Best Software for Automating Call Center Quality Monitoring

Manual QA sampling covers 3 to 10 percent of calls in most contact centers, according to ICMI's contact center research. For contact centers serving multilingual customer bases, that coverage gap compounds: agents handling Spanish, French, or Mandarin calls often fall outside QA review entirely because scoring tools only process English transcripts reliably. The platforms below automate scoring across 100 percent of calls and support multilingual transcription so QA programs do not have blind spots by language.

How We Ranked These Platforms

Platforms were selected based on their ability to automate call scoring at scale, support multilingual transcription, and produce data connecting quality monitoring to outcomes. Weighting reflects the priorities of QA managers responsible for program coverage, accuracy, and compliance across languages.

Insight7 platform data from Q4 2025 shows transcription accuracy at 95 percent and LLM-generated QA insight accuracy above 90 percent across evaluated calls. The platform supports 60+ languages including Spanish, French, German, Polish, Ukrainian, and Romanian.

Does Call Quality Monitoring Software Support Multiple Languages?

Most QA platforms depend on a transcription layer for accuracy. The quality of multilingual QA is directly determined by the quality of multilingual transcription underneath it. Platforms built on general-purpose ASR engines typically support 30 to 60 languages with accuracy varying significantly by accent and regional dialect. Key questions when evaluating multilingual support: Does the platform detect language automatically or require manual selection per call? Does scoring logic apply consistently across languages, or only to English transcripts? Are compliance-specific terms handled correctly in each target language?

Insight7

Insight7 is a standalone call analytics and QA platform that applies configurable weighted criteria to 100 percent of calls automatically. Each criterion includes a definition of what good and poor looks like, with a toggle that switches between verbatim compliance checking and intent-based scoring per criterion. Multilingual support covers 60+ languages, enabling QA programs to apply the same scoring rubric to English, Spanish, French, German, Italian, Polish, Ukrainian, and other language calls without separate configurations.

Agent scorecards cluster multiple calls into a single view per agent per period, showing criterion-level performance trends regardless of the language the call was conducted in. TripleTen processes over 6,000 learning coach calls per month through Insight7, including multilingual sessions, at the cost equivalent of one US-based project manager.

Con: Initial scoring alignment requires 4 to 6 weeks of criteria tuning before AI scores reliably match human QA judgment. Regional accent variations such as UK and Irish accents can cause transcription errors requiring company-context programming.

Pricing starts at approximately $699/month on a minutes-based model. See insight7.io/pricing/.

Insight7 is best suited for contact centers in financial services, healthcare, or insurance where 100 percent call coverage, configurable compliance scoring across multiple languages, and evidence-backed per-agent scorecards are program requirements.

Insight7 delivers the most configurable multilingual scoring architecture on this list, making it the strongest option for QA programs that need criterion-level evidence across languages.

Speechmatics

Speechmatics is a transcription-layer platform delivering high-accuracy speech-to-text in 50+ languages with an on-premise deployment option. It is not a QA platform. Speechmatics produces accurate transcripts that other tools or custom engineering can score. For teams building a custom multilingual QA stack with data residency requirements, Speechmatics provides the transcription foundation.

Con: Requires significant internal engineering to build any QA layer on top of transcription output. No out-of-box scoring, no agent scorecards, no CSAT correlation.

Speechmatics is best suited for enterprise engineering teams building custom call analytics stacks that need a high-accuracy, on-premise multilingual transcription engine.

Scorebuddy

Scorebuddy is a hybrid QA platform combining manual scorecard evaluation with an automated scoring layer. A side-by-side interface lets QA leads compare AI scores to human scores on the same call and calibrate criteria before committing to full automation. For multilingual contact centers, the calibration interface allows QA managers to validate that AI scoring is consistent across language variants before removing human oversight.

Con: At high call volumes (10,000+ calls per day), the manual review component creates backlogs that undermine automation benefits. The hybrid model works best for teams with 20 to 100 agents, not enterprise-scale contact centers.

Scorebuddy is best suited for QA programs transitioning from manual review that need a structured calibration path, particularly for teams introducing multilingual automation incrementally.

Zendesk QA

Zendesk QA (formerly Klaus) applies automated scoring to 100 percent of interactions across voice, email, and chat, with CSAT correlation data surfaced within the Zendesk dashboard. Multilingual support is available through Zendesk's broader translation infrastructure, making it a practical option for global support teams already on the Zendesk platform.

Con: Scoring categories are less configurable than standalone platforms. Teams with complex multilingual compliance requirements or multi-criterion weighted rubrics will hit configuration limits quickly.

Zendesk QA is best suited for support teams already on the Zendesk platform that need multilingual QA coverage without adding a separate vendor.

Tethr

Tethr applies a pre-built effort score model to every call, quantifying customer friction signals including policy obstacles, process failures, and agent-created effort. The model translates these signals into a predictive metric correlating with churn risk.

Con: The fixed model limits customization. Teams needing configurable scoring criteria or multilingual compliance-specific verbatim checking will find the pre-built effort score insufficient.

Tethr is best suited for CX analytics teams prioritizing customer effort reduction and churn prediction over configurable multilingual agent performance scoring.

If/Then Decision Framework

If your priority is 100 percent call coverage with configurable compliance scoring across multiple languages, then use Insight7 because its 60+ language support applies the same weighted criteria system across all call languages in a single QA program.

If your team needs an on-premise multilingual transcription engine to build a custom QA stack, then use Speechmatics because it is the only platform on this list with a fully self-hosted deployment option across 50+ languages.

If your team is transitioning from manual review and needs calibration tools for multilingual scoring, then use Scorebuddy because the side-by-side AI and human scoring interface lets QA leads validate multilingual accuracy before removing human oversight.

If you are already on Zendesk and need multilingual QA coverage without adding a vendor, then use Zendesk QA because it activates within the existing Zendesk infrastructure.

If your primary goal is reducing customer effort and predicting churn across languages, then use Tethr because its effort score model produces a standardized churn-correlated signal at scale.

FAQ

What call quality monitoring software supports multilingual transcription?

Insight7 supports 60+ languages including Spanish, French, German, Polish, Ukrainian, and Romanian with QA scoring applied across all languages using the same configurable criteria. Speechmatics supports 50+ languages as a pure transcription engine without built-in QA scoring. Most major CCaaS platforms such as Zoom, RingCentral, and Amazon Connect support multilingual transcription as an input layer but require separate QA tooling on top.

How accurate is multilingual call transcription for QA purposes?

Accuracy varies by language, accent, and ASR engine. General benchmarks show English accuracy at 90 to 95 percent on clean audio; accuracy for other languages ranges from 80 to 93 percent depending on regional accent and audio quality. Insight7 reports 95 percent transcription accuracy overall, though regional accent variations such as UK and Irish accents require company-context programming to achieve that benchmark. For compliance-critical multilingual programs, a 4 to 6 week calibration period is standard before automated scores are used for coaching decisions.

What is the best quality monitoring software for multilingual contact centers?

For contact centers needing full coverage with configurable compliance scoring across languages, Insight7 delivers the most complete multilingual QA architecture. For Zendesk-native support teams, Zendesk QA activates without additional procurement. For engineering teams building custom stacks with strict data residency requirements, Speechmatics provides the strongest transcription foundation. The right choice depends on whether the program needs out-of-box QA scoring or a transcription layer for a custom build.