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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.
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.
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.
AI-powered healthcare assistant enhances medical transcription by 120% with Gladia
Published on Feb 28, 2025
Medical transcription is among the most critical and challenging verticals for ASR models to date.
Filled with drug names and medical jargon, medical consultations, dictations, and online conferences require versatile solutions, with custom vocabulary and specialized models needed to make speech-to-text solutions attuned to jargon. There’s the issue of security too, as audio from medical consultations is among the most sensitive confidential data out there.
A fast-growing healthcare generative AI startup, who prefers to remain anonymous, turned to Gladia for top-quality medical transcription at scale. Here’s how we helped them increase their accuracy and speed of transcription, all while ensuring 100% security of confidential user data.
Challenge
Doctors spend about 60% of their time on computers, doing non-clinical work. This startup is aiming to get that number to 15%, enabling doctors to allocate most of their time for consultation, diagnostics, and other high-value tasks with the help of AI.
They knew that having accurate transcription for note-taking during consultations was the first step in designing a holistic solution to achieve this milestone.
Indeed, the platform’s ability to understand and actively transcribe jargon-filled medical conversations is an essential prerequisite for LLM-powered notes, prescriptions, and intricate EHR enrichment that distinguish their AI co-pilot.
Speed is likewise a key factor for them, as the ability to generate notes shortly after the consultation is critical for efficient clinical workflows.
Moreover, they needed to ensure 100% protection of all user data in accordance with HIPAA and GDPR, which most of the US-based providers are generally not able to provide.
This is why their team took the task of choosing a speech-to-text provider very seriously. With regular evaluations in place, they have tested over 7 different providers before, including the Big Tech cloud solutions — all of which ultimately failed to strike the right balance between accuracy, speed, price, and security standards.
Following a swift onboardingwith our tech team, they began to use Gladia as its primary speech-to-text provider. The results did not take long to show.
By working with the Gladia team to iterate and scale up, they saw a noticeable impact on their system’s performance:
The team was likewise impressed by the quality of Gladia’s technical assistance, allowing them to not only set up their dedicated environment in a matter of hours but also benefit from Gladia’s in-house engineering expertise to optimize their infrastructure as a whole.
Given the initial success with Gladia API and its on-premise deployment, this innovative company is already considering how they will leverage our product in the future as they extend their platform to new stakeholders.
For instance, they look forward to experimenting more with multilingual transcription and translation, which would enable patients to consult physicians in their native language. They also intend to leverage speaker diarization for collective medical meetings.
About Gladia
Gladia provides a speech-to-text and audio intelligence API for building virtual meeting and note-taking apps, call center platforms, and media products, providing transcription, translation, and insights powered by best-in-class ASR, LLMs and GenAI models.
Having read this case study, do you feel like Gladia could be the right fit for your business too?
