Prompt optimization, automated voice testing, monitoring and more.
Test your AI voice agent against 1000s of simulated users in minutes.
AI voice agents are hard to get right. A small change in prompts, function call definitions or model providers can cause large changes in LLM outputs.
We're the only end-to-end platform that supports you from development to production.
Teams currently spend hours testing their voice agents by hand. Use our voice characters (see demo) to create 1000s of concurrent phone calls to your voice agents and find bugs.
This is 1000x more efficient than testing your voice agents by hand.
Featured in our YC launch here.
For B2B teams, each of your customers requires a slightly different prompt.
You can store, manage, version and keep your prompts synced with voice infra providers from Hamming.
Featured in our YC launch here.
Writing prompts by hand is slow and tedius. Use our prompt optimizer (free to try) to automatically generate optimized prompts for your LLM.
Use our prompt playground to test LLM outputs on a dataset of inputs. Our LLM judges the quality of generated outputs. Save 80% of manual prompt engineering effort.
Featured in our YC launch here.
Go beyond passive monitoring. We actively track and score how users are using your AI app in production and flag cases using LLM judges that need your attention.
Easily convert calls and traces into test cases and add them to your golden dataset.
Featured in our YC launch here.
Co-Founder & CTO @ Lilac Labs
We automate the person taking orders at the drive-thru with voice. Order accuracy is extremely critical for our customers. Getting an order wrong (i.e., missing allergies) means significant financial loss.
Hamming helps us simulate 1000s of customer calls (dietary restrictions, allergies, large group orders, etc.) and find gaps in our system in minutes. This gives us a huge peace of mind and clarity on where we need to improve.
Hamming is an essential part of our infra that directly unlocks revenue.
We're experts in supporting companies tackling high-stakes domains where making mistakes leads to high churn or regulatory consequences.
Building AI agents is a team effort. Hamming is built to support cross-team collaboration.
Create scenarios and characters for your agents that test the entire conversational space.
For each experiment, track your hypothesis, proposed changes and learnings.
Override AI scores. Every override aligns the AI judge with your preferences.
Search across all traces and quickly root-cause why your AI system produced a particular answer.
AI pipelines are non-deterministic. You can run multiple runs for the same experiment - visualize performance distributions and isolate flake tests.
Share datasets, experiment results and traces with teammates.
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