Hamming AI

Hamming AI, a product from Lilac Labs, is designed to revolutionize the testing process for AI voice agents, emphasizing speed and efficiency. Founded by industry veterans Sumanyu and Marius, with experience at companies like Citizen, Tesla, and Anduril, Hamming AI targets the critical need for rapid iteration in the development of large language model (LLM) voice agents. By automating the testing of these agents, Hamming AI allows users to conduct hundreds of simultaneous calls, identifying bugs significantly faster than traditional manual methods.

The platform excels in creating Character.ai-style personas and scenarios, setting the stage for intricate testing environments that mimic real-world interactions. Hamming AI’s core technology seamlessly integrates with existing systems, using sophisticated analytics to pinpoint areas of improvement. This is crucial for applications like drive-through voice agents in fast food chains, where order accuracy and reliable handling of customer requests are paramount.

With a focus on industries requiring high reliability and performance, Hamming AI is ideal for businesses looking to streamline their voice agent refinement process. Whether dealing with complex customer scenarios or integrating with high-stakes systems, this tool offers a comprehensive solution to enhance both development and operational phases of AI voice deployment.

Hamming AI offers a platform that automates the testing of AI voice agents, making the process 100 times faster than manual methods. Here are some of its key features:

Core Functionalities

Hamming AI enables the automatic testing of LLM voice agents by simulating conversations with varied personas and scenarios. Users can create Character.ai-style personas and run hundreds of simultaneous phone calls to identify and fix bugs in the voice agents. This allows voice agents to be evaluated for their ability to manage issues like background noise, silences, or interruptions.

Data Handling and Analytics

The platform provides detailed analytics to pinpoint areas of improvement. Each conversation is scored using deterministic checks and LLM judges that are specific to the problem domain, such as order accuracy and conversational tone. This scoring helps track quality metrics in production, allowing for ongoing evaluation and refinement of the voice agents.

Customization Options

Users can create diverse user personas and scenarios that cover the expected conversation space, tailored to their specific needs. This flexibility supports various applications, such as ensuring order accuracy in drive-through scenarios for fast food chains.

Target Audience and Use Cases

Hamming AI is designed for companies building voice agents who require reliable systems. The platform is especially beneficial for applications where customer interactions are critical, such as in fast food services, where handling dietary restrictions or distracted customers accurately is essential for success.

These features collectively make Hamming AI a powerful tool for developing robust and efficient AI voice agents.