Regal 首次亮相 Goal Oriented Agents 在每个呼叫中设置一个演员和一个导演模型
企业语音人工智能公司Regal Voice Inc. 今天在其平台上添加了Goal Oriented Agents，使得企业利用它们来定义一个呼叫必须完成什么，并提供两个AI模型来分割到那里的工作。
新的agents旨在解决一个问题 Regal 称显示在汽车保险声称等电话中上升，其中报告事故的人倾向于解释发生了什么，在哪里和谁参与了一次事故。 Agents 建立在条件逻辑上，经常为呼叫者已经给出的细节回圈，只是让每个字段都得到填充。 将整个agent建在一个提示上
Goal Oriented Agents在每个呼叫上都设置了两个模式。 Regal称他们为演员和导演，两人在打电话者停止交谈后立即开始工作。 演员，一个更小更快的模型调用对话，立刻回答。 在幕后，导演检查现阶段的目标是否已经实现，并且可以将呼叫转移到一个新的阶段，给演员提供新的指示。
企业从目标节点中建立agents，每个节点都列出在节点结束时要达到的目标以及任何先到的前提条件。 预订回调可以算作这些目标之一。 agent在采取行动前必须先确定一个先决条件，例如打电话者的出生日期。 Regal 称也可以写成普通语言条件
导演在每个回合后都会回顾进展情况，所以一个答案可以同时勾掉几个项目。 Regal的汽车保险索赔样本中有一个叫Dan的打电话者在第一个留言中描述了车辆损坏、照片证据和伤害。 三者皆得标为所收，agent直指其名。 因此演员的下一个问题是他在哪里。
Regal 称复合摄入量和资格调用量是它为agents所见到的最强用途之一。 公司命名为医疗保障入学、路边援助和抵押贷款资格，符合《健康保险可携带性和问责法》的医学摄入是另一套。
Google有限责任公司、AAA和丰田汽车公司是该公司服务的200多个企业之一。 Five9股份有限公司的联络中心平台客户通过8月的整合获得了Regal的语音agents.
Regal是一个风险资本支持的创业企业，迄今为止拥有8300万ZQZ. 其中包括2024年10月的4 000万美元回合。
图片：Regal
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Regal debuts Goal Oriented Agents, putting an actor and a director model on every call
Enterprise voice artificial intelligence company Regal Voice Inc. today added Goal Oriented Agents to its platform, enabling businesses using them to define what a call has to accomplish, and providing two AI models that split the work of getting there.
The new agents are aimed at a problem Regal says shows up in calls such as auto insurance claims, in which someone reporting an accident tends to explain what happened, where and who was involved in one go. Agents built on conditional logic often circle back for details the caller already gave, just so each field gets filled. Building the whole agent on a single prompt keeps the conversation open, and in Regal’s view it leaves business processes only loosely followed.
Goal Oriented Agents put two models on each call. Regal calls them an actor and a director, and both start work as soon as the caller stops talking. The actor, a smaller and faster model tuned for dialogue, replies right away. Running behind it, the director checks whether the goals for the current stage have been met and can move the call to a new stage with fresh instructions for the actor.
Businesses build the agents out of goal nodes, each listing the goals to be met by the end of the node and any prerequisites that come first. Booking a callback can count as one of those goals. A prerequisite is something the agent has to establish before it can act, such as the caller’s date of birth. Regal said those can be written as plain-language conditions too, for example “the caller mentioned a death in the family.”
The director reviews progress after every turn, so one answer can tick off several items at once. Regal’s sample auto insurance claim has a caller named Dan describing the vehicle damage, photo evidence and injuries in his first message. All three get marked as collected, and the agent goes straight to his name. Once it has that, the director sees location and policy number are still missing, so the actor’s next question is where he is.
Regal said complex intake and qualification calls are among the strongest uses it has seen for the agents. The company named Medicare enrollment, roadside assistance and mortgage qualification as uses the design opens up. Medical intake that complies with the Health Insurance Portability and Accountability Act is another.
Google LLC, AAA and Toyota Motor Corp. are among the more than 200 enterprises Regal says it serves. Customers of Five9 Inc.’s contact center platform gained access to Regal’s voice agents through an integration in August.
Regal is a venture capital-backed startup that has raised $83 million to date. That includes a $40 million round in October 2024.
Image: Regal
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