{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"deepgram-api","slug":"deepgram-api","name":"Deepgram API","type":"api","url":"https://deepgram.com","page_url":"https://unfragile.ai/deepgram-api","categories":["voice-audio"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":"$0.0043/min"},"status":"active","verified":false},"capabilities":[{"id":"deepgram-api__cap_0","uri":"capability://data.processing.analysis.streaming.speech.to.text.transcription.with.real.time.processing","name":"streaming-speech-to-text-transcription-with-real-time-processing","description":"Converts live audio streams to text via WebSocket (WSS) protocol with ultra-low latency processing. Deepgram's Flux models process audio chunks incrementally, detecting natural speech boundaries and returning partial transcripts in real-time without waiting for audio completion. Supports 150-225 concurrent WebSocket connections depending on tier, enabling high-throughput voice applications.","intents":["I need to transcribe live phone calls or voice conversations as they happen","I want to build a real-time voice assistant that responds to user speech immediately","I need to process multiple concurrent audio streams from different users simultaneously","I want to detect when a speaker finishes talking to trigger downstream LLM processing"],"best_for":["voice agent developers building conversational AI","contact center platforms requiring live call transcription","teams building real-time meeting transcription tools"],"limitations":["WebSocket connections limited to 150 concurrent (free/pay-as-you-go) or 225 (Growth tier) — scaling beyond requires multiple API keys or tier upgrade","Latency metrics not publicly specified — 'ultra-low latency' is marketing claim without SLA guarantees","Audio format support and sample rate constraints not documented","No built-in persistence — transcripts must be captured and stored by client application"],"requires":["API key from Deepgram (free tier includes $200 credit with no expiration)","WebSocket client library (native browser WebSocket or Node.js ws module)","Audio input source (microphone, audio stream, or hardware device)","Network connectivity with WSS (secure WebSocket) support"],"input_types":["audio/stream (real-time PCM or compressed audio)","audio/raw (raw audio bytes)"],"output_types":["JSON (partial and final transcripts with confidence scores)","structured metadata (speaker identification, timing, alternatives)"],"categories":["data-processing-analysis","real-time-streaming"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_1","uri":"capability://data.processing.analysis.batch.audio.transcription.with.speaker.diarization","name":"batch-audio-transcription-with-speaker-diarization","description":"Processes pre-recorded audio files via REST API with automatic speaker identification and segmentation. Nova-3 models analyze complete audio files to detect multiple speakers, assign speaker labels, and return structured transcripts with speaker turns and timing information. Handles background noise, crosstalk, and far-field audio through deep learning-based noise robustness.","intents":["I need to transcribe recorded meetings or interviews and identify who said what","I want to process large audio files without real-time constraints","I need to extract speaker segments for downstream analysis or editing","I want automatic language detection across 45+ languages without pre-specifying the language"],"best_for":["podcast and audio content platforms","legal and compliance teams processing recorded depositions or interviews","research teams analyzing multi-speaker audio datasets"],"limitations":["REST API limited to 50 concurrent requests (free/pay-as-you-go) or 50 (Growth tier) — no increase with tier upgrade for REST","Maximum audio duration not specified — may require chunking for very long files","Speaker diarization accuracy depends on audio quality and speaker count — no published accuracy metrics","Pricing per hour of audio (exact rates not provided in documentation) — costs scale linearly with file duration"],"requires":["API key from Deepgram","Pre-recorded audio file (format and codec support not documented)","HTTP client library (curl, requests, axios, etc.)","File hosting or ability to send audio via multipart/form-data or URL reference"],"input_types":["audio/file (pre-recorded, format UNKNOWN)","audio/url (remote file reference)"],"output_types":["JSON (transcript with speaker labels, timing, confidence)","structured speaker segments (speaker ID, start time, end time, text)"],"categories":["data-processing-analysis","audio-intelligence"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_10","uri":"capability://data.processing.analysis.custom.model.training.for.proprietary.speech.patterns","name":"custom-model-training-for-proprietary-speech-patterns","description":"Deepgram