Crux Labs 融资超过 6M 用于用人判断改进企业 agents
Crux Labs，一个将企业判断转化为持续agent改进的人工智能平台，发布今天拥有超过600万美元的资金。
Benchstrength和Misneach领导了该轮比赛，Analog Ventures和Pareto控股公司参加了该轮比赛。
企业AI agents在部署中的规模可以从每天数千到数百万用户交互。 现有的可观察性平台使得人类更容易进行监控和检查，但使得在更高量的agent行为难以改进。
许多团队最终根据特定的度量，阈值或随机选择，对1%或更少的痕迹进行取样，进行人工审查，这意味着绝大多数的agent故障通过。
称联合创始人兼首席执行官Julie Kheyfets(照片，左), “Agents在实现目标方面是不可思议的，但他们无法接触我们人类在脑海中收集的多年的热力。
从公司的角度来看，如果在专家的头上存在“什么是好的”的话，纠正办法总是会很晚才出现。 这可能意味着一个问题作为一个小故障出现到升级到一个门票输入系统并最终应用一个补丁之间要经过几周的时间。 如果专家与AI agents处于同一水平，这个周期可以大大缩短。
Crux用自己的agents来应对这一挑战，充当评估员和改进团队。 他们捕捉了员工的专家判断，并校准了数百万人的互动，因此员工不需要看一个小样本来了解正在发生的事情。 他们可以扩大自己的判断力跨越更大的部分。
称公司在保健、网络安全、金融服务和其他复杂产业方面，在高成长的创业企业和财富500家企业中，其平台得到了强有力的推动。
称联合创始人兼首席技术官Krishna Kulkarni(右翼)。
照片：Crux AI
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Crux Labs raises over $6M to improve enterprise agents with human judgment
Crux Labs, an artificial intelligence platform turning enterprise judgment into continuous agent improvement, launched today with over $6 million in funding.
Benchstrength and Misneach led the round, with participation from Analog Ventures and Pareto Holdings.
The scale of enterprise AI agents in deployment can range from thousands to millions of user interactions per day. Existing observability platforms make agentic traces easier for humans to monitor and inspect, but make it difficult to improve agent behavior at higher volumes.
Many teams end up sampling the top 1% or less of traces for manual review based on a particular metric, threshold or random selection, meaning that the vast majority of agent failures pass by.
“Aligning AI agents to human judgment is one of the biggest challenges of our time,” said co-founder and Chief Executive Julie Kheyfets (pictured, left). “Agents are incredible at attaining goals, but they lack access to the years of heuristics that we as humans have collected in our heads.”
From the company’s point of view, if “what good looks like” exists in the heads of experts, chances are that fixes will always arrive late. This could mean weeks passing between a problem appearing as a small glitch and escalating to the point where a ticket is entered into the system and a patch eventually applied. This cycle can be greatly reduced if the experts and the AI agents are on the same level.
Crux uses its own agents to address this challenge by acting as evaluators and an improvement team. They capture employees’ expert judgment and calibrate it across millions of interactions, so workers don’t need to look at a tiny sample to understand what’s happening. They can amplify their own judgment across a larger segment.
The company said it has seen strong traction for its platform across high-growth startups and Fortune 500 businesses in healthcare, cybersecurity, financial services, and other complex industries.
“Engineering teams know how to build AI agents, and subject matter experts know what success looks like, but enterprises lack the bridge between them,” said co-founder and Chief Technology Officer Krishna Kulkarni (right).
Photo: Crux AI
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