{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"gladia","slug":"gladia","name":"Gladia","type":"api","url":"https://www.gladia.io","page_url":"https://unfragile.ai/gladia","categories":["voice-audio"],"tags":[],"pricing":{"model":"usage-based","free":true,"starting_price":"$0.09/hr"},"status":"active","verified":false},"capabilities":[{"id":"gladia__cap_0","uri":"capability://data.processing.analysis.real.time.streaming.speech.to.text.with.sub.300ms.latency","name":"real-time streaming speech-to-text with sub-300ms latency","description":"WebSocket-based live transcription engine that converts audio streams to text with <300ms end-to-end latency, supporting continuous audio input without fixed context windows. Implements partial transcript delivery (<100ms) via a 'Partials' feature that streams intermediate results before final transcription is complete, enabling responsive UI updates and real-time user feedback during active speech.","intents":["Build live transcription into voice calls or meetings with minimal perceptible delay","Display intermediate transcription results to users as they speak for real-time feedback","Integrate transcription into WebSocket-based voice applications without polling","Support continuous audio streaming from telephony or WebRTC sources"],"best_for":["Voice AI agents and conversational interfaces (Pipecat, Vapi, Recall integrations)","Real-time meeting transcription platforms (LiveKit, VideoSDK, Twilio integrations)","Live captioning and accessibility applications","Telephony-integrated voice applications"],"limitations":["WebSocket connection required — no HTTP polling fallback documented","Partial transcripts may contain errors corrected in final output — requires UI handling for corrections","Concurrent connection limits vary by tier: 30 (Starter), Flexible (Growth), Unlimited (Enterprise)","Real-time processing does not include all audio intelligence features (diarization, translation, PII redaction latency unknown)"],"requires":["WebSocket client library (native browser WebSocket API or Node.js ws module)","Gladia API key (obtained from https://www.gladia.io)","Audio stream source (microphone, WebRTC peer connection, telephony stream, or file-based streaming)","Supported audio codec (specific codec list not documented — consult API reference)"],"input_types":["audio/raw PCM stream","audio/webm","audio/mp3","audio/wav","audio/ogg"],"output_types":["JSON with transcribed text, word-level timestamps, confidence scores","Partial transcript objects (intermediate results)","Language detection metadata"],"categories":["data-processing-analysis","real-time-streaming"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_1","uri":"capability://data.processing.analysis.asynchronous.batch.audio.transcription.with.file.upload","name":"asynchronous batch audio transcription with file upload","description":"HTTP-based async transcription API that accepts pre-recorded audio files (via file upload or URL), queues them for processing, and returns results via polling or webhook. Implements server-side processing with claimed 'no hallucinations' guarantee, supporting 100+ languages with automatic language detection and code-switching (mixed-language) handling within single files.","intents":["Transcribe recorded meetings, podcasts, or interviews in batch without real-time constraints","Process large audio archives with flexible concurrency limits","Integrate transcription into asynchronous workflows (CI/CD, scheduled jobs, background workers)","Support multi-language content with automatic language detection"],"best_for":["Content creators processing podcast/video libraries","Enterprise teams transcribing meeting recordings at scale","Developers building no-code automation (Zapier, Make, n8n integrations available)","Applications requiring batch processing with cost optimization (67% cheaper on Growth tier)"],"limitations":["Maximum file duration not documented — consult API reference for constraints","Processing time not specified — latency SLA unknown (only real-time SLA of <300ms documented)","Webhook support status unknown — polling may be required for result retrieval","Concurrency limits: 25 (Starter), Flexible (Growth), Unlimited (Enterprise) — Starter tier may bottleneck high-volume workloads","No built-in retry logic documented — client must implement exponential backoff"],"requires":["Gladia API key with Starter tier or higher","HTTP client library (curl, axios, requests, fetch)","Audio file in supported format (specific list not documented)","Polling mechanism or webhook endpoint for result retrieval"],"input_types":["audio file upload (multipart/form-data)","audio file URL (HTTP/HTTPS)","supported formats: WAV, MP3, WebM, OGG, FLAC (specific list incomplete)"],"output_types":["JSON with full transcription text","Word-level timestamps and confidence scores","Detected language code","Processing status and job ID for polling"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_10","uri":"capability://text.generation.language.audio.summarization.and.key.point.extraction","name":"audio summarization and key point