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Hamming automates the QA of voice agents. (both pre-deployment testing and post-deployment analytics) Making voice AI agents reliable is hard. A small change in prompts, function call definitions, or model providers can cause large changes in LLM outputs. We have a proven track record of helping enterprises win with AI. Sumanyu (CEO) previously helped Citizen (safety app) grow its users by 4X and grew an AI-powered sales program to 100s of millions in revenue/year at Tesla. Our eng team ranks #1 on https://workweave.ai/

1. You explain your problem. 2. Kater identifies the most important data questions to ask. 3. Kater writes the code. 4. You get insights in seconds rather than weeks. Kater.ai flips the script on enterprise analytics by making every user an expert analyst. It uses a continuous classification engine to turn a single business question into a contextualized package of questions that is specific to your needs. Kater puts the power of data into the hands of business experts while ensuring they use trusted data that is specific to their persona. No more waiting for data analysts. No more wasted time on analysis misfires and rework. Yvonne was a data engineer and analyst who built the entire data stack at CREXi. Robin led engineering in Microsoft. Data is the new oil. Companies are data-rich, insight-poor. We're helping companies become insight-rich. This is the future of data.