How real-time STT empowers multilingual support & unlocks international growth

Published on July 18, 2025
How real-time STT empowers multilingual support & unlocks international growth

Businesses expanding globally face an immediate language barrier. Customers want service in their native tongue, but most companies and call center providers don’t have enough multilingual agents to meet that demand.

Even when local agents are available, internal systems and supervisors may not understand the calls, making it hard to coach, train, or enforce quality standards. These language gaps delay expansion and introduce risks around compliance, consistency, and customer satisfaction.

But real-time speech-to-text (STT) and machine translation (MT) changes that. 

Together, they make it possible for agents to speak in one language while customers hear another, and for supervisors and AI systems to monitor every interaction, whether it’s French or Farsi.

Providers that build this capability into their stack can drive international growth for their clients, and revenue growth for themselves. This article unpacks exactly how. 

Key takeaways:

  • Language is becoming a growth bottleneck. As BPOs and CCaaS platforms face pressure to expand globally while cutting costs, multilingual support is no longer a nice-to-have — it’s a competitive necessity.
  • Everyone benefits from real-time voice AI. Customers get faster, in-language support; agents can work more productively; supervisors gain visibility for QA and coaching; and enterprise clients get scalable global service.
  • Success depends on how you implement it. Integrating real-time STT and MT into existing workflows is key, and choosing a contact center–ready STT provider makes all the difference.

Why multilingual customer service is a challenge

Most companies want to grow into new markets, but language quickly becomes a bottleneck for several reasons:

  • Talent limitations: Hiring fluent support or sales agents for every target language is expensive, time-consuming, and often unrealistic (especially for companies expanding into multiple markets at once). Even in large global BPOs, language-specific hiring can slow down onboarding, drive up wages, and limit scalability.
  • QA and management blind spots: When calls happen in a language a manager doesn’t speak, quality control breaks down. Supervisors can’t effectively coach agents, review transcripts, or spot compliance issues. This creates risk, not only to customer experience, but also to brand consistency and regulatory oversight.
  • Fragmented systems: Most CRMs, QA platforms, agent assist tools, and compliance systems are designed with a single language (typically English) in mind. Running multilingual support means toggling between tools, translating manually, or losing out on key insights from calls in other languages.

The result? Many businesses hold off on international expansion. Not because of lack of demand, but because of the internal complexity multilingual service introduces.

This makes multilingual support at scale a clear differentiator for BPOs and CCaaS providers. If your platform or service can solve this challenge—by enabling seamless, scalable multilingual support—you don’t just add a feature. You unlock growth.

How real-time STT and MT solve this challenge

Modern speech-to-text (STT) and machine translation (MT) tools eliminate the language barriers that have slowed international expansion and complicated support operations.

STT technology transcribes live voice conversations instantly, capturing speaker turns, timestamps, and context in real time, even in noisy or high-volume environments. Importantly, it doesn’t just convert speech into text; it preserves structure and nuance.

Machine translation (MT) then translates these conversations on the fly. Agents, AI tools, or supervisors can interact with the content in their preferred language, regardless of the language being spoken by the customer.

This changes what’s possible in real-time support:

  • Agents can serve in any market: A support agent in the Philippines can respond to a German customer all while speaking English. The conversation is translated in both directions instantly, keeping the dialogue natural and accurate.
  • AI and agent assist tools go multilingual: Real-time agent assist tools—such as auto-suggested replies or knowledge base lookups—can function regardless of the customer’s language. With live transcription and translation, AI understands the conversation in context and supports the agent in their native language. Teams only need to build these tools once, and they scale to every market.
  • Supervisors regain visibility: Managers who don’t speak a given language can still review transcripts, monitor active calls, and deliver coaching. They’re no longer locked out of QA and training just because the call happened in Sanskrit.

Benefits for BPOs and CCaaS platforms

Real-time STT and MT are strategic capabilities that directly support growth, efficiency, and quality at scale. For BPOs and CCaaS providers, these tools unlock smarter ways to serve clients, manage global teams, and compete in more markets. This leads to:

  • Lower support costs: By removing the requirement to hire dedicated agents for each language, businesses reduce staffing complexity and labor costs. Offshoring becomes more viable, even in regions that don’t share a language with the end customer.
  • Easier global expansion: Serving new geographies no longer requires hiring entire teams of local, fluent agents. With translation layered into the workflow, companies can support multiple languages using their existing infrastructure. Time to market drops from months to weeks.
  • Smarter offshoring: BPOs can offshore support to lower-cost regions without compromising service quality. Even if agents don’t speak the customer’s native language, real-time MT bridges the gap—and enables centralized QA, regardless of language.
  • More consistent performance at scale: With real-time transcription and translation, managers can evaluate calls, coach agents, and enforce quality standards—no matter the language. Brand voice, compliance, and customer experience stay aligned globally, improving CSAT and retention while making performance management more fair and data-driven.

How to implement real-time multilingual support

Adding real-time multilingual capabilities to your call center tech stack isn’t as complex as it sounds. It really just relies on thoughtful integration and operational readiness. Let’s break it down.

Step 1: Choose high-performance STT + MT tools

Look for providers with strong multilingual coverage, low transcription and translation latency, and high accuracy across diverse accents and call conditions. Cloud-native tools with real-time APIs are ideal. 

The goal is smooth, conversational translation, not laggy or fragmented outputs.

Pro tip: Test tools in real-world conditions, especially with background noise or non-native speakers. Vendor claims don’t always match performance in the field.

Check out our Buyer’s Guide for STT APIs to help evaluate vendors and choose the right one.

Step 2: Integrate with your agent desktop and QA tools

Transcriptions and translations should appear directly in the tools agents already use. That could be a custom desktop app, a CCaaS interface, or CRM-integrated call handling software.

The same goes for QA: real-time or post-call data must flow into performance dashboards and feedback loops automatically.

Step 3: Customize agent assist triggers and alerts across languages

Agent assist systems often rely on detecting keywords or sentiment in a specific language. With multilingual support, you’ll need to adapt these to work post-translation—or use models that are language-agnostic. 

Ensure escalation alerts, prompts, and compliance checks remain accurate after translation.

Step 4: Enable multilingual QA and coaching workflows

Once the systems are in place, enable supervisors and QA teams to consistently act on translated data. Managers should be able to review transcripts and summaries, add feedback, and track agent performance, regardless of the original call language.

Build training playbooks that show how to use translated insights effectively, so coaching isn’t left to guesswork or ad hoc interpretation.

Pro tip: Use summarization models alongside MT to create clean, translated recaps of long calls. This helps managers focus on key moments, not wade through entire transcripts.

How Gladia empowers global support with real-time voice AI

Gladia’s real-time STT API offers industry-leading accuracy, low-latency streaming, and support for over 100 languages (including 42 that other providers don’t support). 

What else sets Gladia apart?

  • Fine-tuned language control: This allows our customers to pre-set expected languages in a call for faster, more accurate transcription, which is ideal for routing and contact center precision.
  • Real-time code-switching: That means agents and customers can switch between languages mid-sentence without breaking comprehension or transcription quality.
  • Consistent accuracy in real-world conditions: Gladia was built and benchmarked for contact centers, not clean lab audio. It performs reliably, even in noisy environments with overlapping speech (exactly the kinds of challenges you face in live support settings).
  • Built-in features: Gladia’s modular add-ons include speaker diarization, custom vocabulary, sentiment analysis, and now, translation controls like context and informal. These features help you localize tone, formality, and phrasing for specific audiences or regions.

Learn more about our unique, hybrid approach to accent management and code-switching, or talk to our team today to make multilingual support a reality.

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