February 2026 Summaries

PII redaction in speech-to-text processes is a crucial practice for ensuring compliance and protecting sensitive personal data from legal, financial, and reputational risks. It involves automatically detecting and replacing personally identifiable information (PII) such as names, addresses, and financial data in audio transcripts, thus preventing these details from being stored in databases in plain text. This practice is essential for adhering to regulations like GDPR, HIPAA, PCI DSS, and CCPA, which mandate strict handling of personal data. Unredacted transcripts pose significant security risks as they can become high-value targets if databases are compromised. Modern systems employ techniques like Named Entity Recognition (NER) for entity detection, and offer various redaction methods including full removal, category tagging, and partial masking. Companies like Gladia provide tools to implement PII redaction, allowing businesses to tailor their redaction processes to meet specific regulatory requirements while maintaining the integrity and usefulness of the data for analysis.

AssemblyAI has established itself as a prominent platform in the speech-to-text and audio intelligence space, catering to over 5,000 customers with millions of API calls processed daily. Known for its accurate transcription and advanced audio intelligence features, the platform offers a unique framework for applying Large Language Models (LLMs) to speech, making it suitable for developers and enterprises requiring comprehensive voice AI capabilities. While AssemblyAI excels in providing deep audio analysis and enterprise-grade compliance, it has limitations in real-time multilingual streaming and modular pricing complexity. In contrast, Gladia, a newer entrant in the market, focuses on multilingual transcription and audio intelligence, offering over 100 languages for real-time and pre-recorded audio with an all-inclusive pricing model. Founded by Jean-Louis Queguiner and Jonathan Soto, Gladia aims to remain a pure-play speech AI provider, avoiding competition with clients' conversational AI products. The choice between AssemblyAI and Gladia depends on specific needs, such as advanced audio analysis and LLM integration versus broad multilingual support and pricing transparency.

In 2026, the choice between Deepgram and Gladia for speech-to-text API services hinges on user needs and priorities, whether they favor a comprehensive voice AI platform or high-accuracy transcription with robust multilingual support. Deepgram, a US-based platform, offers an extensive suite of voice AI solutions, including text-to-speech and a unified Voice Agent API, making it ideal for teams seeking to build end-to-end voice solutions, particularly for English-speaking markets. It focuses on providing flexibility, custom model training, and on-premise deployment options, though its modular pricing for additional features like speaker diarization could increase costs for users needing comprehensive audio analysis. In contrast, Gladia, a European startup, emphasizes transcription accuracy and developer experience, offering a real-time-first architecture with strong multilingual capabilities for over 100 languages and code-switching. Gladia’s pricing model is straightforward, inclusive of all audio intelligence features without add-ons, and aligns with privacy-conscious users by ensuring no customer data is used for model training on paid plans. While Deepgram’s platform is suited for those requiring a broad voice AI infrastructure, Gladia appeals to teams needing high-accuracy, real-time transcription, especially in international or GDPR-compliant contexts.

Deepgram is a versatile voice AI platform offering speech-to-text, text-to-speech, and conversational AI capabilities, appealing to enterprises looking to build voice-enabled applications. Founded in 2015 by former physicists from the University of Michigan, Deepgram uses an end-to-end broad learning architecture and has garnered significant funding from major investors like NVIDIA and Y Combinator. The platform's strengths include a unified API for voice AI applications, custom model training for industry-specific needs, and flexible deployment options. However, it may not be the best choice for those needing transcription in more than 40 languages or seeking a focused speech-to-text solution without the added platform complexity. In comparison, Gladia offers a specialized approach to speech AI, focusing on transcription and audio intelligence with support for over 100 languages and robust multilingual capabilities. While Deepgram provides a comprehensive suite for those requiring an integrated voice AI solution, Gladia's emphasis on precision and privacy makes it a preferred choice for multilingual transcription needs and privacy-conscious organizations. The decision between the two platforms depends on whether the user needs the extensive features of Deepgram's full voice AI suite or the specialized, multilingual focus of Gladia.