offers custom model training for organizations with proprietary speech patterns, accents, or domain-specific audio characteristics. Custom models are trained on customer-provided datasets and deployed as dedicated endpoints. Enables organizations to achieve higher accuracy on edge-case audio (heavy accents, background noise, specialized vocabulary) that generic models struggle with.","intents":["I have a large dataset of customer audio and want to train a model specific to our user base","I need to handle regional accents or speech patterns that generic models misrecognize","I want to improve accuracy on noisy or far-field audio specific to my environment","I need a proprietary model that competitors cannot access"],"best_for":["enterprise organizations with large proprietary audio datasets","specialized industries (medical, legal, technical) with domain-specific speech","global companies with regional accent variations"],"limitations":["Custom model pricing not provided — requires sales contact, likely expensive","Minimum dataset size not specified — unclear how much training data is required","Training timeline not documented — unclear how long model development takes","No published accuracy improvements from custom training — no benchmarks","Custom models require dedicated endpoints — cannot share infrastructure with public models"],"requires":["API key from Deepgram","Large labeled audio dataset (size UNKNOWN)","Contact with Deepgram sales for custom model engagement","Dedicated API endpoint for custom model (provisioned after training)"],"input_types":["audio/dataset (labeled training audio)","metadata/annotations (transcripts and labels for training data)"],"output_types":["custom-model/endpoint (dedicated API endpoint for inference)"],"categories":["data-processing-analysis","customization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_11","uri":"capability://text.generation.language.smart.formatting.for.readable.transcripts","name":"smart-formatting-for-readable-transcripts","description":"Automatically applies formatting rules to transcripts to improve readability without manual post-processing. Converts numbers to digits, adds punctuation, capitalizes proper nouns, and formats currency/dates according to locale. Smart formatting operates on raw transcription output, transforming 'one thousand two hundred thirty four dollars' to '$1,234' and 'the meeting is on january fifteenth' to 'The meeting is on January 15th'.","intents":["I want transcripts that are immediately readable without manual cleanup","I need formatted numbers, dates, and currency in transcripts for reports","I want proper capitalization and punctuation without post-processing","I need locale-specific formatting (US vs. UK date formats, etc.)"],"best_for":["content platforms publishing transcripts to users","compliance and legal teams requiring clean transcript records","customer-facing applications where transcript quality matters"],"limitations":["Formatting rules and customization options not documented","Locale support not specified — unclear which regions/date formats are supported","Formatting accuracy not published — edge cases with ambiguous numbers unclear","Cannot disable formatting — no option to get raw transcript if needed","Formatting applied uniformly — no per-segment or per-speaker customization"],"requires":["API key from Deepgram","STT request with smart formatting enabled (parameter name UNKNOWN)","Audio input (streaming or batch)"],"input_types":["audio/stream or audio/file (speech to transcribe)"],"output_types":["JSON (formatted transcript with numbers, dates, currency, punctuation)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_12","uri":"capability://data.processing.analysis.multi.language.support.within.single.conversation.stream","name":"multi-language-support-within-single-conversation-stream","description":"Flux Multilingual model supports 10 languages (English, Spanish, German, French, Hindi, Russian, Portuguese, Japanese, Italian, Dutch) within a single WebSocket stream, automatically detecting language switches mid-conversation. Enables applications to handle multilingual users without requiring separate connections or language pre-specification. Language detection happens continuously throughout the stream.","intents":["I want to support users who switch between languages mid-conversation","I need a single voice agent that handles multiple languages without user selection","I want to transcribe international meetings where participants speak different languages","I need to avoid connection overhead from language switching"],"best_for":["international