dynamic model of the world. By tracking context in real-time, they can proactively adjust behavior, minimizing errors and downtime in critical applications like IoT monitoring and autonomous vehicles.
Reasoning & Decision‑Making: Moving beyond simple rule execution, agentic AI leverages large language models, reinforcement learning, and probabilistic inference to weigh trade‑offs and select optimal courses of action. This advanced reasoning capability enables them to handle ambiguous scenarios such as personalized financial advice or dynamic resource allocation, and deliver high-quality outcomes and strategic insights.
Adaptive Learning & Memory: Agentic systems can refine their strategies through continual learning, retaining contextual memory across interactions. This adaptability ensures that agents improve their performance with every interaction.
Multi‑Modal Interaction: By fusing text, speech, vision, and other sensory channels, agentic AI achieves more natural and accurate interactions. For instance, an in‑store kiosk can recognize products via camera input and offer real‑time vocal guidance, or a telemedicine robot can combine spoken instructions with haptic feedback. This enhances accessibility and engagement across diverse use cases.
These capabilities make agentic AI a powerful force for automation and innovation, enabling businesses to deploy intelligent agents that perceive complex environments, converse naturally, learn continuously, and collaborate effectively. And in the long run, these systems transform how organizations operate and engage with their customers.
Top Speech Generation Service Providers
In this part of the blog, we will be taking a closer look at some of the most popular speech generation models in 2025.
Amazon Polly Neural TTS
Shortly after the debut of Wavenet, one of the first commercially available TTS services, Amazon launched Polly in late 2016 as a managed text-to-speech API. Amazon Polly is a fully managed service that generates voice on demand, converting any text to an audio stream. With the 2019 introduction of Neural TTS voices, Amazon shifted to a two-stage architecture: a Tacotron-style sequence-to-sequence model generates mel-spectrograms, and a neural vocoder converts them to waveforms.
This separation of concerns struck a practical balance and was able to deliver lifelike speech at lower latency and cost than pure waveform models. While Polly’s closed-source API democratized access to dozens of languages and styles, it offered limited on-prem customization and became a black-box service for enterprises.
Microsoft Azure Neural TTS
In late 2018, Microsoft entered the speech generation race with Azure Neural TTS. By leveraging transformer-based acoustic models and a proprietary neural vocoder, Azure’s service is able to produce rich, expressive voices dubbed “HD.” Azure Neural TTS’ major selling point is its customization. Speech Synthesis Markup Language (SSML) tags allowed fine control over emotion, emphasis, and even viseme data for avatar lip-sync.
By utilizing containerized deployments, companies are also able to keep speech synthesis as on-prem infrastructure. However, mastering the service demanded fluency in SSML and high computing investment for high-fidelity voices.
ElevenLabs Voice Engine
When ElevenLabs launched its Voice Engine in early 2023, it merged a commercial polish with research-grade prosody control. ElevenLabs’ pipeline began with a spectrogram generator which was then fed into a low-latency GAN-based vocoder. This generator was inspired by FastSpeech and enhanced by sentiment-aware embeddings.
The resulting voice output dynamically adjusts tone, pacing, and emphasis based on narrative context. ElevenLabs is particularly common amongst content creators and indie studios for its expressive, story-driven speech even though its powerful voice-cloning capabilities raised ethical questions.
OpenAI TTS
OpenAI TTS is a commercial speech generation service powered by OpenAI. Introduced at DevDay on November 6, 2023, the TTS service was trained on hundreds of thousands of hours of multilingual speech–text pairs curated across diverse domains, and is capable of generating human-like voices in over 100 languages. Its architecture uses transformer-based acoustic models to predict high-resolution mel-spectrograms, followed by a GAN-based neural vocoder for low-latency, high-fidelity waveform synthesis.
The main selling point is its seamless integration with GPT-powered conversational pipelines, enabling end-to-end voice interactions without stitching together separate services. However, its lack of fine-grained emotional-affect controls might be of concern to businesses looking to maintain strict brand voice consistency.
Cartesia TTS
Cartesia TTS is an enterprise-grade speech generation service powered by Cartesia Labs. Introduced in March 2024, the TTS service was trained on over 50,000 hours of professionally recorded, multi-domain speech–text data, and is capable of generating human-like voices in 30+ languages. Its architecture was built using Conformer-based sequence-to-sequence acoustic models to produce high-resolution mel-spectrograms, coupled with a HiFi-GAN neural vocoder for real-time waveform synthesis.
The main selling point is its fully customizable, brand-aligned voice personas, allowing businesses to craft unique audio identities. Compute-intensive model requirements might be of concern to businesses looking to deploy on low-resource edge devices or minimize cloud inference costs.
