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How decision intelligence improves customer service consistency in contact centers
TL;DR: Contact centers fail to deliver consistent service when routing infrastructure runs on static rules engines that cannot handle the complexity of real human conversation. Modern speech-to-text infrastructure addresses this by processing raw audio and feeding structured outputs to your CRM, using machine learning to analyze intent, sentiment, and speaker characteristics. Transcription accuracy sets the ceiling for every downstream action: a wrong word silently corrupts a CRM entry, a missed intent misfires a routing decision, and a misread sentiment score delays escalation. This playbook covers how to build and deploy that architecture without blowing your latency budget or your unit economics.
TL;DR: Live agent assist only works when the transcription layer delivers partial results fast enough for downstream NLP to process within a sub-second window. If the pipeline exceeds 1,000ms total, prompts arrive after agents have already spoken, which inflates Average Handle Time and erodes agent trust. This playbook covers the full real-time pipeline architecture, from streaming transcription through intent analysis to agent desktop rendering, and shows how contact centers can expand QA coverage from a 1-3% manual sample to 100% of interactions without adding headcount.
How to identify prospect companies from sales call transcripts
TL;DR: Most product teams try to run LLM extraction on raw, undiarized transcripts and end up with CRM records polluted by the sales rep's own company names, tools, and competitor mentions. The fix is an async-first pipeline that separates speaker dialogue before any entity extraction happens. This guide walks through a working Python and Claude API pipeline using our async transcription, pyannoteAI Precision-2 diarization, and Solaria-3 or Solaria-1 depending on your language mix, so you extract clean prospect-side signals and sync accurate data to your CRM.
How VEED is streamlining video editing and subtitles with AI transcription
Published on Jul 25, 2024
User-generated content has become a cornerstone of the internet-driven economy. As part of this shift, various platforms have emerged to provide easy-to-use tools to create high-quality video content in a matter of minutes — with AI transcription playing a foundational role in their product development.
VEED is one of the leading AI video editor platforms today, relying on Gladia’a transcription API to empower video content creators around the globe. Read on to find out which features they improved thanks to our API and the impact of speech-to-text on VEED’s roadmap, user engagement, and growth.
About Veed
VEED was founded in 2018 by Sabba Keynejad and Tim Mamedov with the aim of democratizing the visual content industry. To deliver on that vision, the company offers a video recording and editing platform that enables anyone to create high-quality video content in minutes without specialized skills.
Originally designed for individual content creators, VEED is currently expanding into the B2B segment, providing its services to communication professionals and the like.
With a staggering 10M active monthly users on its platform uploading one video every second, the company is delivering new features and expanding its user base across geographies.
Preview of VEED
Challenge
The ability to roll out new, value-adding features as part of its core offer, is among top strategic priorities for platforms like VEED when it comes to user acquisition and engagement.
Among the core VEED features today are automatic subtitles, eye contact AI and editing tools like Magic Cut and Silence Removal. The editing toolkit allows users to automatically remove errors, pauses, and repetitive words from raw footage in a single click, transforming long, imperfect footage into short, punchy edits optimized for social channels.
All these features rely on Transcription as their core, so having an accurate, reliable provider capable of transcribing speech across languages was key.
The issue they encountered, however, was that a lot of existing alternatives didn’t provide satisfactory results on non-English languages based on internal benchmarks run by the VEED team to assess API providers.
Requirements
In this context, VEED was looking to deploy a high-quality transcription and audio intelligence API to integrate with its platform, based on the following specifications:
Accurate and fast transcription API, capable of handling large volumes of audio transcription at a scalable cost.
Language recognition and transcription beyond English, to serve the platform’s expanding global user base in countries like India, the Philippines, Brazil, Germany, and so on.
Top-level precision for word-level timestamps, with the start and end times of each word, detected perfectly, being an essential pre-requisite for video editing and subtitles generation.
Audio enhancement features, like the ability to remove background noise as part of the integration to improve the quality of transcription.
Customer support, including SALs and a dedicated Slack channel to address issues in real time and provide custom guidance.
Data security and compliance, such as SOC2, especially as the company expands into the B2B target segment with more stringent data requirements.
Solution
Enter Gladia! With Gladia, the VEED team was able to implement:
Subtitles in 21 languages with timestamps, generated in a matter of seconds, with a confidence score designed for users to review and edit if they need.
AI-powered editing tools, which remove silences, filler words, and repetitions in a video based on the time-stamped transcript to streamline the editing process
Auto Subtitles by VEED
Impact & ROI
By working with the Gladia team to iterate and scale up, VEED’s team saw a noticeable impact on their own customers, from users praising the quality of the transcription to prospects converting specifically after trying it out.
The team at VEED is continuing to explore the possibilities that transcription brings to their AI product, and is now considering how they will leverage it in the future with upcoming features requiring advanced multilingual transcription and metadata extraction.
We're thrilled to be part of this amazing journey with them, and thank VEED for putting their trust in us! We look forward to partnering with more customers to tackle new challenges, and make speech AI more accessible to media companies worldwide.
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?