extraction","description":"Post-transcription feature that generates abstractive or extractive summaries of transcribed content, condensing long audio into key points, action items, or executive summaries. Processes transcribed text to identify salient information and generate concise summaries without requiring manual review of full transcripts.","intents":["Generate executive summaries of long meetings for busy stakeholders","Extract action items and decisions from meeting transcripts","Create searchable summaries of podcast or video content","Reduce time spent reviewing lengthy call recordings"],"best_for":["Meeting intelligence and productivity platforms","Executive briefing and decision support systems","Content curation and podcast platforms","Knowledge management and documentation systems"],"limitations":["Summary length and style options not documented — unclear if configurable or fixed-length","Abstractive vs extractive approach not specified — unknown if generates new text or extracts existing phrases","Key point extraction format not documented — unclear how many points extracted or selection criteria","Accuracy and completeness not benchmarked — no metrics on summary quality","Language support for summarization not documented","Requires prior transcription — cannot summarize raw audio"],"requires":["Completed transcription from async or real-time endpoint","Gladia API key with audio intelligence features enabled","Minimum transcript length (threshold unknown)"],"input_types":["transcribed text","optional: speaker attribution and timestamps"],"output_types":["JSON with generated summary text","Key points list","Action items (if detected)","Summary length and compression ratio"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_11","uri":"capability://data.processing.analysis.automatic.language.detection.and.code.switching.support","name":"automatic language detection and code-switching support","description":"Transcription feature that automatically detects the language(s) spoken in audio and handles code-switching (mixing of multiple languages within single utterance or file). Solaria-1 model identifies language boundaries and switches recognition models or language contexts mid-stream, enabling accurate transcription of multilingual content without pre-specification of language.","intents":["Transcribe multilingual meetings where participants switch between languages","Process content from bilingual or multilingual regions without language pre-configuration","Support immigrant communities and international teams with mixed-language communication","Automatically detect language for content where language is unknown in advance"],"best_for":["International teams with multilingual participants","Regions with multiple official languages (Canada, Belgium, Singapore, etc.)","Immigrant communities and multicultural organizations","Global content platforms serving diverse language users"],"limitations":["Code-switching accuracy not benchmarked — no metrics on language boundary detection","Maximum number of languages per file not specified","Language pair compatibility unknown — may not support all language combinations equally","Latency impact of code-switching unknown — may add processing overhead vs single-language transcription","Language detection confidence not documented — unclear if confidence scores provided"],"requires":["Audio containing one or more of 100+ supported languages","Gladia API key (no special configuration required for code-switching)"],"input_types":["audio with single or multiple languages"],"output_types":["JSON with transcribed text","Detected language code(s)","Language boundaries and switching points","Per-segment language identification"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_12","uri":"capability://tool.use.integration.audio.to.llm.integration.and.structured.output.generation","name":"audio-to-llm integration and structured output generation","description":"Feature that connects transcribed audio output directly to large language models (LLMs) for downstream processing, enabling structured data extraction, question answering, or content generation from audio. Provides integration patterns for piping transcription results into LLM APIs (OpenAI, Anthropic, etc.) with optional structured output schemas (JSON, function calling).","intents":["Extract structured data from audio (e.g., meeting notes in JSON format)","Answer questions about audio content using LLM reasoning","Generate meeting minutes, summaries, or reports from transcription","Classify or categorize audio content using LLM-based analysis"],"best_for":["Developers building AI agents that process audio input","Meeting intelligence platforms generating structured outputs","Content analysis and classification systems","Conversational AI systems that need to understand audio context"],"limitations":["Integration method not documented — unclear if Gladia provides SDK helpers or requires manual API chaining","Supported LLM providers not specified — unknown which models/APIs are officially supported","Structured output schema support unknown — unclear if supports OpenAI function