Conversational Agents

In 2025, revenue growth was strong, but churn among enterprise customers stood out a key, organizational pain point. Small SMB customers relied on very basic, agentic experiences that could handle a wide variety of scenarios.

Conversely, after speaking with customers and customer-facing teams, we found enterprises needed extremely detailed and structured agentic AI experiences to handle very specific business verticals and operations.

Gail agents are comprised of a voice/persona, behavior and knowledge, tailored for the channels and tasks it will be deployed to.

Those agents can then be deployed across various channels like web-chat, SMS, or WhatsApp with a script to carry out conversations that are built for desired outcomes and objectives like renewing insurance policies, collecting payments, or being a support line.

Users can create their own custom agents using generative AI or browse agents already built for certain tasks or lines of work from an agent specific page.

Customers have the ability to easily change how an agent sounds, and how the agent interacts with customers in different conversational scenarios.

Different speech to text models work differently, so we use simple terms to explain how and when to use different features allows for customers to deploy the best agents

With the tap of a button, users can actually have real conversations with their agents, simply using their device microphone and the browser.

When AI agents have real conversations with real people, things don’t always go as planned so we built a suite of testing tools to allow for complex simulations to catch errors and allow for optimization before launch

While Gail does send automatic reports and create tasks for necessary followups and to-dos, sometimes users want to go back and actually view the details of a conversation Gail had with a customer. From this screen, users can easily understand the overview of a conversation or see the exact transcript as well.