voice applications and platforms","multilingual customer support systems","global meeting transcription services"],"limitations":["Limited to 10 languages (Flux Multilingual) — Nova-3 supports 45+ but only in batch mode","Language switching detection accuracy not published — edge cases with code-switching unclear","Flux Multilingual pricing higher than English-only Flux ($0.0078/min vs. $0.0065/min)","No way to restrict to specific languages — detection is automatic across all 10","Requires WebSocket streaming — not available in REST batch API"],"requires":["API key from Deepgram","Flux Multilingual model specified in request","WebSocket connection (WSS protocol)","Audio input with multiple languages"],"input_types":["audio/stream (real-time audio with language switching)"],"output_types":["JSON (transcript with detected_language field, language per segment)"],"categories":["data-processing-analysis","language-detection"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_13","uri":"capability://automation.workflow.concurrent.connection.management.with.tiered.rate.limits","name":"concurrent-connection-management-with-tiered-rate-limits","description":"Deepgram enforces concurrent connection limits that vary by API type and subscription tier. WebSocket STT supports 150 (free/pay-as-you-go) or 225 (Growth tier) concurrent connections; REST STT/TTS limited to 50 concurrent; Voice Agent API limited to 45 (free) or 60 (Growth) concurrent; Audio Intelligence limited to 10 concurrent regardless of tier. Developers must manage connection pooling and queuing to respect these limits.","intents":["I need to understand how many simultaneous users my application can support","I want to implement connection pooling and queuing for high-traffic applications","I need to plan infrastructure scaling based on concurrency limits","I want to know when to upgrade to Growth tier for higher concurrency"],"best_for":["platform engineers planning capacity and scaling","teams building high-concurrency voice applications","SaaS providers offering voice features to multiple customers"],"limitations":["Audio Intelligence capped at 10 concurrent regardless of tier — severe bottleneck for sentiment/topic/summarization at scale","REST API concurrency does not increase with Growth tier — only WebSocket benefits from tier upgrade","No documented queuing or backpressure mechanism — unclear how requests beyond limit are handled","Concurrency limits are per API key — no way to aggregate limits across multiple keys","No burst capacity or temporary overages — hard limits with no flexibility"],"requires":["API key from Deepgram","Understanding of application's expected concurrent user count","Connection pooling or queuing implementation in client code"],"input_types":["configuration (tier selection, API key management)"],"output_types":["rate-limit-headers (HTTP headers indicating remaining concurrency)"],"categories":["automation-workflow","infrastructure"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_14","uri":"capability://automation.workflow.freemium.tier.with.200.dollar.credit.and.no.expiration","name":"freemium-tier-with-200-dollar-credit-and-no-expiration","description":"Deepgram offers free tier with $200 credit that never expires, no credit card required to sign up. Free tier includes access to all public models (Flux, Nova-3) and all endpoints (STT, TTS, Voice Agent, Audio Intelligence) at full concurrency limits (150 WebSocket STT, 50 REST, etc.). Developers can build and test production applications without payment until credit is exhausted.","intents":["I want to prototype a voice application without upfront cost","I need to evaluate Deepgram's quality and latency before committing to paid tier","I want to build a small-scale application that fits within free tier usage","I need to avoid credit card requirement for initial development"],"best_for":["individual developers and startups","teams evaluating Deepgram before enterprise commitment","hobby projects and proof-of-concepts"],"limitations":["$200 credit is fixed — no monthly refresh or additional free tier after credit exhausted","Credit expiration not specified — documentation says 'no expiration' but unclear if this is permanent","No free tier for custom models — custom training requires paid engagement","Concurrency limits apply to free tier same as paid — no separate free tier caps","No SLA or uptime guarantee specified for free tier"],"requires":["Email address to sign up (no credit card required)","API key provisioned after account creation"],"input_types":["account-creation (email)"],"output_types":["api-key (provisioned for free tier