Regal出道于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，让企业使用它们来定义一个呼叫必须完成什么，并提供两个AI模式来分割到达该站的工作。
新的agents旨在解决一个问题 Regal 称显示在汽车保险等电话中上升声称，其中报告出事故的人倾向于解释发生的事情，在哪里和谁参与了一次去。 Agents建立在条件逻辑上，经常回回圈，以了解呼叫者已经给出的细节，只是使每个字段都得到填充。 将整个agent建在单一的提示上
Goal Oriented Agents在每次呼叫中都设置了两个模式。 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，马上回答。 在幕后，导演检查目前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。
企业从目标节点中构建出agents，每个节点都列出在节点结束时所要达到的目标以及任何先来的先决条件。 预订回调可以算作这些目标之一。 一个先决条件是agent在采取行动之前必须确定的东西，例如打电话者的出生日期。 Regal 称也可以写成普通语言条件
导演在每次转会后都会回顾进展情况，因此一个答案可以同时勾出几个项目。 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、相片证据和伤害。 三者被标记为所收，而agent直取他名。 因此演员的下一个问题就是他在哪里。
Regal 称复合摄入量和资格调用量是它所见到的agents最强的用途之一。 公司命名为医疗保健计划注册、路边援助和抵押贷款资格，因为其设计是开放的。 符合《健康保险可携带性和问责制法》的医学摄取是另一种做法。
Google有限责任公司、AAA和丰田汽车公司是该公司服务的200多家企业之一。 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是一个由风险资本支持的创业企业，迄今为止拥有8 300万ZQZ. 这包括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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