calling, JSON schema, or other formats","Latency of chained calls not optimized — sequential API calls (Gladia → LLM) add cumulative latency","Cost implications unknown — requires separate LLM API calls with additional per-token charges"],"requires":["Completed transcription from Gladia API","LLM API key (OpenAI, Anthropic, Cohere, etc.)","LLM integration library or manual HTTP client for chaining","Structured output schema definition (if using function calling)"],"input_types":["transcribed text from Gladia","optional: speaker attribution, timestamps, sentiment metadata"],"output_types":["LLM-generated structured data (JSON, function call results)","Natural language responses to questions about audio","Extracted entities, summaries, or classifications"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_13","uri":"capability://data.processing.analysis.automatic.chapterization.and.content.segmentation","name":"automatic chapterization and content segmentation","description":"Post-transcription feature that automatically segments long-form audio content into chapters or sections based on topic changes, speaker transitions, or temporal boundaries. Generates chapter markers with timestamps and optional titles, enabling navigation and content discovery in podcasts, audiobooks, or long meetings.","intents":["Create chapter markers for podcasts or audiobooks without manual editing","Enable users to jump to relevant sections in long audio content","Segment meeting recordings by topic or agenda item","Generate table of contents for audio content"],"best_for":["Podcast and audiobook platforms","Long-form content creators (YouTube, Spotify, Apple Podcasts)","Meeting recording platforms with content navigation","Educational platforms with lecture recordings"],"limitations":["Segmentation algorithm not documented — unclear if uses topic modeling, speaker changes, or other heuristics","Chapter title generation not specified — unknown if auto-generated or requires manual input","Minimum content length not specified — may not work well on short audio","Accuracy of chapter boundaries not benchmarked","Customization options unknown — unclear if chapter length or granularity is configurable","Requires prior transcription — cannot chapterize raw audio"],"requires":["Completed transcription from async or real-time endpoint","Gladia API key with audio intelligence features enabled","Long-form audio content (minimum length unknown)"],"input_types":["transcribed text with timestamps","optional: speaker attribution, sentiment data"],"output_types":["JSON with chapter boundaries and timestamps","Chapter titles (auto-generated or provided)","Chapter summaries (if available)","Chapter duration and word count"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_14","uri":"capability://automation.workflow.multi.tier.concurrency.and.rate.limiting.with.flexible.scaling","name":"multi-tier concurrency and rate limiting with flexible scaling","description":"API rate limiting and concurrency management system that varies by subscription tier: Starter tier (25 async, 30 real-time concurrent requests), Growth tier (flexible concurrency), and Enterprise tier (unlimited concurrency). Enables cost-conscious developers to start small and scale to unlimited throughput as demand grows, with transparent tier-based pricing ($0.61/hr Starter, $0.20/hr Growth, custom Enterprise).","intents":["Start transcription integration with low-cost Starter tier and scale to Growth/Enterprise as volume increases","Manage API costs by understanding concurrency limits and pricing per tier","Plan capacity for batch transcription workloads within tier constraints","Upgrade to Enterprise for unlimited concurrency without per-request rate limiting"],"best_for":["Startups and solo developers with low transcription volume","Growing companies scaling from Starter to Growth tier","Enterprise organizations with high-volume transcription needs","Cost-conscious teams optimizing transcription spend"],"limitations":["Starter tier concurrency limits (25 async, 30 real-time) may bottleneck high-volume workloads","Growth tier concurrency limits not specified — 'flexible' is vague without numeric thresholds","Rate limit headers and reset timing not documented","Burst capacity not specified — unclear if temporary spikes above concurrency limit are allowed","Retry logic and backoff strategies not documented","Tier upgrade process and effective date not specified"],"requires":["Gladia account with chosen tier (Starter, Growth, or Enterprise)","Understanding of concurrent request patterns for workload","HTTP client with retry logic for handling rate limit responses"],"input_types":["concurrent API requests within tier limits"],"output_types":["HTTP 429 (Too Many Requests) when concurrency limit exceeded","Rate limit headers (if documented)","Queued request processing within tier limits"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_15","uri":"capability://safety.moderation.zero.data.retention.and.gdpr.hipaa.compliance.options","name":"zero data retention and gdpr/hipaa compliance options","description":"Enterprise privacy feature