CheckOps
Hamming
Hamming tests, red-teams and monitors voice and chat AI agents: simulated calls before launch, failed calls rerun as regression tests, and production monitoring.
- LLM & agent evaluation
- AI-enabled testing
- AI testing agents
- Security Testing
- SaaS
- Paid
- End-to-end & functional
- Security testing
- Release & CI gates
- Production monitoring & observability
Latest public signals
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Introduction
Hamming calls itself “the security layer for voice and chat agents”. The official site describes three stages: test before launch, red-team what could go wrong, and monitor every production call.
Before launch, agents are red-teamed against prompt injection, jailbreaks and social engineering. On every release, failed calls are rerun as regression tests. In production, every call is monitored for leaks and policy breaks. The site lists SOC 2 Type II, a HIPAA BAA and GDPR DPA, SSO, RBAC and single-tenant deployment.
Features
- Simulated calls: Automated test callers exercise voice agents.
- Red teaming: Prompt injection, jailbreak and social-engineering probes.
- Regression from failures: Failed calls become regression tests.
- Production monitoring: Every call checked for leaks and policy breaks, with alerts.
- Scale: The site cites 10K+ voice agents tested and 50K+ concurrent test calls; vendor figures.
- Enterprise security: SOC 2 Type II, HIPAA BAA, SSO, single-tenant option.
Pros
- Voice-specific: Purpose-built for phone and voice agents.
- Closes the loop: Production failures feed regression tests.
- Security focus: Red teaming is core, not an add-on.
- Compliance: Healthcare-ready options.
- Human agreement: Claims 95%+ agreement with human evaluators; vendor figure.
Cons
- No public pricing: Demo-led; see site.
- Narrow scope: Voice and chat agents only.
- Hosted service: Calls and recordings flow through Hamming.
- Vendor metrics: Scale and accuracy figures are self-reported.
- Simulations cost: Large concurrent call tests are a paid service.
Usage and Links (Example)
Request a demo, connect your voice or chat agent’s phone number or endpoint, define scenarios and personas, run simulated calls, and turn failures into regression tests. Enable production monitoring to alert on leaks and policy breaks.
Resources:
Pricing
Hamming does not publish prices. See site or request a demo.
Recommended for?
- Teams launching voice agents in support, healthcare or finance.
- Security and compliance teams responsible for conversational AI.
- Product teams wanting regression tests from real failed calls.
- Not a fit for non-conversational apps.
Conclusion
Hamming focuses on testing and securing voice and chat agents across launch, release and production.
Its value is highest where a single bad call carries real risk.
Alternatives
Other tools on CheckOps that cover similar ground. Open a page, or compare one with Hamming side by side.
CCovalCoval is a voice AI testing and evaluation platform that simulates conversations, observes production calls and adds human review to make voice agents deployment-ready.Compare with Hamming
CCekuraCekura is automated QA for voice and chat AI agents: simulations, evaluations, red-teaming and production call monitoring, with a loop that turns failures into evals and fixes.Compare with Hamming
LLangWatchLangWatch is an Apache-2.0 open-source platform for agent observability, evals and agent simulation testing, with prompt management, red-teaming and voice-agent testing.Compare with Hamming
PPromptfooPromptfoo is an open-source CLI for LLM evals and red teaming. The community tool is free; enterprise features are quoted.Compare with Hamming
GGiskardGiskard offers an Apache-2.0 open-source library for evals, red teaming and test generation for AI agents, plus a commercial Hub for agent red-teaming, evaluation and guardrails.Compare with Hamming
Ggarakgarak is NVIDIA's Apache-2.0 LLM vulnerability scanner that probes models and dialog systems for hallucination, data leakage, prompt injection, toxicity, jailbreaks and more.Compare with Hamming