ChatTTS
ChatTTS is an open-source speech generation model designed for conversational applications. ChatTTS model was trained on 100,000 hours of Chinese and English and is capable of producing high-quality, natural-sounding speech in both languages.
The main selling point of ChatTTS is its open-source nature and its high-quality synthesis of human speech. If you’re looking for an affordable high-quality TTS service, you should consider ChatTTS.
Dia
Designed by Nari Labs, Dia is a speech generation model that performs best in dialogue generation use cases. With its 1.6B parameter training scope, Dia generates realistic conversations from text scripts for multiple speakers. It also factors in non-verbal elements in spoken language like laughter, sighing, and coughing.
Dia is free for commercial and non-commercial use under the Apache 2.0 license. One drawback of this model is that it supports only English. This might be of concern for businesses looking to build solutions for multiple languages.
Spitch TTS
Spitch started with the charge towards building quality language models for African languages and has now built text and speech models for Yoruba, Igbo, Hausa, and English since its launch in 2023. Spitch’s speech generation module supports these four languages with unique voices for each language and is actively working towards supporting more voices and languages soon.
With the fading representation of African languages in the digital system, this is a much-needed cause to support. Our TTS systems are specifically engineered to capture the nuances in spoken African languages. We also support live speech generation through our streaming options. Get started with our speech generation service here.
Core Criteria for Speech Generation in Agentic Systems
Having considered some of the top speech generation models, it is important to choose the right speech generation model for your agentic AI task. Here are some factors worth considering when selecting speech generation models for your agentic AI systems.
Naturalness & Human-likeness: People are more likely to resonate with voices that closely mimic human prosody, tone, and emotional nuance. This fosters deeper engagement and trust, leading to higher customer satisfaction scores and increased conversion rates. Leading industry surveys identify naturalness as the primary driver of user satisfaction in TTS investments, with enterprises reporting up to a 20 % uplift in engagement metrics when adopting higher-quality voices.
Contextual Adaptability: Agents that dynamically adjust delivery by modulating tone, pacing, and content based on dialogue state and user intent, reduce friction and resolution times. Such models could cut customer support costs by as much as 30 %. By leveraging context-aware pipelines, businesses can preemptively surface relevant information, provide personalized marketing, lowering repeat inquiries, and boost first-contact resolution rates.
Latency & Throughput: Real-time responsiveness is critical for customer satisfaction. Every 100 ms reduction in response delay correlates with a 5 % increase in user retention. High-throughput TTS pipelines ensure they can handle peak loads without degradation and avoid costly downtimes. Optimizing for low latency and high throughput can yield operational cost savings of 30-40 % by reducing over-provisioning and improving resource utilization.
Scalability & Cost: Scalability and cost are also important factors worth considering when selecting the right TTS model. How elastic is the TTS service you want to use? Does it allow for elastic scaling? These are some of the questions you might want to ask. Also, consider whether the services pricing model is flexible or not.
Meet Spitch Agents: Our Agentic AI Service
Spitch Agents is a voice-operated agentic software that enables users and businesses to develop and consume agentic AI solutions powered by Spitch. It offers businesses and entrepreneurs a plug-and-play platform where businesses can plug in their custom information and have agents tailored to their use cases without breaking a sweat.
Our key selling points are:
Multilingual support: Reach a wider global audience and connect with customers in their preferred language, including Yoruba, Igbo, Hausa, and English, without the high cost of translators. This boosts customer satisfaction and opens doors to new markets, giving your business a significant competitive advantage.
Customizable AI Agents: Get AI assistants tailored specifically to your business, whether for answering customer questions, explaining products, providing personal support, or generating reports. Connect your data, and these agents will work precisely how you need them to, improving efficiency and service.
Automated data collection: Effortlessly gather valuable insights from customer interactions on your site to understand their needs better. By seeing the most common questions, you can proactively address concerns and improve your offerings, leading to happier customers and smarter business decisions.
Intuitive design: Our platform is designed to be incredibly easy for anyone to use, with no technical skills required. This means your team can quickly adopt and benefit from our powerful features without complex training, saving time and effort.
Getting Started with Spitch Agents
Head over to our website here to try out Spitch Agents. Once you are signed in, select your language and preferred agent and have at it! If you would like to develop a more personalized solution for your business, click the Contact Sales button to schedule an appointment with us.
Concluding Remarks
In today’s fast-paced digital landscape, the evolution of speech generation has fundamentally transformed how AI agents perceive, decide, and interact. The world is currently moving towards voice-operated systems and you don’t want to limit the reach of your Agentic AI service by limiting it to text.
You could either spend a lot of time and resources building your voice-agentic AI from scratch and, or choose Spitch Agents. Our AI Agents are customizable with custom voices available on request. This means businesses can simply plug in their data, and easily scale high-quality agents for their needs. If you favour the later option, head to Spitch Agents to schedule a call with us.
