Vattara AI today announced the general availability of Evals Agent, its first product in a new enterprise platform built to help organizations confidently test, deploy, and monitor Voice AI agents across the development and production lifecycle.
As enterprises move Voice AI agents from pilots into real customer-facing workflows, reliability has become one of the biggest barriers to adoption. Voice agents are increasingly being deployed across customer support, sales, healthcare, financial services, and internal operations. But unlike traditional software, Voice AI systems are probabilistic, real-time, and dependent on multiple interconnected layers working together at once.
A single customer conversation can involve speech recognition, large language models, retrieval pipelines, prompt orchestration, business APIs, memory, tool execution, telephony, and speech synthesis. A failure in any one layer can appear to the customer as a broken conversation, delayed response, incorrect answer, poor handoff, or unresolved issue.
Vattara AI was built to solve this reliability gap.
With Evals Agent, teams can generate thousands of synthetic voice conversations that simulate real customer interactions before an agent goes live. The platform runs more than 100 edge cases per evaluation cycle, helping teams test for interruptions, accents, background noise, latency issues, unexpected customer behavior, prompt failures, and industry-specific conversation flows.
Instead of waiting for real customers to expose failures in production, engineering, QA, and AI teams can identify weak spots earlier, improve agent behavior faster, and move toward deployment with greater confidence.
“Enterprises are no longer asking whether Voice AI works. They are asking whether it can be trusted in production,” said Lokesh Kannan K, Co-Founder and CEO of Vattara AI. “Voice agents are moving into healthcare, fintech, support, and other high-impact environments faster than the testing infrastructure around them. We started Vattara AI to give teams an objective way to measure, validate, and continuously improve voice agent reliability before and after deployment.”
Built to Evaluate the Full Voice AI Stack
Underlying the Evals Agent is Vattara AI’s CLEAR framework, which scores voice agents across five dimensions: Conversation, Latency, Experience, Accuracy, and Resolution (CLEAR) measuring 40+ signals per evaluation. Most internal evaluation tools stop at the transcript or LLM layer. Vattara covers the entire voice stack along with telephony.
CLEAR is built to catch what standard tools miss: latency spikes, tone mismatches, and clumsy interruption handling that never shows up in text but is obvious the moment a customer hears it. More importantly, the framework evaluates whether the agent actually understands user intent and successfully achieves the core objective of the call.
“The fundamental challenge with Voice AI is that it is non-deterministic,” said Kharthigeyan PS, Co-Founder and CPTO of Vattara AI. “Every live customer interaction involves multiple real-time dependencies that traditional testing cannot fully predict. Enterprises need an independent reliability layer built specifically for voice infrastructure, one that helps them evaluate quality objectively and reduce the risk of internal self-grading.”
Vendor-Neutral by Design
Vattara AI operates as a vendor-neutral reliability and observability layer for Voice AI infrastructure. The platform integrates with existing providers including ElevenLabs, Deepgram, Sarvam, Groq, and LiveKit, allowing teams to evaluate their voice stack without being locked into a single model, vendor, or testing methodology.
This approach enables enterprises and Voice AI builders to test across different components of their stack while maintaining flexibility as models, infrastructure providers, and orchestration tools evolve.
Early Pilot Validation
Vattara AI is currently working with pilot customers across enterprise and Voice AI provider environments. Early users are using the platform to reduce manual testing effort, accelerate production readiness, and provide clearer evidence that a voice agent is ready to go live.
“What I’m looking for is something dynamic by nature — pre-production testing that reflects how customers actually talk, not a fixed script,” said a technical lead at a leading eyewear retailer piloting the platform.
A Voice AI agent provider running a separate pilot said the ability to trigger simulations through an API and receive structured evaluation reports could help its own customers gain confidence before deployment.
Vattara AI aims to help enterprise teams reduce the uncertainty that slows Voice AI deployments, giving them measurable readiness data before an agent reaches production.
Defining Voice-Ops for the Enterprise
With this launch, Vattara AI is introducing its broader vision for Voice-Ops: an operational framework for testing, deploying, monitoring, and continuously improving Voice AI systems.
Just as DevOps helped teams bring reliability to cloud infrastructure, Voice-Ops brings a dedicated engineering discipline to real-time conversational AI. It gives engineering, QA, AI, and operations teams the infrastructure required to manage probabilistic voice systems across pre-production and production environments.
Vattara AI’s roadmap extends beyond pre-production testing. Observe Agent, planned for Q4 2026, will provide continuous monitoring of live voice agent performance without adding latency to customer calls. The company is also developing ToolBox Agent, designed to validate API handoffs and tool execution across complex voice orchestration workflows.
Together, these products reflect Vattara AI’s long-term vision of becoming the reliability and observability layer for enterprise Voice AI operations.
Founding Team
Vattara AI was founded by Lokesh Kannan K and Kharthigeyan PS.
Lokesh previously led go-to-market for ElevenLabs across the Asia-Pacific region and held GTM roles at Rocketlane and Zoho Corp, alongside consulting work with Voice AI providers including Navana AI and Voxy Health.
Kharthigeyan brings deep domain experience in observability from ManageEngine, along with more than a decade of experience building and scaling enterprise SaaS products from early stages through growth.
The company is advised by Ambi Moorthy, CEO of GoZen and R. Chandrasekaran, Managing Director of Igarashi Motors.
Availability
Vattara AI Evals Agent is generally available today. Organizations can request access or schedule a demo at vattara.ai.
Observe Agent is planned for Q4 2026, and ToolBox Agent remains in active development.
About Vattara AI
Vattara AI builds an enterprise platform for evaluating, testing, and monitoring Voice AI systems across the development and production lifecycle. Built for organizations deploying conversational AI in customer-facing and business-critical environments, the platform helps engineering teams validate conversational quality, simulate real-world voice interactions, monitor production performance, and improve operational reliability
