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HappyRobot

@HappyRobot • 2,724 subscribers

Achieving Enterprise Superintelligence by putting agents to work. https://t.co/2JCeAmsEoY

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HappyRobot has been famous for our voice experience for a long time. You want to know our secret? We have always built for the limiting factor - solving for the incremental details that determine whether a voice, an agent, can actually have a natural conversation.

HappyRobot has been famous for our voice experience for a long time. You want to know our secret? We have always built for the limiting factor - solving for the incremental details that determine whether a voice, an agent, can actually have a natural conversation.

23,473 次观看 • 1 个月前

We're extremely excited to announce our $15.6M Series A led by a16z! We're building the AI communications platform for logistics. Go check out our new website and book a demo: You might be surprised who calls you back ;)

We're extremely excited to announce our $15.6M Series A led by a16z! We're building the AI communications platform for logistics. Go check out our new website and book a demo: You might be surprised who calls you back ;)

97,158 次观看 • 1 年前

Your agent should meet its adversary before it meets your customers or partners. Introducing Adversarial Agents: AI-powered mock users that try to break your agent by simulating hypothetical hostile scenarios to cover all possible 'unhappy' paths. Prompt injection. Topic derailing. Instruction overrides. Every angle that a bad actor or a frustrated caller might try or edge cases that may come up - test any and all possible scenarios before the agent goes live. Plus, get a full audit report measured against expected behavior showing exactly what held and what broke, with correction suggestions for each failure, so you can deploy with confidence. Red-team your AI agents before you ship them.

Your agent should meet its adversary before it meets your customers or partners. Introducing Adversarial Agents: AI-powered mock users that try to break your agent by simulating hypothetical hostile scenarios to cover all possible 'unhappy' paths. Prompt injection. Topic derailing. Instruction overrides. Every angle that a bad actor or a frustrated caller might try or edge cases that may come up - test any and all possible scenarios before the agent goes live. Plus, get a full audit report measured against expected behavior showing exactly what held and what broke, with correction suggestions for each failure, so you can deploy with confidence. Red-team your AI agents before you ship them.

10,826 次观看 • 1 个月前

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