Roark

Roark helps teams test, monitor, and improve their voice agents.

Voice AI is exploding, but reliability is still the #1 challenge. Teams spend hours manually testing agents and still miss failures. In the last 6 months, Roark has processed over 10M minutes of calls, powering monitoring and simulation for teams across the Voice AI ecosystem (including YC companies).

We close that gap by combining:

📊 Monitoring & Evaluation - 40+ built-in metrics (latency, instruction-follow, sentiment, etc.), custom dashboards, alerts, and the ability to define your own. Up to 15 speakers with automatic speaker identification.

🎭 Simulations & Personas - end-to-end phone/WebSocket simulations for inbound and outbound agents, with configurable personas (accents, languages, speech & behavior profiles). Define tests as conversations with a graph-based approach, so you can easily branch into edge cases and variants.

🔁 Full lifecycle loop - failed calls automatically become repeatable tests, so every failure makes your agent stronger.

Roark is the missing QA layer for Voice AI - helping teams ship agents they can trust.

Roark is a cutting-edge evaluation, testing, and simulation platform designed specifically for voice AI agents. It automates the creation of test suites from real customer interactions and AI-driven edge-case predictions, enabling businesses to validate every conversational path before deployment. This helps companies ship reliable voice AI faster by replaying real production calls against the latest AI changes, ensuring real-world validation beyond scripted tests. Roark primarily serves voice AI development teams in sectors like healthcare, legal, and customer support, addressing the challenge of testing voice agents efficiently and accurately to improve customer experience and operational efficiency[1][2][3][4].

Founded by James Zammit and Daniel Gauci Mizzi, both experienced engineers with backgrounds in AI, infrastructure, and mobile development, Roark emerged from the founders’ recognition of a universal problem: voice AI teams lacked effective tools to test updates without manual, error-prone processes. Their combined expertise in scaling complex systems and AI-powered products informed Roark’s development. Early traction includes recognition as a Y Combinator W25 batch company and adoption by teams seeking a smarter, faster way to test and monitor voice agents[2][3][4].

Core Differentiators

• Real Production Data Replay: Unlike traditional scripted tests, Roark replays actual customer calls, capturing real accents, background noise, and conversational nuances for authentic validation[3][4].
• Automated Test Suite Generation: AI-driven edge-case prediction creates comprehensive test suites automatically from real interactions, reducing manual effort and blind spots[1].
• Multi-Speaker and Sentiment Analysis: Roark analyzes individual speakers in multi-party calls and evaluates sentiment and vocal cues, providing deeper insights into user experience beyond transcripts[3].
• Continuous Improvement Loop: Failed calls automatically become new tests, enabling teams to proactively manage regressions and ship updates with confidence[3][6].
• Developer-Friendly Observability: Provides voice AI teams with metrics and monitoring tools akin to modern software dev tools, fostering a culture of continuous iteration and quality assurance[4].

Role in the Broader Tech Landscape

Roark rides the growing trend of voice AI adoption across industries, where conversational agents are becoming critical customer touchpoints. The timing is crucial as voice AI complexity increases and traditional testing methods fail to capture real-world variability. Market forces such as rising customer expectations for seamless voice interactions and regulatory demands for reliability in sectors like healthcare amplify the need for robust testing platforms. Roark’s approach influences the ecosystem by setting a new standard for voice AI observability and quality assurance, complementing conversation intelligence tools and enabling faster, safer deployment of voice agents[3][4].

Quick Take & Future Outlook

Roark is poised to expand its influence as voice AI adoption accelerates and enterprises demand higher reliability and better user experience. Future trends shaping Roark’s journey include advances in AI-driven simulation, integration with broader AI development pipelines, and deeper analytics for multi-modal conversational AI. As voice agents become more ubiquitous, Roark’s platform could evolve into an essential infrastructure layer for voice AI observability, helping teams ship innovations faster while minimizing risk. Its unique real-call replay capability and continuous testing loop position it well to lead in voice AI quality assurance, driving improved customer interactions across industries[3][4][6].