Hamming AI: Automated Testing for Reliable Voice Agents

Building reliable AI voice agents has always been a complex challenge. The need for diverse, accurate, and context-sensitive responses often leads to repeated cycles of manual testing and optimization, which is slow and resource-intensive.

Making Voice Agents Reliable

Voice agents must handle an enormous variety of user interactions, adapting seamlessly to different scenarios. However, ensuring this level of reliability requires extensive testing, which is traditionally done manually.

A small change in prompts or model configurations can drastically affect the performance, resulting in an exhausting cycle of bug fixing and testing.

Most teams currently follow a workflow where they manually call their voice agents to detect bugs, tweak their prompts or models, and call again to check for improvements.

This process is tedious, prone to human error, and becomes a bottleneck for achieving consistent performance.

Scalable Automated Testing

Hamming AI provides an automated platform that tackles this issue head-on by simulating real-world interactions using AI-driven personas. These personas emulate actual users, enabling Hamming AI to run thousands of concurrent tests on voice agents.

This ensures that agents can handle diverse scenarios and unexpected inputs more reliably. For instance, Hamming has been used by an AI-driven drive-through startup to achieve 99.99% order accuracy by simulating complex customer scenarios.

Features and Innovations

Character AI for Voice Testing: Hamming AI's platform creates hundreds of virtual characters that interact with the voice agent, testing its capabilities in various real-life situations, such as ordering food or canceling an appointment. This simulation-driven approach makes testing 100 times faster and significantly more thorough than manual testing.

Prompt Optimization and Monitoring: The platform also offers tools for prompt management, active monitoring, and scenario-based debugging. By storing and optimizing prompts, Hamming ensures they remain in sync with changing voice infrastructure needs, helping teams adapt quickly when updates are required.

Active Production Monitoring: Beyond development, Hamming AI continuously monitors voice agents in production. It logs and tags production calls in real time, flagging issues that require engineering attention. This approach helps teams maintain high-quality customer interactions without the need for constant manual checks.

Hamming AI has proven highly effective in industries like fast food and customer service. By automating both testing and quality assurance, it not only speeds up the development cycle but also ensures that voice agents perform accurately in high-stakes environments.

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Company Overview

Hamming AI is an enterprise technology company focused on automating the testing and optimization of AI voice agents. Headquartered in San Francisco, California.

Hamming AI has successfully secured funding from top-tier venture capital firms, including backing from Y Combinator.

The Team

Sumanyu Sharma, Co-Founder & CEO: Sumanyu is a seasoned leader with experience growing user bases and revenue for leading tech companies. Before founding Hamming AI, he helped Citizen, a safety app, grow its monthly active users by 4x and scaled an AI-powered sales program at Tesla to hundreds of millions in revenue annually. Sumanyu brings deep expertise in AI, data science, and growth strategy to Hamming AI.

Marius Buleandra, Co-Founder & CTO: Marius has extensive experience in engineering and data infrastructure, having previously worked as an Engineering Manager at Anduril and as a founding engineer at Spell, an MLOps startup acquired by Reddit. His expertise in building scalable systems and infrastructure is instrumental in developing Hamming AI's robust automated testing platform.