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TechCrunch AI · 2026/7/29 14:41:06

Encore AI raises $30M to build AI agents that learn from customer calls
AI 中文解读
Encore AI刚刚拿下3000万美元投资,核心卖点是它能让AI代理“偷师”企业最优秀的客服和销售员工。这家公司通过分析大量客户通话、邮件和聊天记录,拆解出哪些话术、哪些策略真正促成了成交或解决问题,然后把这些成功经验打包成AI的“剧本”。换句话说,AI不再只是机械回答,而是学会了员工讲的笑话、举的例子,甚至能模仿顶尖关系经理的应对方式。对企业而言,这意味着客户服务会更高效,客户体验会更一致——无论你打电话遇到的是真人还是AI,得到的建议和语气可能都来自同一个优秀“模板”。对普通人来说,以后打客服电话时,可能会感觉对方更懂你、解决更快,因为AI正在把公司里最强的沟通技巧变成标准服务。不过,这类工具也意味着你的通话记录会被深度分析,隐私边界值得留意。
Encore AI, a startup that studies companies’ customer interactions to train and deploy AI voice agents that can work alongside customer support and sales teams, or operate autonomously, has raised $30 million in a Series A round led by Team8.
Founded in 2022 as Insait IO by CEO Dvir Ginzburg, the company started out building recommendation software for financial advisers and relationship managers. Now rebranded as Encore AI, the startup has expanded that system into a platform that analyzes conversations between a company’s employees and customers to identify which approaches resulted in successful outcomes, and uses those findings to train its AI agents.
The result, according to Ginzburg, is an AI agent that leverages the strongest parts of the playbooks used by an organization’s employees.
“Sometimes our agents even tell the jokes that the relationship managers are telling, or give the anecdotes or examples that the relationship managers are giving, because we literally run by the playbooks that we see working […] The agent we build is a package of many different playbooks that have worked throughout the process,” he told TechCrunch in an exclusive interview.
Ginzburg calls the process “interaction mining.” The company’s platform collects call recordings, emails, and text messages, and connects that info with CRM systems. It then divides the customer interactions into stages and tries to find out which parts of a conversation helped move the process along, and which failed.
This lets Encore’s agents, and consequently its customers, learn what works best for any particular client or interaction, as different employees may be either more or less effective at different points during a sales or customer success process, Ginzburg told TechCrunch.
The company’s platform also lets companies identify where their existing customer support and sales processes are falling short, identify inefficiencies and friction points, and find key issues.
A screenshot of Encore AI’s interaction mining toolImage Credits:Encore AI
Encore says its agents can communicate directly with customers by voice or text, as well as act as assistants to employees, recommending responses and tactics during conversations.
The company has more than 40 enterprise customers globally, the majority of which are financial institutions, according to Ginzburg. He said Encore’s annual recurring revenue has increased more than 5x since it raised its seed round less than 18 months ago, though he declined to disclose exact revenue numbers or valuation.
Encore’s early to this market, but its share may become harder to defend as large CRM providers like Salesforce, SAP, Zoho, and HubSpot can build similar AI capabilities around their customers’ data. But Ginzburg contends that access to data alone isn’t enough, as established vendors would need to overhaul their processes to make historical customer conversations the foundation of their agents like Encore does.
“The biggest players that we are competing against, they don’t see [conversational] history as a data point that they are utilizing. For them to start asking for conversational data with their current employees will require changing their entire implementation stack and technological stack,” he said.
Planven, Lukatz, and Garage also participated in the round, as did some banks and insurers. Encore said some of the financial institutions participating in the round first used its product before deciding to invest.
The startup plans to use proceeds from the Series A to expand its U.S. sales operations and deploy its platform with more large financial institutions.
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