access)"],"categories":["automation-workflow","pricing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_15","uri":"capability://automation.workflow.pay.as.you.go.pricing.with.growth.tier.discounts","name":"pay-as-you-go-pricing-with-growth-tier-discounts","description":"Deepgram offers two pricing models: pay-as-you-go (per-minute consumption) and Growth tier (pre-paid annual credits with 10-20% discount). Pay-as-you-go pricing ranges from $0.0048/min (Nova-3 Monolingual) to $0.0078/min (Flux Multilingual) for STT. Growth tier offers same models at discounted rates ($0.0042-$0.0068/min) with pre-paid annual commitment. Pricing is per-minute of audio processed, not per request.","intents":["I want to understand the cost of my voice application at different scales","I need to calculate ROI for voice features in my product","I want to optimize costs by choosing the right model for my use case","I need to budget for annual voice infrastructure costs"],"best_for":["product managers and finance teams planning voice feature costs","startups evaluating unit economics of voice applications","enterprises negotiating volume discounts"],"limitations":["TTS and Voice Agent pricing not provided in documentation — cost structure unknown","Audio Intelligence pricing not provided — sentiment/topic/summarization costs unclear","Pricing per minute of audio, not per request — long audio files are expensive","Growth tier requires annual pre-payment — no monthly commitment option","No volume discounts beyond Growth tier — enterprise pricing requires sales contact"],"requires":["Estimate of monthly audio volume (in minutes)","Model selection (Flux vs. Nova-3, English vs. Multilingual)","Tier selection (pay-as-you-go vs. Growth)"],"input_types":["configuration (model, tier, estimated volume)"],"output_types":["cost-estimate (monthly or annual cost)"],"categories":["automation-workflow","pricing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_16","uri":"capability://tool.use.integration.deepgram.cli.with.28.api.commands.and.mcp.server","name":"deepgram-cli-with-28-api-commands-and-mcp-server","description":"Deepgram CLI is a command-line tool with 28 built-in commands for transcription, synthesis, and management tasks. Includes integrated MCP (Model Context Protocol) server, enabling AI agents to call Deepgram APIs directly without custom integration code. CLI supports both interactive and scripted usage, with output formatting options (JSON, text, etc.).","intents":["I want to test Deepgram APIs from the command line without writing code","I need to integrate Deepgram into shell scripts or CI/CD pipelines","I want to give AI agents direct access to Deepgram capabilities via MCP","I need to batch process audio files from the command line"],"best_for":["developers testing APIs during development","DevOps engineers integrating voice into CI/CD pipelines","AI agent builders using MCP for tool integration","teams automating batch transcription workflows"],"limitations":["28 commands is modest — unclear which operations are supported vs. full API","MCP server implementation details not documented — unclear which Deepgram features are exposed","CLI output formatting options not specified — unclear what formats are available","No documented CLI authentication beyond API key — no OAuth or other auth methods","CLI version and compatibility not specified — unclear which OS/platforms are supported"],"requires":["Deepgram CLI installed (installation method UNKNOWN)","API key from Deepgram (configured via environment variable or config file)","Shell environment (bash, zsh, PowerShell, etc.)"],"input_types":["command-line-arguments (audio file path, model selection, etc.)","audio-file (for transcription commands)"],"output_types":["text/json (command output, formatted per user selection)","audio-file (for TTS commands)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_17","uri":"capability://tool.use.integration.sdk.support.across.five.languages.with.feature.parity","name":"sdk-support-across-five-languages-with-feature-parity","description":"Deepgram provides official SDKs for Python, JavaScript, Go, .NET, and Java. SDKs abstract HTTP/WebSocket complexity, handle authentication, manage connection pooling, and provide language-idiomatic APIs. Feature parity across SDKs is claimed but not verified — specific version numbers and supported features per SDK not documented.","intents":["I want to integrate Deepgram into my Python/JavaScript/Go/Java application","I need to handle WebSocket connections without managing raw sockets","I want language-idiomatic APIs rather than raw HTTP calls","I need automatic retry logic and error handling"],"best_for":["developers building applications in Python, JavaScript, Go, .NET, or Java","teams wanting to avoid low-level HTTP/WebSocket management","applications requiring robust error