Encore AI raises $30M for AI agents that learn from calls

▼ Summary
– Encore AI raised $30 million in a Series A round led by Team8 to train and deploy AI voice agents for customer support and sales.
– The startup analyzes employee-customer conversations to identify successful approaches, using those findings to train its AI agents.
– Encore’s platform collects call recordings, emails, and texts, then divides interactions into stages to determine what drives success or failure.
– The company has over 40 enterprise customers, mostly financial institutions, and its annual recurring revenue has grown more than 5x since its seed round.
– Proceeds from the Series A will be used to expand U.S. sales operations and deploy the platform with more large financial institutions.
Encore AI has secured $30 million in Series A funding to scale its platform that analyzes customer conversations and builds AI voice agents capable of working alongside or replacing human support and sales teams. The round was led by Team8.
Founded in 2022 under the name Insait IO by CEO Dvir Ginzburg, the company initially developed recommendation software for financial advisors and relationship managers. After rebranding to Encore AI, the startup transformed that foundation into a system that studies interactions between employees and customers, pinpoints which behaviors drive success, and then trains its AI agents to replicate those winning tactics.
Ginzburg describes the result as an agent that embodies the best practices already proven within an organization. “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,” he said. “The agent we build is a package of many different playbooks that have worked throughout the process.”
He calls this approach “interaction mining.” Encore’s platform collects call recordings, emails, and text messages, linking that data with CRM systems. It then breaks down each customer interaction into stages, identifying which segments advanced the conversation and which fell flat. This granular analysis allows Encore’s agents , and, by extension, its clients , to learn what works best for each specific customer or scenario, since different employees may excel at different points in a sales or support cycle.
Beyond powering AI agents, the platform helps companies spot weaknesses in their existing processes, uncover inefficiencies, and highlight recurring friction points. Encore’s agents can communicate directly with customers via voice or text, or serve as real-time assistants to human employees, suggesting responses and strategies during live interactions.
The company now serves more than 40 enterprise customers globally, most of which are financial institutions. Ginzburg noted that Encore’s annual recurring revenue has grown more than fivefold since its seed round less than 18 months ago, though he declined to share specific revenue figures or valuation.
Encore is an early mover in this space, but competition is heating up as major CRM players like Salesforce, SAP, Zoho, and HubSpot develop similar AI capabilities around their own customer data. Ginzburg argues, however, that access to data alone is insufficient. He believes established vendors would need to fundamentally rework their systems to make historical customer conversations the core of their AI agents, as Encore does.
“The biggest players that we are competing against, they don’t see [conversational] history as a data point that they are utilizing,” Ginzburg said. “For them to start asking for conversational data with their current employees will require changing their entire implementation stack and technological stack.”
Planven, Lukatz, and Garage also participated in the round, alongside several banks and insurers. Encore noted that some of the financial institutions that invested first used the product before deciding to back the company. The startup plans to use the Series A funds to expand its U. S. sales operations and deploy its platform with more large financial institutions.
(Source: TechCrunch)




