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Speech-To-Text

Call center transcription software: what enterprises should look for in 2026

TL;DR: Most contact centers evaluate transcription software using clean-audio lab benchmarks, then watch QA automation break down when BPO (Business Process Outsourcing) agents switch languages mid-call or phone-line noise degrades the signal. In 2026, the criteria that matter are real-world multilingual WER, all-inclusive per-hour pricing, and data sovereignty that holds up under GDPR and HIPAA audit. For enterprise teams, the highest-ROI evaluation step is testing on real BPO call samples rather than vendor demo audio, and asking every shortlisted provider for an all-in per-hour price with diarization, sentiment, and entity extraction enabled.

Speech-To-Text

PII redaction for call recordings: how ingestion-level redaction keeps calls PCI compliant

TL;DR: Legacy pause-and-resume systems don't remove agents, local desktops, or telephony infrastructure from PCI DSS audit scope. Automated, ingestion-level PII redaction scrubs sensitive data before it reaches any database. By removing cardholder data at the ingestion layer, contact center platforms using automated redaction can potentially reduce audit complexity, cut agent handle time (AHT), and protect downstream CRM and LLM pipelines from corrupt data. The accuracy floor for reliable entity detection in PCI audits is significantly higher than for standard QA transcription, making STT model selection a compliance decision as much as a product one.

Speech-To-Text

GDPR, SOC 2, and ISO 27001 speech-to-text: the contact center compliance and certification guide

TL;DR: When your contact center routes voice data through a transcription vendor, every certification gap in that vendor's stack becomes your compliance liability. Voice recordings qualify as personal data under GDPR Article 4, and processing them through uncertified APIs creates direct financial exposure. This guide breaks down what GDPR, SOC 2 Type II, ISO 27001, HIPAA, and PCI DSS each require of your audio infrastructure vendor and maps those requirements to the QA coverage rates and cost-per-contact metrics you manage daily. We hold GDPR, SOC 2 Type II, ISO 27001, HIPAA, and PCI DSS certifications, and never use customer audio for model training on Growth or Enterprise plan.

Ebook: Ultimate guide to using LLMs with speech recognition

Published on Jan 7, 2025
Ebook: Ultimate guide to using LLMs with speech recognition

Large Language Models (LLMs) have enabled businesses to build advanced AI-driven features, but navigating the many available models and optimization techniques isn't always easy.

If you’re looking to combine speech recognition (STT) and LLMs for cutting-edge voice apps, look no further! Our ultimate guide is finally here, and it’s filled with valuable strategies and hands-on insights from our work with hundreds of audio-first companies and extensive interviews with experts in AI note-taking, sales enablement and customer support.

What you'll learn:

  • The pros and cons of open-source vs proprietary models;
  • Best practices for optimizing LLM performance;
  • Key metrics and indicators to measure the success of STT systems;
  • A checklist for evaluating LLM and STT vendors for voice apps
  • ... and much more!
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