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September 15, 2023

Using Voice APIs to Streamline Your Business



A voice API can transform your business. Once integrated into your company’s applications, AI phone calls and other personalized outreach can build meaningful relationships between you and your customers. Suddenly, every touchpoint from inbound sales to follow-ups can be fully automated by a friendly, empathetic, and helpful AI.

In this guide, we’ll start by defining voice APIs and explaining how they work. We’ll learn about the underlying models that power voice applications, including text-to-speech models, large language models, and speech-to-text models. After, we’ll learn about the business applications of voice calling, and how software developers are leveraging AI phone calls to generate more revenue for their companies. Lastly, we’ll cover how you can integrate a voice call API into your applications right now, using Bland, the communications platform for AI phone calling.

Programmable Voice API: How AI Phone Calls Work

To build a voice chat application programming interface (API), a voice API provider must leverage three distinct models. The first model transcribes the audio of the speaker (speech-to-text) using a speech API. The second model - a large language model - reads the transcribed audio and uses the context of the entire conversation to formulate a response. The third model, speech-to-text, outputs the response as audio, back to the speaker. The result: a phone call where an AI speaks to a human.

Depending on the API, you’ll notice differences in voice capabilities, including multi-language offerings, live translation, and even custom voice clones. Additionally, some APIs will offer customization options like providing the AI a custom prompt to determine its conversational style, plus passing additional information about the speaker to improve the overall experience.

Integrating with Bland AI

At Bland AI, we made our API dead simple to integrate. With just ten lines of code, you can integrate AI phone calls - for any (ethical) purpose - and handle both inbound and outbound calls. The use cases range from customer service to inbound sales to reactivation. Pretty much whatever you need - Bland can do it.

Visit our documentation to see exactly how you can use Bland’s AI voice call API.

Benefits of using Voice APIs

There are many benefits to building a voice application for your customers. Great voice applications like outbound calling and customer service enable you to better engage your customers. Building personal relationships, using your best voice, and enabling advanced features for all your customers.

Imagine if the next time a customer visited your website: an integrated voice solution could enable them to easily navigate by speaking. Similarly using AI phone numbers could enable your company to instantly answer customers’ questions, enabling them to make purchases faster.

Such improvements in voice technology both cause better experiences for customers while also enabling companies to make additional revenue. It’s a win-win that causes many enterprises to seriously consider adding voice-calling capabilities to their applications.

Industry-specific use cases

Healthcare, for example, is an industry where voice messages are especially powerful; they enable telehealth companies to prevent no-shows to appointments. Or reschedule on the phone. Additionally, AI voice APIs enable older enterprises to remove their interactive voice response (IVR) systems. Those systems are the same ones that force people to wait on hold for hours on end. Imagine instead that the next time you call insurance, a human answers the phone. You instantly get the answers to the questions you have. Which enables you to be healthier, faster.

That’s the power of Voice AI: anyone can quickly get the information they need, always in a personalized manner.

Challenges of using Voice APIs

Most enterprises are hesitant to leverage voice APIs for a few reasons. Brand is a big one: if an AI representing your company says something offensive, mean, or unhelpful to a customer, how will that affect customers’ perceptions of your company? As a result, most brands require extensive observability into every interaction the AI has with their customers, giving them full visibility into every conversation, and enabling them to flag and make improvements to the AI’s prompt.

Another challenge many enterprises face when adding AI voice chat is knowing how to make the AI good at conversation. By default, large language models lack a contextual understanding of how normal people speak during conversation. This has to do with the way most LLMs are trained. Unfortunately, though, the result is most companies are hung out to dry because they don’t know what the right prompts are. This creates a burden for the voice call platforms: to get the right prompts and supply them to customers.

Maintaining conversational quality

Another consideration for many enterprises is quality. Imagine your AI speaks to people on the phone but sounds robotic. That experience will probably feel unpleasant. Customers may become frustrated and want to speak to a human. The only way AI can replace humans is when the quality becomes incredibly high.

At Bland AI, our team has solved all the above problems. Our AI is incredibly conversational. We offer full observability into every interaction. And we built our systems to be incredibly secure and keep our customers’ data safe.

To sign up for a developer account and start using Bland’s API, visit the Bland developer portal.


Voice APIs will transform both your business and every underlying industry in the world. Advancements in dynamic caller ID, recorded audio files, and third-party apps will enable a new wave of innovations in customer experience and engagement.

To learn more about how you can transform your company and the way you connect with customers, sign up for Bland’s AI phone calling platform. Our API makes it easy to configure inbound and outbound phone calls with AI.

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The Latest, from Bland

Serving sectors including real estate, healthcare, logistics, financial services, alternative data, small business.