that enables immediate deletion of audio files and transcripts after processing, with no data retention for model training or analytics. Available on Enterprise tier with explicit 'zero data retention' option, combined with GDPR/HIPAA compliance certifications (SOC 2 Type II) across all paid tiers. Enables privacy-sensitive use cases (healthcare, legal, financial) without data residency concerns.","intents":["Process sensitive healthcare data (HIPAA) without data retention liability","Comply with GDPR data minimization requirements for EU users","Transcribe confidential legal documents without long-term storage","Meet data privacy regulations in regulated industries"],"best_for":["Healthcare organizations processing patient data (HIPAA compliance)","Legal firms handling confidential client communications","Financial services processing customer data (PCI-DSS, SOX)","EU-based organizations subject to GDPR","Organizations with strict data retention policies"],"limitations":["Zero data retention only available on Enterprise tier — Starter/Growth tiers have unknown retention policies","Model training opt-out available on Growth and Enterprise — Starter tier may use data for training","Default training opt-out only on Enterprise — Growth tier requires explicit opt-out","EU data residency available but specific regions not documented","Data deletion timing not specified — unclear if immediate or within SLA","Audit trail and deletion confirmation not documented"],"requires":["Enterprise tier subscription for zero data retention","GDPR/HIPAA compliance requirements (available on Starter tier and above)","SOC 2 Type II certification verification (available on Starter tier and above)","Data Processing Agreement (DPA) for GDPR compliance (likely required)"],"input_types":["sensitive audio data (healthcare, legal, financial)"],"output_types":["Transcription results","Deletion confirmation (if documented)","Compliance certification (SOC 2 Type II, GDPR, HIPAA)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_2","uri":"capability://data.processing.analysis.speaker.diarization.and.segmentation","name":"speaker diarization and segmentation","description":"Post-transcription audio intelligence feature that identifies and segments distinct speakers within a single audio file, labeling transcript segments by speaker identity (Speaker 1, Speaker 2, etc.). Processes transcribed audio to assign speaker labels to word-level timestamps, enabling conversation analysis and multi-speaker meeting transcripts.","intents":["Generate meeting transcripts with speaker attribution for each statement","Analyze conversation dynamics by identifying who spoke when and for how long","Create searchable transcripts where users can filter by speaker","Support accessibility features that distinguish between multiple speakers"],"best_for":["Meeting transcription and recording platforms (LiveKit, VideoSDK, Recall integrations)","Interview and podcast transcription with multiple participants","Legal and compliance teams requiring speaker-attributed meeting records","Accessibility applications for multi-speaker content"],"limitations":["Diarization accuracy not documented — no benchmarks provided for speaker count or audio quality requirements","Maximum number of distinguishable speakers not specified","Requires prior transcription — cannot be run independently on raw audio","Latency impact unknown — whether diarization adds significant processing time to async transcription","Speaker identity not resolved to actual names — only numeric labels (Speaker 1, 2, etc.)"],"requires":["Completed transcription from async or real-time endpoint","Audio file with multiple distinct speakers","Gladia API key with audio intelligence features enabled"],"input_types":["transcribed audio with word-level timestamps"],"output_types":["JSON with speaker labels per transcript segment","Speaker turn boundaries with timestamps","Speaker-attributed transcript segments"],"categories":["data-processing-analysis","audio-intelligence"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_3","uri":"capability://safety.moderation.pii.redaction.and.sensitive.data.masking","name":"pii redaction and sensitive data masking","description":"Post-transcription content filtering that identifies and masks personally identifiable information (PII) categories within transcribed text, replacing detected PII with placeholder tokens or redaction markers. Operates on completed transcription output to sanitize sensitive data before downstream processing or storage.","intents":["Automatically redact credit card numbers, SSNs, or phone numbers from transcribed calls","Comply with data privacy regulations (GDPR, HIPAA) by removing PII before storage or sharing","Create shareable transcripts with sensitive information masked for non-authorized users","Reduce data retention liability by removing PII from transcription records"],"best_for":["Healthcare and HIPAA-regulated organizations transcribing patient calls","Financial services processing customer support recordings","Legal firms handling confidential client communications","Contact centers requiring