List of Deepgram Speech to Text Customers
San Francisco, 94104, CA,
United States
Since 2010, our global team of researchers has been studying Deepgram Speech to Text customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Deepgram Speech to Text for Speech Recognition AI from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Deepgram Speech to Text for Speech Recognition AI include: CallTrackingMetrics, a United States based Professional Services organisation with 81 employees and revenues of $30.0 million, Sharpen Technologies, a United States based Professional Services organisation with 120 employees and revenues of $16.0 million, Max Contact, a United Kingdom based Professional Services organisation with 100 employees and revenues of $10.0 million and many others.
Contact us if you need a completed and verified list of companies using Deepgram Speech to Text, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Deepgram Speech to Text customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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CallTrackingMetrics | Professional Services | 81 | $30M | United States | Deepgram | Deepgram Speech to Text | Speech Recognition AI | 2025 | n/a |
In 2025, CallTrackingMetrics deployed Deepgram Speech to Text in their AWS VPC to raise transcription accuracy above 90%. Deepgram Speech to Text is a Speech Recognition AI used to improve conversation analytics for marketing attribution and contact-center workflows at CallTrackingMetrics.
The implementation embedded real-time and batch transcription capabilities into the companys US marketing and CRM deployment, delivering faster transcripts and higher accuracy for conversation intelligence pipelines. Configuration emphasized Deepgram Speech to Text transcription models and an ingestion pipeline that fed transcripts into CallTrackingMetrics analytics engines for attribution and contact routing insights. The deployment structure in the AWS VPC preserved cloud boundary control while enabling low-latency processing for contact-center workflows.
Operational scope centered on marketing and CRM teams across the United States, with transcripts routed into marketing attribution workflows and contact-center analytics to support campaign measurement and agent workflows. Governance activities included configuring data flows and transcript handling inside the AWS VPC and updating conversation analytics processes to consume higher fidelity text. According to the vendor case study this approach improved analytics quality and reduced costs for customers by delivering faster, more accurate transcripts.
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Max Contact | Professional Services | 100 | $10M | United Kingdom | Deepgram | Deepgram Speech to Text | Speech Recognition AI | 2024 | n/a |
In 2024, MaxContact integrated Deepgram Speech to Text into its cloud contact-centre platform, establishing a Speech Recognition AI capability to support compliance, agent coaching, and analytics. The deployment targeted MaxContact's UK contact-center and CRM space and positioned Deepgram Speech to Text as the central transcription engine for voice interaction capture and analysis.
The implementation configured Deepgram Speech to Text to deliver high-fidelity transcriptions that feed the companys speech analytics and quality assurance workflows. Functional capabilities implemented included automated transcription for compliance review, transcript indexing for analytics, and transcript-based inputs to agent training processes, with configuration focused on accuracy and throughput rather than on-premise infrastructure.
Deepgram Speech to Text was integrated with MaxContacts cloud contact-centre platform and CRM systems to populate analytics pipelines and compliance repositories, enabling faster insight delivery to customers. Operational governance was adjusted to incorporate transcript review and analytics-driven coaching workflows, and the rollout covered the UK contact-center operational footprint. The program resulted in materially higher transcription accuracy and faster insights for customers, improving compliance monitoring, agent training, and analytics readiness.
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Sharpen Technologies | Professional Services | 120 | $16M | United States | Deepgram | Deepgram Speech to Text | Speech Recognition AI | 2021 | n/a |
In 2021, Sharpen Technologies implemented Deepgram Speech to Text, a Speech Recognition AI solution, as part of a US-based contact-center and CRM use case. The deployment targeted improved automated transcription quality to support supervisors, quality assurance, and operations workflows across agent coaching and compliance.
Deepgram Speech to Text was configured to deliver both real-time streaming transcription and post-call processing, and Sharpen trained custom models to capture customer-specific vocabularies. Functional capabilities implemented included verbatim transcriptions for QA sampling, live transcription for supervisor coaching and compliance monitoring, and transcript feeds for real-time analytics and operational reporting.
The implementation integrated transcription outputs into Sharpen’s contact center and CRM workflows to route transcripts into coaching systems, compliance review queues, and analytics dashboards, positioning speech-to-text as a primary data source for agent performance and operational insight. According to the vendor case study the rollout yielded an immediate, significant improvement in transcription accuracy and the ability to train custom models for customer-specific vocabularies.
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