2022年5月13日

分享Lang.ai宣布其完成一係列10.5美元由納瓦企業參與的新的和現有的投資者包括海洋事業,論壇,Flexport基金,以及行業領袖——邁克Murchison (Ada)的首席執行官,喬奎姆樂Typeform (CEO)和哈維爾·馬塔Yalo (CEO),工程和銷售高級領導人在開拓基於ai公司包括Google,重量和偏見,美人,Ocrolus。”朗的使命是讓任何人受益於人工智能的力量,我們采取了不同的方法針對商業用戶和視覺上完成,而不是通過傳統的機器學習方法,依靠大型數據集和標簽/培訓”為高增長品牌,擴展客戶支持從來沒有困難,但從來沒有更重要。大流行增加了品牌所需的寬度的支持而偉大的辭職使得尋找人才服務那些更加困難。通過朗的應用技術,殘雪團隊能夠更有效率。朗自動實時標記每一位客戶的談話。標記每一票,公司啟用提取更細粒度的見解關於客戶交互和更加智能地解決他們的問題通過易於部署自動化規則。現有客戶包括縫合修複、坡道、好雞蛋,新生,花瓣卡、河馬保險和一對眼鏡。朗的自動化連接到現有的幫助台解決方案,比如Zendesk和對講機。它不需要代碼,沒有技術資源開始。這是一個低升力、高影響解決方案利用潛力增長的數據量和自動化的客戶服務團隊。 Some real-life customer examples include Fintechs routing tickets to their Product Operations team when launching new products, E-commerce brands automatically escalating canceled orders to reduce fulfillment costs, and brands auto-responding to zero-touch tickets via email for issues where an agent doesn’t need to be involved. Across all these use cases, Lang helps CS teams scale. Ramp is one example of this, as put by Tony Rios, Customer & Product Lead at Ramp; “When we onboarded Lang, we were a team of 2 support agents, including myself, and just setting up our Zendesk instance to our needs. While we’ve scaled the business massively over the past year, we’re always thinking through how we scale operationally without throwing more people at the problem. Lang is able to handle many of the most time-consuming tasks like tagging, routing to the right team of agents and handing playbooks to our agents. Related Posts “Lang’s mission is to empower anyone to benefit from the power of AI, and we’ve taken a different approach tailored for business users and done visually, instead of via traditional machine learning approaches that rely on large data sets and labeling/training,” says Jorge Penalva, CEO of Lang. “Even companies with strong data-driven cultures and dedicated insights teams, understand the power of flexibly defining their tags to gain deeper and faster insights without having to tap into scarce and expensive technical resources.” “The modern enterprise is inundated with unstructured data from emails to SMS to tickets. The customer service team is at the center of this but has no easy way to manage, let alone leverage, this data. Lang is pioneering an emerging category of companies that empower CX teams to generate actionable insights and uniquely take action on those insights automatically. This turns CX from a cost center to a customer retention center.” Manish Patel, Nava Ventures The purpose of the funding is to expand Lang’s ability to assist CX teams with a Control Center for Revenue and Automation opportunities. By understanding what each individual customer is saying at any point in their buying journey, Lang wants to help CX teams correlate this data to their purchase history as well as recommend automations for tedious workflows agents must follow when dealing with specific issues. To do this, Lang will be investing heavily in R&D and GTM teams. Ultimately, the goal of Lang.ai is to become a core layer of the CX stack to build automations and extract better insights by structuring qualitative data. Lang will continue to partner with both the frontend players (e.g. Self-Service Automation platforms ) and the backend players (Data warehouses and BI tools) to help clients drive value from data with a unified view.