How Humach used Confident AI to ship voice AI 200% faster

_{THE COMPANY}

Humach is pioneering the future of enterprise-grade voice AI agents

With over 30 years of experience in providing live agent support for enterprises such as McDonald's, Visa, and Amazon, Humach is transforming its expertise into building the world’s best digital AI voice agents. Their mission is to deliver emotionally intelligent, multimodal voice AI assistants that can interact and transact at scale for global enterprises.

At the heart of Humach’s strategy is its AI Whisperer program—a human-in-the-loop workforce that ensures every voice agent deployment is secure, governed, and aligned with client expectations. Unlike consumer-facing assistants such as Alexa, Humach’s voice agents are tailored for enterprises who need robust, highly customizable, and compliant solutions.

“We believe conversations are the most natural way for enterprises to engage their customers and employees,” says Sean Austin, Chief of AI at Humach. “Our mission is to combine voice, EQ tuning, and human oversight to deliver intelligent agents that don’t just transact, but build trust.”

Today, Humach serves scaled enterprises such as such as McDonald's, Visa, and Amazon across industries, delivering bespoke digital voice experiences that drive value for both customers and employees.

_{THE BUILDUP}

Humach needed a better way to scale testing for enterprise voice experiences

Building enterprise voice agents isn’t just about getting an LLM to talk—it’s about creating secure, compliant, and highly personalized deployments that enterprises can trust. Each project comes with its own unique requirements, meaning Humach must continuously adapt its testing and training processes.

Sean’s team faced several challenges common in enterprise AI deployments:

• Customization at scale: Every client needed their own criteria, workflows, and evaluation standards.

• Governance-first mindset: Enterprises prioritized secure data handling and governance as table stakes before even considering user experience.

• Multi-turn complexity: Voice agents aren’t single-shot prompts—they require rich, multi-turn interactions that must be simulated, tested, and refined across multiple personas and demographics.

“We knew we needed a platform that could help us simulate real-world conversations, evaluate them against enterprise-specific criteria, and ensure security from day one,” explains Sean.

_{THE PROBLEM}

Manual evaluation couldn’t keep pace with enterprise demands

Before Confident AI, Humach relied on a mix of manual evaluations and ad-hoc processes to test its agents. While this worked at smaller scale, it wasn’t sustainable as their enterprise deployments grew.

The team faced three key blockers:

1. Fragmented testing pipelines: Testing involved engineers, QA, AI Whisperers, and PMs—but without a centralized workspace, collaboration was disjointed. Metrics lived in separate spreadsheets or internal notes, while datasets in CSVs - making peer review slow and error-prone.

2. Limited visibility into key metrics: Latency, bias, and factuality were core concerns for clients—but tracking them consistently across projects required custom tooling Humach didn’t have.

3. Scaling simulations was painful: Designing and running multi-turn simulations meant cobbling together datasets, scenarios, and persona definitions outside of their core platform. Without proper tooling, this slowed down onboarding of new AI Whisperers and made consistent evaluation difficult.

As Humach’s deployments scaled, it became clear that building their own evaluation workspace would require hundreds of thousands of dollars in engineering time—resources better spent on improving the voice agent experience itself.

_{THE SOLUTION}

A unified workspace for annotation, evaluation, and simulation

After evaluating multiple options, Humach ultimately chose Confident AI as its LLM evaluation platform of choice. Multi-turn simulation support was a major deciding factor. For Humach, realistic conversation testing is central to building enterprise-ready voice agents. “We run a lot of large-scale, multi-turn simulations, and Confident AI made it far easier to design scenarios and execute those tests without piecing together external tools,” Sean explains.

Another thing that stood out first was the breadth of features. “The platform came ready with latency tracking, bias evaluation, and relevancy metrics,” says Sean. “But more importantly, it gave us the flexibility to design our own evaluations whenever a client project demanded it.”

The collaborative workspace also changed how teams worked together. Instead of engineers, AI Whisperers, and PMs trading spreadsheets, everyone now operated in a single environment where peer review and standardized processes came built-in.

_{THE IMPACT}

200% faster speed to market, empowered non-technical teams, and seamless collaboration

By adopting Confident AI, Humach didn’t just move faster—it transformed how its technical and non-technical teams work together.

“Confident AI increased our speed to market by 200%,” says Sean Austin, Chief of AI. “By focusing our time on delivering value instead of reinventing testing pipelines, we can bring new solutions to clients much faster.”

For Dezaray Hammond, VP of training & development, the breakthrough was how the platform enabled non-technical AI Whisperers to take part in the process. “Our annotators can now work directly in Confident AI alongside engineers,” she explains. “That means no more CSVs, no more scattered spreadsheets—just one centralized workflow where everyone contributes.”

This shift turned evaluation from a siloed task into a true cross-team effort. With more than 20 annotators labeling multi-turn datasets inside Confident AI, Humach can now scale governance, bias checks, and relevancy testing in ways that weren’t possible before. As Sean puts it, “For us, compliance and trust aren’t optional—they’re required. Confident AI helps us deliver both.”

And on the human side, the partnership matters just as much as the product. “Working with Confident AI is a joy,” Dezaray concludes. “They’re responsive, supportive, and genuinely feel like partners. That makes all the difference when we’re building something this important.”