Maven AGI ships enterprise voice agents with Hamming
“It's not just time saving, it's the capability and velocity. You can't even do it without a platform like Hamming.”
Dongsheng Wang, Tech Lead, Voice AI at Maven AGI
Maven AGI built its voice platform around quality from day one. Hamming became the testing platform that helped the team scale that standard.
- Location
- Boston, Massachusetts
- Industry
- Enterprise AI
- Funding
- Series B ($50M, $78M total)
Use Cases:
- •End-to-end voice agent testing
- •Concurrent load testing
- •Background noise validation
- •CI/CD release gating
Meet Maven AGI
Maven AGI builds enterprise-ready AI agents to support the full customer journey, with a focus on complex, high-friction enterprise environments.
With Hamming, Maven AGI was able to
The Challenge: maintaining a simulation/testing platform is not easy
Maven AGI has treated voice quality and reliability as core product requirements from day one. Long before scaling the platform, the team invested heavily in automated simulations and testing because they recognized early that great voice experiences depend on rigorous validation under real-world conditions.
Early on, the voice team built a homegrown simulation and smoke-testing system alongside the first version of the voice agent. With a small engineering team, they moved quickly and even used manual calling as a load test, asking tens of team members to place calls. While useful, those calls were far from true concurrency or production-scale testing.
As the product matured, the testing roadmap split into two demanding categories. Voice-specific requirements, including additional language support, background-noise simulation, and large-scale concurrent call testing, required specialized infrastructure. Table-stakes platform work, including repeatable test management, automated regression testing, and CI/CD integration, also carried an ongoing build-and-maintain cost. Rather than divert engineering focus from its voice agents and customer products, Maven AGI chose a purpose-built testing platform that provided both categories of capability out of the box.
“We were testing for a customer under high pressure for background noise. Then we saw a Hamming background noise feature we didn't notice before. Maybe it was released last week. We used it, and it was awesome.”
Dongsheng Wang, Tech Lead, Voice AI at Maven AGI
Before and After Hamming
How Hamming Transformed Voice Agent Testing at Maven AGI
Automated End-to-End Testing for Complex Workflows
Maven AGI's agents handle multi-step enterprise workflows (seven or eight steps deep) where each step must execute correctly for the conversation to succeed.
Hamming handles the testing layer, enabling the team to quickly add a suite of complex tests.
Learn more: Guide to AI Voice Agent Quality Assurance →
Concurrent Load Testing at Scale
Hamming gave Maven AGI true concurrent load testing on demand. The team routinely runs hundreds of parallel calls in a single session to stress-test their infrastructure.
When a customer asked Maven AGI to validate 100 concurrent calls, the team delivered, turning what used to be a difficult customer request into a routine one.
Learn more: Complete Voice Agent Testing Guide →
Background Noise and Environment Simulation
A customer raised a background-noise edge case that needed to be reproduced, fixed, and validated under pressure. Hamming's simulated noise environments let the team exercise those scenarios on demand and ship the fix with confidence.
The team now tests against simulated noise on demand, opening up a category of testing that wasn't practical to cover before.
Learn more: Background Noise Testing for Voice Agents →
CI/CD Integration
Maven AGI integrated Hamming into its CI/CD pipeline to run smoke tests with every release. If the tests aren't green, the team investigates before deploying. The flow isn't fully automated yet, but it gives the team an early signal to catch problems before they ship.
Beyond CI/CD, the team uses Hamming's UI for deeper exploratory testing when tuning agents for specific customers. The combination of automated smoke tests and on-demand testing gives the team confidence to move faster.
Learn more: Voice Agent Regression Testing →
Why Quality Matters to Maven AGI
Customer expectations for voice agents are evolving incredibly fast. Just a year ago, simply having a realistic conversational voice agent felt groundbreaking. Today, that level of quality is no longer impressive, it's the minimum standard users expect.
That shift is exactly why Maven AGI invested early in systematic testing and evaluation. The team has always maintained a high quality bar and refuses to ship voice experiences that feel unreliable, unnatural, or unfinished. As expectations continue to rise, catching regressions, validating performance across environments, and stress-testing systems under load have become essential parts of the development process.
“Yesterday was amazing. Today it's just expected.”
Dongsheng Wang, Tech Lead, Voice AI at Maven AGI
Why Maven AGI Chose Hamming
Maven AGI evaluated five or six platforms and ran real test scenarios against the top two. Hamming won on product polish, data model, and how well it matched the team's mental model of agent testing.
The build-versus-buy decision was clear. As Dongsheng put it: “We're builders, we want to build stuff. But when we seriously looked at this as a startup, buying made more sense.”
What won the team over:
The Results
An FTE Reclaimed, Plus Infrastructure Work Avoided
Manual testing alone consumes 0.5–1 FTE. That estimate does not include the additional engineering time required to build, operate, and continuously expand production-grade voice testing infrastructure, including concurrent-call orchestration and background-noise environments to regression tooling and CI/CD integrations. With Hamming, Maven avoids both costs: day-to-day manual validation and an ongoing internal testing-platform investment.
Hundreds of Concurrent Calls on Demand
A customer recently asked Maven AGI to validate 100 concurrent calls. The team delivered in a single session and routinely runs well beyond that to stress-test their infrastructure. Manual testing couldn't get close.
Voice-Specific Testing, Ready When Needed
The Maven voice team was under pressure to validate background-noise performance for a customer deployment, and Hamming already had simulated noise environments ready to use. Alongside language coverage and concurrent-call testing, these voice-specific capabilities let Maven validate real customer conditions without building another specialized testing system.
What's Next
A QA agent that calls Hamming on its own
Maven AGI is building an internal QA agent to automatically verify changes. Rather than hardcoding which tests to run, the agent will dynamically decide what to validate based on the change and call Hamming's MCP endpoints to execute the right tests.
Closing the guardrails gap
Maven AGI's testing strategy today is heavily focused on ensuring voice agents reliably complete intended tasks and that new releases don't introduce regressions in quality or behavior. As the platform continues to mature, the team is expanding its coverage around guardrails for customer workflows and edge-case interactions, including more sophisticated adversarial prompts and jailbreak attempts.
This work builds on Maven AGI's existing detection and prevention measures. Working with Hamming helped identify opportunities to make systematic red-teaming and adversarial evaluation an even stronger part of the broader safety and reliability roadmap.
“We get new features so quickly, you guys are building things on the fly. All the features we ask for, they turn around in one or two weeks. Looking back, we made the right decision. We're really happy.”
Dongsheng Wang, Tech Lead, Voice AI at Maven AGI
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