Bland Labs catches critical bugs before customers do with Hamming
“It's like going from manual labor to using a tractor. You can prompt an agent in 30-45 minutes, but testing takes the next 2-3 hours. Building voice agents is 70% testing. Hamming makes that 70% manageable.”
Ahmad Rufai Yusuf, Forward Deployed Engineer at Bland Labs
- Location
- United States
- Industry
- Voice AI Implementation
- Stage
- Private
Use Cases:
- •Pre-deployment voice agent testing
- •Multilingual agent validation
- •Healthcare guardrail testing
- •Behavioral persona testing
Meet Bland Labs
Bland Labs is the official Bland AI implementation partner. From strategy to deployment, they build production-ready voice AI agents that drive cost savings and generate revenue—with 500K+ calls automated, $40M+ ROI generated, and 20+ agents deployed for clients like MyPlanAdvocate and American Way Health.
With Hamming, Bland Labs was able to
The Challenge: Manual Testing Was the Biggest Bottleneck in Voice Agent Development
Before Hamming, the Forward Deployed Engineering team relied entirely on manual review. Engineers would scan call transcripts one by one, checking for bugs, hallucinations, and guardrail violations. For a single customer deployment, this process could consume an entire day. For larger rollouts, it stretched into a full week.
With customers running 1,000 to 10,000+ calls per day, manual testing wasn't sustainable. Engineers could prompt an agent in 30-45 minutes, but then spend the next 2-3 hours testing—making testing 70% of the work. The team's time was consumed by repetitive QA instead of higher-value engineering.
Testing became the primary bottleneck in voice agent development. Building and prompting an agent was fast. Validating that it worked correctly across every scenario was not.
The Testing Bottleneck Was Real
70% of the work: Building voice agents is 70% testing. Prompting takes 30-45 minutes, but testing took the next 2-3 hours
Full days consumed: When calls came in concurrently, engineers spent entire days scanning call logs manually
Week-long cycles: Some deployments took half a week or a full week of back-and-forth review before launch
Scale challenges: Customers running 1,000-10,000+ calls per day made manual testing unsustainable
The Impact
| Metric | Result |
|---|---|
| Test calls run before customers start testing | 200 |
| Faster deployment cycles vs manual testing | 3x |
| Multilingual coverage without in-house speakers | 100% |
Before and After Hamming
How Hamming Transformed Voice Agent Testing at Bland Labs
Pre-Deployment Testing at Scale
With Hamming, Bland Labs now runs 100-200 test calls before customers ever interact with an agent. By the time a customer makes their first test call, the engineering team has already identified and resolved bugs, hallucinations, and guardrail violations.
This approach drives customer confidence. Instead of discovering issues during live testing, customers experience agents that have already been validated across a wide range of scenarios. The obvious problems are caught early, and edge cases are surfaced before they reach production.
Learn more: Guide to AI Voice Agent Quality Assurance →
Behavioral and Multilingual Testing
Most of Bland Labs' testing is behavioral. The team uses Hamming to simulate the full range of personas their agents will encounter in production: angry callers, impatient users, and elderly customers who need extra time.
For multilingual customers, Hamming unlocked testing that wasn't previously possible. The team has tested agents in Spanish, and could easily expand to languages like German without needing native speakers. If a customer needed a German-language agent, they wouldn't need to hire a German speaker—Hamming enables automated validation and helps the team ship with confidence.
Learn more: Multi-Language Support for Voice AI Testing →
Healthcare Guardrails and Compliance Testing
For healthcare customers, Bland Labs tests guardrails that prevent agents from making statements they shouldn't. During testing, Hamming flagged an agent making personalized medical assurances like "I assure you that you're going to get 100% healthy" or "this procedure will give you 100%."
These are exactly the kinds of errors that need to be caught before deployment, not after. By surfacing guardrail violations in testing, Hamming has helped Bland Labs and their customers avoid potential trouble in production.
Learn more: HIPAA & Clinical Workflow Testing Checklist →
The Transformation
2-3 Hours → Minutes
Per Agent Testing
Building voice agents is 70% testing. What used to take 2-3 hours of manual review per agent now happens automatically—freeing engineers to ship faster.
100-200 Calls Ahead
Before Customers Test
By the time customers make their first call, Bland Labs has already run 100-200 tests. Bugs are caught before customers ever see them.
Week → Same Day
Deployment Cycles
Testing cycles that took half a week or a full week of back-and-forth review now complete the same day. "It's like getting a tractor after years of manual labor."
Why Bland Labs Chose Hamming
Before Hamming, the engineering team spent entire days manually reviewing call logs. Testing was slow, inconsistent, and pulled engineers away from higher-value work. Each team member had their own approach to QA, and there was no shared framework for what "tested" actually meant.
Hamming changed that. The team could now run hundreds of tests in parallel, validate multilingual agents without native speakers, and catch guardrail violations before customers ever made a call. As the platform evolved, improvements to speed, UX, and audio quality made it easier to integrate into their daily workflow.
Bland Labs chose Hamming because:
The Results
Hamming has become central to how Bland Labs deploys voice agents for enterprise customers. Testing that used to consume 2-3 hours per agent now happens in minutes. Week-long deployment cycles now complete the same day.
The shift wasn't just about speed. Hamming changed how the team approaches quality. Testing is no longer the 70% bottleneck that slows down deployment—it's a competitive advantage that builds customer trust before agents ever go live.
2-3 Hours Reclaimed Per Agent
Before Hamming, prompting an agent took 30-45 minutes, but testing took the next 2-3 hours. That time is now reclaimed. Engineers validate agents across hundreds of scenarios without the manual grind of scanning call logs one by one.
100-200 Calls Before Customers Test
By the time customers make their first test call, Bland Labs has already run 100-200 tests. Bugs, hallucinations, and guardrail violations are caught early. Customers experience agents that work—not agents that are still being debugged.
A Shared Standard for Quality
With Hamming, "I tested it" now means something consistent across the team. Engineers no longer have their own individual approaches to QA. There's a shared framework, a common language, and confidence that critical paths are covered every time.
“I would definitely recommend Hamming to anyone that builds voice agents, especially if they do a lot of volume. It speeds up the rate of builds because testing is what makes agents feel more natural than robotic to customers. The better and faster the testing, the more rockets you can launch quickly—and feel good that they won't blow up.”
Ahmad Rufai Yusuf
Forward Deployed Engineer at Bland Labs
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