PII-safe transcript storage and sharing"],"limitations":["Specific PII categories redacted not documented (e.g., credit card, SSN, phone, email, address) — consult API reference","Redaction accuracy not specified — false positive/negative rates unknown","Redaction format not documented — unclear if replaced with [REDACTED], [PII], or other markers","Context-aware redaction unknown — may not distinguish between PII in different contexts (e.g., 'John' as name vs common word)","Requires prior transcription — cannot be applied to raw audio"],"requires":["Completed transcription from async or real-time endpoint","Gladia API key with audio intelligence features enabled","GDPR/HIPAA compliance requirements (available on Starter tier and above)"],"input_types":["transcribed text with word-level metadata"],"output_types":["JSON with redacted transcript text","Redaction metadata (location, category, confidence)","Original and redacted versions for audit trails"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_4","uri":"capability://text.generation.language.audio.translation.to.target.languages","name":"audio translation to target languages","description":"Post-transcription translation feature that converts transcribed text from source language to specified target language(s), enabling multilingual content distribution. Operates on completed transcription to produce translated text while preserving word-level timestamps and speaker attribution from original transcription.","intents":["Translate meeting transcripts to multiple languages for international teams","Create localized versions of podcast or video content for different markets","Support multilingual accessibility by providing transcripts in user's preferred language","Enable global content distribution without re-recording in multiple languages"],"best_for":["International teams with multilingual participants","Content creators distributing to global audiences","Enterprise organizations with cross-border operations","Accessibility platforms serving multilingual users"],"limitations":["Target language list not documented — unclear which languages are supported for translation","Translation quality not specified — no benchmarks or accuracy metrics provided","Latency impact unknown — whether translation adds significant processing time","Timestamp preservation unclear — may not align translated text with original audio timing","Requires prior transcription — cannot translate raw audio directly"],"requires":["Completed transcription from async or real-time endpoint","Target language specification (language code or name)","Gladia API key with audio intelligence features enabled"],"input_types":["transcribed text in source language"],"output_types":["JSON with translated text","Language code for target language","Preserved timestamps and speaker attribution"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_5","uri":"capability://data.processing.analysis.automatic.subtitle.generation.with.timestamps","name":"automatic subtitle generation with timestamps","description":"Post-transcription feature that generates subtitle files (SRT, VTT, or similar formats) with word-level timestamps and speaker labels, enabling video/audio content to be captioned. Converts transcribed text and timing metadata into standard subtitle formats compatible with video players and streaming platforms.","intents":["Generate SRT/VTT subtitle files for video content without manual timing","Add captions to video uploads on YouTube, Vimeo, or other platforms","Create accessible video content for deaf and hard-of-hearing users","Enable searchable video content through indexed captions"],"best_for":["Video content creators and producers","Accessibility teams adding captions to video libraries","Streaming platforms (YouTube, Vimeo, Twitch) integrations","Educational content creators"],"limitations":["Subtitle format options not documented — unclear if SRT, VTT, WebVTT, or other formats supported","Line break and character limit handling not specified — may not optimize for readability on different screen sizes","Speaker label inclusion in subtitles unclear — may not distinguish speakers in output","Styling options unknown — no information on font, color, positioning customization","Requires prior transcription — cannot generate subtitles from raw audio"],"requires":["Completed transcription with word-level timestamps","Gladia API key with audio intelligence features enabled","Video file or duration information for timing alignment"],"input_types":["transcribed text with word-level timestamps"],"output_types":["SRT subtitle file","VTT subtitle file","WebVTT with styling metadata","JSON with subtitle segments and timings"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_6","uri":"capability://data.processing.analysis.custom.vocabulary.injection.for.domain.specific.terms","name":"custom vocabulary injection for domain-specific terms","description":"Pre-transcription configuration feature that injects domain-specific vocabulary, acronyms, or proper nouns into the Solaria-1 model's recognition pipeline, improving accuracy for specialized