As the speech-to-text market diversifies, businesses seek alternatives to Deepgram that better align with specific needs, such as broader language coverage, data privacy, or cost efficiency through self-hosting. Gladia offers extensive multilingual transcription with real-time code-switching across over 100 languages and configurable privacy controls, making it ideal for global applications. AssemblyAI provides comprehensive audio intelligence and LLM integration for advanced speech understanding, while Speechmatics excels in on-premise solutions and healthcare-specific models. Rev.ai caters to small teams needing affordable transcription with human accuracy guarantees, and AWS Transcribe integrates seamlessly with existing AWS infrastructure. OpenAI Whisper offers a cost-effective self-hosted solution for teams with infrastructure expertise, and Soniox delivers real-time translation across 60+ languages without a latency penalty. These alternatives cater to organizations with specific requirements that may not align with Deepgram’s offerings, allowing them to choose based on language support, deployment needs, and budget constraints.

Deepgram, a leading player in the speech-to-text industry, is renowned for its real-time streaming, batch processing, and audio intelligence features, but its focus may not align with all organizations' specific needs. As the demand for speech AI becomes more specialized, alternatives to Deepgram, such as Gladia, AssemblyAI, Speechmatics, Rev.ai, AWS Transcribe, OpenAI Whisper, and Soniox, offer tailored solutions to meet diverse business requirements. These alternatives provide features like extensive multilingual transcription, LLM integration for audio insights, on-premise deployment for regulated industries, affordable transcription with human accuracy guarantees, seamless AWS ecosystem integration, self-hosted models for cost reduction, and real-time translation across numerous language pairs. The emphasis is on finding the right fit for unique business needs, with some organizations potentially employing multiple solutions alongside Deepgram to address varied use cases effectively.

AssemblyAI and Gladia offer distinct approaches to speech-to-text and audio intelligence services, each with unique pricing structures and features that appeal to different user needs. AssemblyAI provides a granular, pay-as-you-go model that allows users to choose specific audio intelligence features as add-ons, making it ideal for those seeking cost optimization and mature LLM integrations like LeMUR. However, its pricing can become complex when multiple features are enabled, and real-time language support is limited to six languages. In contrast, Gladia's approach emphasizes transparent, inclusive pricing that bundles essential features like speaker diarization and language detection into its base rates, supporting over 100 languages with real-time code-switching. This makes Gladia appealing for users who prefer predictable costs and robust multilingual capabilities. Both platforms offer free tiers for initial testing, but Gladia's emphasis on data privacy without pricing penalties and its focus on being a speech AI infrastructure provider rather than a broader Voice AI platform differentiate it from AssemblyAI. The choice between the two depends on the user's preferences for pricing transparency, feature inclusivity, multilingual support, and data privacy.

In a comprehensive comparison of Deepgram and Gladia, the article delves into the intricacies of their pricing structures and strategic directions for speech-to-text services. Deepgram, a full-stack voice AI platform, offers a credit-based pricing system with additional charges for features like speaker diarization and audio intelligence, making it ideal for teams seeking a unified API stack for voice applications. However, its pricing can be complex, and its focus on expanding into other voice AI areas might dilute its core transcription quality. Conversely, Gladia provides transparent, all-inclusive per-hour pricing with features such as speaker diarization and support for over 100 languages included, making it appealing for teams prioritizing predictable costs and extensive multilingual support. Gladia remains focused solely on transcription and audio intelligence, ensuring that it doesn't compete with clients building their own voice agents. While Deepgram's one-time $200 free credit is beneficial for initial testing, Gladia's ongoing 10 free hours monthly caters to teams with continuous low-volume needs. The choice between the two depends on whether a team is looking for a comprehensive voice AI solution with potential competitive overlap (Deepgram) or a specialized transcription partner with clear pricing and privacy assurances (Gladia).