handling and retry logic"],"limitations":["SDK version numbers not documented — unclear which versions are current or stable","Feature parity not verified — unclear if all SDKs support all Deepgram features","SDK documentation quality not assessed — may vary by language","No mention of async/await support — unclear if SDKs support async patterns","SDK maintenance status not specified — unclear if all SDKs are actively maintained"],"requires":["SDK for target language (Python, JavaScript, Go, .NET, or Java)","API key from Deepgram","Language runtime (Python 3.x, Node.js, Go 1.x, .NET Core, Java 8+)"],"input_types":["audio/stream or audio/file (passed to SDK methods)"],"output_types":["language-native objects (SDK returns typed objects, not raw JSON)"],"categories":["tool-use-integration","developer-tools"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_2","uri":"capability://data.processing.analysis.automatic.language.detection.and.multilingual.transcription","name":"automatic-language-detection-and-multilingual-transcription","description":"Automatically identifies spoken language from audio without pre-configuration, supporting 45+ languages in Nova-3 Multilingual model or 10 languages in Flux Multilingual for real-time. Detection happens during initial audio processing; language is returned in response metadata and used to optimize transcription accuracy for that language's phonetics and vocabulary.","intents":["I need to transcribe audio without knowing the language in advance","I want to support global users speaking different languages in a single application","I need to handle code-switched or multilingual conversations automatically","I want to avoid manual language selection in my UI"],"best_for":["international platforms serving users across multiple countries","contact centers with multilingual customer bases","global media and broadcasting platforms"],"limitations":["Flux Multilingual limited to 10 languages (English, Spanish, German, French, Hindi, Russian, Portuguese, Japanese, Italian, Dutch) — Nova-3 supports 45+ but only in batch mode","Language detection confidence not returned in API response — no way to assess detection reliability","Code-switching (mixing languages mid-sentence) support not documented","Detection accuracy depends on audio duration — very short clips may misidentify language"],"requires":["API key from Deepgram","Audio input (streaming or batch)","No language parameter required (detection is automatic)"],"input_types":["audio/stream or audio/file (any supported language)"],"output_types":["JSON (detected_language field in response metadata)","transcript (optimized for detected language)"],"categories":["data-processing-analysis","language-detection"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_3","uri":"capability://planning.reasoning.conversational.turn.detection.and.interruption.handling","name":"conversational-turn-detection-and-interruption-handling","description":"Flux models detect natural speech boundaries and turn-taking in conversations, automatically identifying when a speaker has finished talking and when another speaker begins. Built-in interruption handling allows overlapping speech to be processed without requiring explicit silence detection thresholds. Enables voice agents to know when to stop listening and trigger response generation without timeout-based heuristics.","intents":["I want my voice agent to respond naturally without waiting for silence timeouts","I need to detect speaker turns in multi-party conversations automatically","I want to handle interruptions gracefully in voice interactions","I need to trigger downstream LLM processing at natural conversation boundaries"],"best_for":["voice agent and conversational AI developers","real-time meeting transcription platforms","customer service voice bots"],"limitations":["Turn detection accuracy not published — no metrics on false positives/negatives","Interruption handling behavior not formally specified — edge cases with rapid back-and-forth unclear","Only available in Flux models (real-time streaming) — not available in Nova-3 batch models","Requires WebSocket streaming — cannot be used with REST batch API"],"requires":["API key from Deepgram","Flux English or Flux Multilingual model (specified in request)","WebSocket connection (WSS protocol)","Client-side logic to listen for turn-detection signals in response"],"input_types":["audio/stream (real-time audio with natural speech patterns)"],"output_types":["JSON (transcript with turn-detection metadata)","signal (implicit — final transcript indicates turn