terminology. Accepts custom word lists or phrase mappings that bias the model toward recognizing specific terms with higher confidence, reducing misrecognition of technical jargon.","intents":["Improve transcription accuracy for medical terminology in healthcare recordings","Correctly recognize company names, product names, and brand terminology","Handle technical jargon and acronyms specific to industry or domain","Reduce post-transcription manual corrections for specialized vocabulary"],"best_for":["Healthcare organizations transcribing medical terminology","Legal firms handling specialized legal vocabulary","Technical teams transcribing engineering or IT discussions","Enterprise organizations with proprietary terminology"],"limitations":["Custom vocabulary format not documented — unclear if accepts word lists, phonetic spellings, or phrase mappings","Maximum vocabulary size not specified — may have limits on number of custom terms","Phonetic guidance unclear — unknown if supports IPA, ARPABET, or other phonetic notation","Confidence impact not quantified — no metrics on accuracy improvement from custom vocabulary","Requires configuration before transcription — cannot be applied retroactively to completed transcriptions"],"requires":["Gladia API key with custom vocabulary feature enabled (tier level unknown)","Custom vocabulary list (format and structure not documented)","Audio content containing the custom terms for effective use"],"input_types":["word list (plain text, CSV, or JSON format)","phrase mappings (term → preferred spelling)","phonetic guidance (format unknown)"],"output_types":["Transcription with improved accuracy for custom terms","Confidence scores reflecting custom vocabulary weighting"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_7","uri":"capability://data.processing.analysis.custom.spelling.rules.and.phonetic.normalization","name":"custom spelling rules and phonetic normalization","description":"Post-transcription text normalization feature that applies custom spelling rules, phonetic mappings, or abbreviation expansions to transcribed text. Enables standardization of variant spellings, acronym expansion, and domain-specific spelling conventions without re-transcribing audio.","intents":["Standardize variant spellings (e.g., 'color' vs 'colour') across transcripts","Expand acronyms to full forms (e.g., 'CEO' → 'Chief Executive Officer')","Apply domain-specific spelling conventions (e.g., medical abbreviations)","Normalize phonetic variations in proper nouns or brand names"],"best_for":["Content teams standardizing transcripts for consistency","Organizations with specific spelling or style guides","Multilingual teams handling variant spellings across regions","Accessibility platforms normalizing text for screen readers"],"limitations":["Rule format and syntax not documented — unclear how to specify custom rules","Context-awareness unknown — may not distinguish between different meanings of same word","Performance impact not specified — latency of rule application unknown","Requires prior transcription — cannot be applied during transcription","Rule complexity limits unknown — no information on regex support or conditional rules"],"requires":["Completed transcription from async or real-time endpoint","Custom spelling rules (format not documented)","Gladia API key with custom spelling feature enabled"],"input_types":["transcribed text","spelling rule definitions (format unknown)"],"output_types":["JSON with normalized transcript text","Mapping of original → normalized terms"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_8","uri":"capability://data.processing.analysis.named.entity.recognition.ner.extraction","name":"named entity recognition (ner) extraction","description":"Post-transcription NLP feature that identifies and extracts named entities (persons, organizations, locations, dates, etc.) from transcribed text, tagging them with entity type and confidence scores. Enables structured data extraction from unstructured transcription output for downstream processing, search indexing, or knowledge base population.","intents":["Extract company names, people names, and locations mentioned in meetings for CRM integration","Identify dates and action items from meeting transcripts for calendar/task management","Build searchable entity indexes from large transcription corpora","Populate knowledge bases with extracted entities from interview or podcast content"],"best_for":["Meeting intelligence and CRM integration platforms","Knowledge management and content indexing systems","Interview and research analysis tools","Compliance and audit teams extracting key entities from recordings"],"limitations":["Entity types supported not documented — unclear if includes PERSON, ORG, LOC, DATE, MONEY, etc.","Accuracy and confidence thresholds not specified — no benchmarks provided","Context-awareness unknown — may not distinguish between entity types in ambiguous cases","Language support for NER not documented — may differ from transcription language support","Requires prior transcription — cannot extract entities from raw audio"],"requires":["Completed