DevRev has launched Voice AI for Customer Agent, a self-service support product that integrates live calls directly into its Computer platform. The new feature aims to address the difficulty customer service teams face in deploying artificial intelligence that delivers measurable results. By moving beyond simple voice interactions, the company seeks to provide AI agents with access to the records, workflows and permissions needed to resolve queries rather than simply deflecting them.
The offering relies on a shared organisational memory that draws on customer records, support tickets, orders, code, documentation and business applications. During a live call, the system can search these sources, provide updates and trigger workflows. If the case cannot be handled automatically, the call transfers to a human agent while preserving the conversation history and business context. The voice service supports multiple languages and records and transcribes calls for later analysis.
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Instead of building a separate voice product, DevRev extends the same underlying system it uses for chat and email. Existing users can add voice through a SIP-based integration with enterprise telephony systems without rebuilding workflows on another platform. This approach reflects a wider market trend as software suppliers try to unify support channels around a single layer of data and automation. The goal is to reduce the handoffs and information gaps that occur when voice, chat and email are handled by different tools.
The governance model used elsewhere in the platform carries into voice interactions. Field-level permissions are inherited from connected systems, and actions taken during a call remain auditable and traceable. DevRev has appointed Jennifer Heape to lead its Voice AI product work. She previously co-founded Vixen Labs and worked on conversational AI product strategy.
She framed the issue in terms of whether support systems can solve problems during the interaction rather than simply maintaining a smooth conversation. “I joined DevRev because the company is focused on what customers actually care about: resolving their issue during the conversation with customer support,” Heape said. “A call can sound polished and still be a poor experience if the agent cannot reach the information needed to solve the problem. Customers do not care which system holds the answer. They care whether they have to repeat themselves, wait for a transfer or call back again.”
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The challenge, according to Manoj Agarwal, Co-Founder and President at DevRev, is less about making a bot sound realistic than about giving it enough access to solve a problem on the spot. “Voice has become another interface for AI. The interesting engineering problem isn’t making an agent sound more natural. It’s giving an agent enough context to make the right decision while the customer is still on the line. In an enterprise, the answer rarely lives in one place. It lives across tickets, documentation, customer records, orders, engineering systems and business applications. If an agent can’t reason within that context, it must eventually hand the conversation to someone who can. Shared organisational memory changes that by giving an agent enough context to resolve a problem instead of simply responding to it,” Agarwal said.
For businesses trying to implement AI, the pressure to show progress is high. Gartner found that 91% of customer service and support leaders are under executive pressure to implement AI, while only 20% of organisations have reduced agent headcount because of it. Forrester has forecast that roughly one-third of brands introducing AI in self-service will fail because the underlying data is not ready. That has sharpened attention on the quality of internal systems and how well AI tools can work across them.
