Hamming

Hamming AI is an automated all-in-one experimentation and production platform for AI voice agents. It enables teams to test, optimize, and monitor AI voice assistants across development and production environments, ensuring reliable call quality, compliance, and high user satisfaction. The platform supports automated testing with thousands of simulated calls, prompt management, prompt optimization, production call analytics, and domain-specific capabilities (appointment scheduling, drive-through, customer support, follow-ups, personal assistants, coaching, tutoring, etc.). It emphasizes speed-to-value, reducing manual testing effort by orders of magnitude, and provides governance features for prompts and prompts syncing with voice infrastructure providers.

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How It Works

• Built to handle high-stakes domains where mistakes lead to churn or regulatory risk.
• Create and manage thousands of concurrent simulated calls to stress-test and debug voice agents.
• Use LLM judges and analytics to score call quality and flag issues before deployment.
• Integrate with diverse voice infra providers and allow platform-agnostic hooks to simulate conversations and log traces.
• Convert real-world calls and traces into test cases to continuously improve a golden dataset.

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Key Features

• End-to-end platform from development to production for AI voice agents
• Automated AI voice agent testing with thousands of concurrent calls
• Prompt management: store, version, and sync prompts with voice infrastructure providers
• Prompt Optimizer & Playground: automatically generate optimized prompts and test outputs
• Production Call Analytics: actively track, score, and flag issues in production
• Domain-specific capabilities: appointment scheduling, drive-through, customer support, follow-ups, personal assistants, coaching, tutoring, and more
• Multi-language support: agents can call in multiple languages
• Platform-agnostic integration: hooks to simulate conversations across various providers
• Efficiency gains: significantly reduces manual prompt engineering effort and testing time

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What You Can Build

• AI Appointment Scheduling: handle bookings, cancellations, and rescheduling across time zones
• AI Drive-through: manage complex orders with constraints like dietary restrictions and substitutions
• AI Customer Support: 24/7 high-quality support with escalation to human agents when needed
• AI Phone Followups: deliver critical information accurately and empathetically
• AI Personal Assistant: manage calendars, tasks, travel itineraries, and preferences
• AI Coaching and Tutoring: simulate diverse learning scenarios and assess explanations
• Multilingual call capabilities: operate in languages including English, French, German, Hindi, Spanish, Italian, and more

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How to Use

1. Define your voice agent and connect your preferred voice infra providers.
2. Create simulated conversations (thousands of calls) to test prompts, function calls, and model behavior.
3. Use the Prompt Optimizer to generate improved prompts and run them through the Playground to evaluate outputs.
4. Deploy to production and use Production Call Analytics to monitor usage, score calls, and automatically generate test cases from traces.
5. Iterate by updating prompts, configurations, and test datasets to continuously improve accuracy and reliability.

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Safety and Compliance Considerations

• Designed for high-stakes domains; ensure proper consent and privacy practices for real-world data.
• Use generation and testing data responsibly; implement escalation to humans when confidence is low.
• Ensure compliance with regulatory requirements relevant to your industry (HIPAA-like considerations when handling sensitive information).

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Audience

• AI product teams building voice agents
• QA and testing teams validating voice call quality
• Ops teams responsible for production monitoring and incident response
• Prompt engineers and ML engineers working on voice AI systems

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Key Outcomes

• Faster time-to-production for AI voice agents
• Higher call quality and user satisfaction
• Reduced manual testing effort and faster iteration cycles
• Governed and scalable prompt management across customers and deployments

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Sample Workflows

• Run automated stress tests with thousands of concurrent calls to identify edge-case failures
• Use the Prompt Optimizer to tailor prompts per customer or use-case and compare results in the Playground
• Transform production traces into test cases to build a robust golden dataset for future testing

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Safety and Legal Considerations

• Ensure user consent and disclosure where required when deploying and testing voice agents
• Avoid exposing sensitive data in logs or test traces; apply data minimization and privacy protections
• Comply with applicable laws and sector-specific regulations when handling voice data