transcription from async or real-time endpoint","Gladia API key with audio intelligence features enabled"],"input_types":["transcribed text"],"output_types":["JSON with extracted entities","Entity type classification (PERSON, ORG, LOC, DATE, etc.)","Confidence scores per entity","Character offsets for entity location in original text"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__cap_9","uri":"capability://data.processing.analysis.sentiment.analysis.and.emotion.detection","name":"sentiment analysis and emotion detection","description":"Post-transcription feature that analyzes emotional tone and sentiment polarity (positive, negative, neutral) of transcribed speech segments, potentially with speaker-level granularity. Processes transcribed text and optionally audio features to classify sentiment and assign confidence scores, enabling conversation analytics and customer satisfaction measurement.","intents":["Measure customer satisfaction from support call transcripts","Identify emotional escalation or de-escalation in conversations","Analyze sentiment trends across multiple meetings or calls","Flag high-priority interactions based on negative sentiment for follow-up"],"best_for":["Contact center analytics and quality assurance teams","Customer experience and NPS measurement platforms","Sales and negotiation analysis tools","Mental health and therapy session analysis"],"limitations":["Sentiment output format not documented — unclear if returns scores (-1 to 1), labels (positive/negative/neutral), or probabilities","Granularity unknown — whether sentiment is per-segment, per-speaker, or per-utterance","Emotion categories not specified — unclear if includes anger, joy, frustration, etc. beyond sentiment polarity","Sarcasm and context handling unknown — may not detect sarcasm or context-dependent sentiment","Language support for sentiment analysis not documented — may differ from transcription languages","Requires prior transcription — cannot analyze sentiment from raw audio"],"requires":["Completed transcription from async or real-time endpoint","Gladia API key with audio intelligence features enabled"],"input_types":["transcribed text","optional: speaker attribution from diarization"],"output_types":["JSON with sentiment classification per segment","Sentiment scores (format unknown)","Confidence scores","Optional: speaker-level sentiment aggregation"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gladia__headline","uri":"capability://voice.audio.enterprise.audio.transcription.api","name":"enterprise audio transcription api","description":"Gladia is an enterprise-level audio transcription API that offers real-time streaming, speaker diarization, and supports over 100 languages with zero data retention, making it ideal for businesses needing accurate and secure transcription services.","intents":["best audio transcription API","audio transcription API for real-time use","top audio transcription services for enterprises","audio transcription solutions for multiple languages","best API for speaker diarization"],"best_for":["enterprises needing high accuracy"],"limitations":[],"requires":["API key for authentication"],"input_types":["audio files"],"output_types":["transcribed text"],"categories":["voice-audio"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":58,"verified":false,"data_access_risk":"high","permissions":["WebSocket client library (native browser WebSocket API or Node.js ws module)","Gladia API key (obtained from https://www.gladia.io)","Audio stream source (microphone, WebRTC peer connection, telephony stream, or file-based streaming)","Supported audio codec (specific codec list not documented — consult API reference)","Gladia API key with Starter tier or higher","HTTP client library (curl, axios, requests, fetch)","Audio file in supported format (specific list not documented)","Polling mechanism or webhook endpoint for result retrieval","Completed transcription from async or real-time endpoint","Gladia API key with audio intelligence features enabled"],"failure_modes":["WebSocket connection required — no HTTP polling fallback documented","Partial transcripts may contain errors corrected in final output — requires UI handling for corrections","Concurrent connection limits vary by tier: 30 (Starter), Flexible (Growth), Unlimited (Enterprise)","Real-time processing does not include all audio intelligence features (diarization, translation, PII redaction latency unknown)","Maximum file duration not documented — consult API reference for constraints","Processing time not specified — latency SLA unknown (only real-time SLA of <300ms documented)","Webhook support status unknown — polling may be required for result retrieval","Concurrency limits: 25 (Starter), Flexible (Growth), Unlimited (Enterprise) — Starter tier may bottleneck high-volume workloads","No built-in retry logic documented — client must implement exponential backoff","Summary length and style options not documented — unclear if configurable or fixed-length","builder identity is not verified yet","no observed match outcomes 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