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How contact center AI improves efficiency: benchmarks and ROI
TL;DR: Manual QA teams review 1–5% of contact center calls; AI-powered platforms can score all of them, but only when the underlying transcript is accurate. WER and DER are the hidden bottlenecks: a wrong name, missed compliance phrase, or misattributed speaker corrupts every downstream system that reads the transcript, from routing and agent assist to post-call summaries and QA scoring. Our Solaria-1 model delivers on average 29% lower WER than alternatives on conversational speech and on average 3x lower DER (diarization error rate), covers 100+ languages including 42 that no other STT API supports, and handles the full audio pipeline (record, transcribe, enrich) in a single API.
How to integrate AI into contact center performance monitoring
TL;DR: Most contact centers manually review only a small fraction of calls, leaving compliance breaches and coaching signals undetected. Scaling to 100% AI QA coverage means choosing between three integration patterns (CCaaS-native tools, add-on API layers, or a custom build), each determined by how well your speech infrastructure handles noisy, multilingual audio. For post-call monitoring, async batch transcription outperforms real-time on accuracy, diarization quality, and cost predictability at scale. The bottleneck is getting a reliable transcript from noisy call center audio, which is where Solaria-1 and all-inclusive per-hour pricing matter most.
AI solutions for call centers without human translators
TL;DR: At an illustrative fully loaded offshore rate of $6–$15/hr, replacing BPO translation at 10,000 hours/month with Gladia's Growth plan brings the estimated cost from $80,000–$150,000 down to approximately $2,000/month, with diarization, translation, NER, and sentiment included at the base rate. Every downstream output is ceiling-bounded by STT accuracy: a single transcription error produces a wrong translation, a wrong CRM entry, and a wrong coaching score. Native code-switching support is the bottleneck most teams discover only in production. Solaria-1 covers 100+ languages, including 42 not available on any other STT API, with mid-conversation code-switching built in from day one.
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?
