Testing Multilingual Voice AI Across Africa
How native speakers tested voice AI agents through real calls, local accents and everyday network conditions across five African markets.
MyDeepTech Team · Case Study · 5 min read
400+ audio hours — of live voice-agent calls recorded across the programme.
5 countries, 6 languages — native-speaker testers recruited across five African markets.
38 native-speaker testers — conducting live calls under real-world network conditions.
1,500+ TTS evaluation tasks — completed in about a week.
The Challenge
A voice AI technology company needed to understand how its agents performed outside controlled testing environments.
Real-world calls can expose challenges that are difficult to reproduce in a lab, including local accents, mixed-language speech, background noise and weak or inconsistent network signals.
The client needed native speakers in local markets to test voice agents under realistic conditions and provide feedback that could be reviewed and acted upon.
Our Approach
MyDeepTech recruited and coordinated native-speaker testers across five African countries, organizing local teams to conduct live calls using real phones and local networks.
Local project leads supported the testing operation, while contributors followed a structured cycle of calling, feedback, tracking and review. Delivery included:
Native-speaker recruitment and coordination across five countries
Live voice-agent calls using real phones and local networks
Testing across accents, languages and everyday call conditions
Feedback capture and issue tracking
Daily activity monitoring and quality checks
Review and monthly reconciliation of project activity
Voice AI needs to work for the people and environments it is built to serve.
A Continuous Testing and Review Loop
Testing was organized as a repeatable loop: testers placed calls, submitted feedback, activity was tracked, and results were reviewed.
This structure helped make observations traceable and supported ongoing review of agent performance under real-world conditions.
Daily tracking, quality checks and monthly reconciliation provided an operational basis for monitoring delivery.
The Result
Across the programme, MyDeepTech supported 400+ audio hours of live voice-agent calls with 38 native-speaker testers across five countries and six languages.
The operation also completed 1,500+ text-to-speech (TTS) evaluation tasks in about a week, giving the client a structured way to test multilingual voice AI with real speakers and real network conditions.
Why It Matters
Voice AI needs to work for the people and environments it is built to serve.
Testing with native speakers across local markets helps teams examine how agents respond to different languages, accents and real-world call conditions.
MyDeepTech combines local talent with coordinated testing operations and measurable delivery to support more grounded voice AI evaluation.
Native-speaker testing + real-world conditions + measurable delivery.
AI Data. Human Intelligence.
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