Hamming is a quality assurance and trust platform for voice and chat AI agents, with the core goal of testing agents before launch, conducting red team exercises on potential risks, and continuously monitoring every call in the production environment, turning failures into regression tests rather than customer complaints.
Purpose Hamming covers three stages in the agent lifecycle: pre-launch testing, risk red teaming, and production monitoring. It is suitable for teams with high reliability requirements, including high-growth startups, banks, and healthcare technology companies in regulated environments.
Main capabilities
- Pre-launch testing: can run conditions that cannot be arranged with real human callers, thousands of concurrent runs, completing validation before external users come into contact with the agent. Supports automatically generating scenarios from system prompts, and scoring with more than 50 built-in metrics. Covers accents, interruptions, background noise, DTMF, and IVR trees. Supports 50K+ concurrent calls, can be integrated into CI/CD, and prevents failed builds from going live.
- Red team exercises: provides adversarial suites compiled from a large number of production deployment patterns, with no need for custom prompts. Covers prompt injection, jailbreaks, PII leakage, policy violations, and social engineering. Each finding generates a reproducible failing test and is rerun on every release.
- Production monitoring: monitors live traffic, detecting drift, unfulfilled commitments, and compliance risks while calls are still in progress. Provides 7×24 health checks and alerts humans before customers notice. Supports native OpenTelemetry observability. Can turn production failures into permanent regression tests with one click.
How to use Agents can be imported from Vapi, Retell, ElevenLabs, or any orchestration framework, by pasting prompts or connecting via API; the company says integration can be completed in 10 minutes. The platform analyzes the prompt and automatically generates hundreds of test scenarios, including happy paths, edge cases, adversarial inputs, accent variations, and background noise conditions, with no need to manually write test cases.
Quality measurement dimensions The platform measures voice agent quality across three dimensions: conversation metrics (turn latency, interruptions, time to first word, talk-listen ratio, etc., tracked in both test and production calls), expected outcomes (whether required information is collected, an appointment is completed, or the customer's issue is resolved), and compliance guardrails (safety violations, prompt injection attempts, and policy violations, auditable per call by rule).
Health checks Every few minutes, replays a set of golden calls to detect drift or interruptions caused by model changes, infrastructure incidents, or prompt regressions, and sends alerts via email and Slack.
Multimodal Tests voice and chat agents simultaneously, using unified evaluation, metrics, andproduction monitoring. The same set of test scenarios, the same dashboard, and the same evaluation framework, with no need to prepare separate tools for voice and chat.
Security and compliance Maintains SOC 2 Type II controls to support enterprise-level data protection, access control, and operational resilience requirements. Supports HIPAA-aligned workflows for testing and monitoring voice agents that handle protected health information (PHI), and can sign business associate agreements (BAAs).
Use cases
- Batch scenario testing and CI/CD gates before voice agents go live
- Adversarial testing of agents for prompt injection, jailbreaks, PII leakage, and more
- Real-time monitoring, drift detection, and human alerts for production calls
- Compliance audits and health checks in regulated industries such as healthcare and finance
- Unified quality assurance covering both voice and chat agents
Limitations The materials do not provide specific pricing, plans, free trial conditions, precise integration step details, the specific number of supported languages and accents, specific values for concurrent test calls, etc.; none of these are currently provided.
