大理石 Cognition 融资 375M 其AI agent工人观看和学习人们的工作方式
人工智能agents如今已经成为企业的一分钱
这才是名为Marble Cognition的创业者在筹集375万美元种子前资金，该轮由Heartcore和Seedcamp领衔主演，看到了天使投资者的参加，其中包括来自麦肯锡公司(McKinsey & Co.,Mistral AI)的高管和Datadog Inc的一名董事会成员。
基于慕尼黑的Marble由德国AI工程师Felix Rösner(左图，左图)和Christophe Schmit(右图)共同创立，后者是最早意识到AI agents已经成为商品之一，几乎每个企业都以某种身份使用。 大多数组织主要使用AI agents来写作软件，但Rösner认为，要看到这些自主工人的真正价值，公司需要为他们提供颗粒式操作背景，告诉他们他们实际需要什么来建造和自动化。
但构建这幅图是一个众所周知的困难挑战，因为很少公司的工作流程按照整洁的蓝图运行。 尽管麦肯锡公司的一项研究表明，理论上可以实现美国所有工作时间的57%的自动化，但大多数公司还没有接近这一目标。
这是因为超过90%的业务流程都生活在混乱的电子邮件线条、分散的电子表格以及员工心中。 为了向AI agents传授需要建造和自动化的东西，公司需要将所有这些过程拼贴成他们可以遵循的图片。
这正是大理石公司寻求应对的挑战。 它的AI agents旨在捕捉源头的这些业务工作流程。 启动程序开发了专用桌面应用程序，该应用程序使用不同的工具和流程坐落并监测员工的工作方式。 它需要截图并捕捉工人的点击和按键，然后将这个数据转换成一个结构化的过程地图，AI agents可以读取和执行，类似于代码。
Rösner 称，“我们谈论的每一个公司都希望AI接管真正的工作，“但没有人能告诉大赦国际这项工作是如何实际完成的。 我们先解决我们的同事在他们接管之前看着工作发生他们以你最好的人民的方式这样做。”
在雇员或其老板担心隐私的情况下，Marble向他们保证，它记录的工人日常工作的所有数据都是匿名的，可以在接触任何AI模型之前进行审查。 此外，其所有模型的处理都可以在客户的私人云层或前提环境中进行。 如果员工在午餐时间浏览Facebook，就会从收集的数据中排除。
一旦收集了数据，Marble就部署其同事，他们旨在从人们手中接管最重复的工作流程，并运行一个组织现有的软件堆，在需要做出重要决定时，人类仍然处于循环之中。
罗斯纳称大理石公司已经为EGYM GmbH, Mutares SE & Co. KGaA和Enam GmbH等早期收养者带来了一些严重的增效。 在一家私人股权支持的美国金融服务公司中，Marble的同事们被配置为创造供人审查的解决方案。 由于这项工作，该公司能够将办案时间缩短90%，这意味着其人类工作人员可以多处理50%左右的声称，而无需雇用其他人。
Seedcamp General Partner Reshma Sohoni是机器人流程自动化公司UiPath Inc.，称的早期后卫，世界上绝大多数公司都希望学习如何使更多的工作自动化。 他的称写道，“Marble填补了这一空白，使公司在AI转型中具有重要背景，从而可以决定其未来。”
照片：大理石 Cognition
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Marble Cognition raises $3.75M for its AI agent workers that watch and learn how people work
Artificial intelligence agents have become two a penny in the enterprise today, but just because they’re rapidly being commoditized does not mean organizations know how best to use them.
That’s the challenge a startup called Marble Cognition is trying to solve after raising $3.75 million in pre-seed funding to coincide with its launch today. The round was led by Heartcore and Seedcamp, and saw participation from angel investors that include executives from McKinsey & Co., Mistral AI and a board member of Datadog Inc.
Munich-based Marble was co-founded by the German AI engineers Felix Rösner (pictured, left) and Christophe Schmit (right), who were among the first to realize that AI agents have already become a commodity, used by almost every enterprise in some capacity or other. Most organizations are using AI agents primarily for writing software, but Rösner believes that to see the real value of those autonomous workers, companies need to provide them with the granular operational context that tells them what they actually need to build and automate.
But building this picture is a notoriously difficult challenge because few corporate workflows run according to neat blueprints. Though a study by McKinsey & Co. suggests that it’s theoretically possible to automate 57% of all work hours in the U.S., most companies haven’t gotten anywhere near that goal.
That’s because more than 90% of business processes live within things like messy email threads, scattered spreadsheets and inside the minds of employees. To teach AI agents what needs to be built and automated, companies need to piece all of those processes into a picture they can follow.
This is exactly the challenge Marble seeks to address. Its AI agents are designed to capture those business workflows at the source. The startup has developed a dedicated desktop application that sits and monitors how employees work using different tools and processes. It takes screenshots and captures worker’s clicks and keystrokes, before transforming this data into a structured process map that AI agents can read and execute, similar to code.
“Every company we talk to wants AI to take over real work,” Rösner said. “But nobody can tell the AI how that work is actually done. So we solve that first. Our Coworkers watch how the work happens before they take it over. They do it the same way your best people do.”
In case employees or their bosses are worried about privacy, Marble reassures them that all of the data it records of their workers working day-to-day is anonymized and can be reviewed before it touches any AI models. In addition, all of its model’s processing can be done within the customer’s private cloud or on-premises environment. It learns to identify non-business-associated computer use too, so if an employee is browsing Facebook during a lunch hour, it will exclude that from the data it collects.
Once the data is gathered, Marble then deploys its Coworkers, which are designed to take over the most repetitive work processes from people and run them end-to-end an organization’s existing software stacks, with humans remaining in the loop when important decisions need to be made.
Rösner said Marble has already delivered some serious efficiency gains for early adopters like EGYM GmbH, Mutares SE & Co. KGaA and Enam GmbH. In the case of one private equity-backed U.S. financial services firm, Marble’s Coworkers were configured to create settlement offers for human review. As a result of that work, the company was able to slash its case-handling times by 90%, which meant that its human staffers could process around 50% more claims without needing to hire anyone else.
Seedcamp General Partner Reshma Sohoni, an early backer of the robotic process automation firm UiPath Inc., said the vast majority of companies in the world want to learn how to automate more of their work. “The hard part has always been mapping out how the work gets done, so you can actually automate it,” he said. “Marble fills that gap, giving companies vital context for AI transformations that could define their future.”
Photos: Marble Cognition
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