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Glossary · AI & Agents

Hamming AI

Definition: Hamming AI is an automated testing and monitoring platform for voice and chat agents. It generates test scenarios from an agent's prompt, runs high volumes of concurrent simulated calls to surface bugs, and tracks live calls for hallucinations, latency, and regressions. API-first, it plugs into CI/CD pipelines to block faulty prompts before they reach production.

Official source: Hamming AI

Overview

What Hamming AI is

Hamming AI is a quality-assurance platform for voice and chat agents, covering automated testing, call analytics, and production monitoring. Instead of manual call-by-call QA, it programmatically exercises an agent at scale and reports where it breaks.

The company went through Y Combinator's S24 batch and pioneered automated scenario generation for voice agents, meaning it can propose test cases directly from an agent's prompt rather than requiring teams to script every scenario by hand.

How it works

Hamming reads your agent's prompt and generates test scenarios, then places large numbers of concurrent simulated phone calls that mimic real conditions such as accents, background noise, and interruptions. It compresses what would be hours of manual dialing into a test report in minutes.

In production, it tracks live calls for hallucinations, latency, and performance degradation, flagging issues in real time. Because it is API-first, tests can be triggered programmatically and wired into CI/CD to gate deployments.

Where it fits in a voice-AI stack

Hamming AI sits in the testing, evaluation, and monitoring layer, independent of the framework or telephony you use to build the agent. It works alongside agent platforms and speech services rather than replacing them.

It competes most directly with Coval; both simulate calls and monitor production, but differ in workflow emphasis. Teams should compare scenario-generation quality, concurrency limits, evaluation flexibility, and CI/CD integration against their own requirements.

Where we use it

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How our team puts Hamming AI to work in real projects.

FAQ

Hamming AI — common questions

What is Hamming AI used for?

Hamming AI is used to test and monitor AI voice and chat agents automatically. It generates test scenarios from the agent's prompt, runs many concurrent simulated calls to find bugs, and monitors live production calls for issues like hallucinations and latency.

Does Hamming AI integrate with CI/CD pipelines?

Yes. Hamming AI is API-first, so tests can be triggered programmatically and integrated into CI/CD pipelines. This lets teams automatically run regression tests and block faulty prompts from reaching production.

How does Hamming AI compare to Coval?

Both are voice-agent testing and monitoring platforms with overlapping features. Hamming AI emphasizes auto-generating scenarios from your prompt and high-volume concurrent call testing, while Coval emphasizes simulation plus a human-review layer that produces reusable evals. Compare both for your use case.

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