completion)"],"categories":["planning-reasoning","real-time-streaming"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_4","uri":"capability://tool.use.integration.unified.voice.agent.orchestration.with.st.llm.tts.integration","name":"unified-voice-agent-orchestration-with-stт-llm-tts-integration","description":"Voice Agent API combines speech-to-text, LLM integration, and text-to-speech in a single WebSocket connection, orchestrating the full conversational loop. Audio input flows to Flux STT model, transcript is sent to configured LLM (provider UNKNOWN), LLM response is streamed to TTS model, and synthesized audio is returned to client — all within one persistent connection without intermediate API calls.","intents":["I want to build a voice agent without managing multiple API connections","I need end-to-end voice conversation with minimal latency between STT and LLM and TTS","I want to handle language detection and turn-taking across the entire conversation pipeline","I need a single authentication point for voice agent infrastructure"],"best_for":["startups building voice assistant MVPs","teams wanting unified voice agent infrastructure without orchestration complexity","applications requiring sub-second latency across STT→LLM→TTS pipeline"],"limitations":["LLM provider options not documented — unclear which models are supported (OpenAI, Anthropic, etc.)","Pricing for Voice Agent API not provided in documentation — cost structure unknown","Concurrency limited to 45 (free/pay-as-you-go) or 60 (Growth tier) WebSocket connections","No documented way to customize LLM behavior (temperature, system prompts, etc.) — integration details unknown","Requires WebSocket — no REST API alternative for simpler use cases"],"requires":["API key from Deepgram","LLM API key (provider and format UNKNOWN)","WebSocket client library","Audio input and output capability (microphone/speaker or audio stream)"],"input_types":["audio/stream (real-time user speech)"],"output_types":["audio/stream (synthesized agent response)","JSON metadata (transcript, language, turn detection)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_5","uri":"capability://text.generation.language.text.to.speech.synthesis.with.streaming.input","name":"text-to-speech-synthesis-with-streaming-input","description":"Converts text to natural-sounding audio via REST or WebSocket API. Supports streaming text input (partial text can be sent before full response is available), enabling real-time audio generation as LLM generates response tokens. Multiple voices and languages available (specific count and list not documented). Synthesized audio is returned as audio stream (format UNKNOWN).","intents":["I want to convert LLM responses to speech in real-time as tokens arrive","I need multiple voice options for different user personas or languages","I want to stream audio output to users without waiting for full text generation","I need TTS integrated with my voice agent pipeline"],"best_for":["voice agent developers","accessibility platforms converting text content to audio","interactive voice response (IVR) systems"],"limitations":["Voice options and language support not documented — unclear which voices/languages available","Maximum text length not specified — no guidance on chunking long responses","TTS pricing not provided in documentation","Audio format and quality options not documented","Concurrency limited to 45 (free/pay-as-you-go) or 60 (Growth tier) combined REST+WSS connections"],"requires":["API key from Deepgram","Text input (format and encoding UNKNOWN)","HTTP client (REST) or WebSocket client (streaming)"],"input_types":["text/plain (text to synthesize)","text/stream (partial text arriving incrementally)"],"output_types":["audio/stream (synthesized audio, format UNKNOWN)"],"categories":["text-generation-language","audio-synthesis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_6","uri":"capability://data.processing.analysis.sentiment.analysis.on.transcribed.speech","name":"sentiment-analysis-on-transcribed-speech","description":"Audio Intelligence endpoint analyzes transcribed speech to detect emotional tone and sentiment (positive, negative, neutral). Processes audio or transcript to extract sentiment signals, returning sentiment labels and confidence scores. Operates as post-processing on transcription output or as standalone analysis on pre-transcribed text.","intents":["I want to detect customer satisfaction or frustration in support calls","I need to monitor agent performance based on conversation tone","I want to identify high-priority or escalation-worthy interactions automatically","I need sentiment trends across multiple conversations for analytics"],"best_for":["contact center analytics platforms","customer experience monitoring tools","voice of customer (VoC) programs"],"limitations":["Sentiment model accuracy not published — no benchmarks or confidence thresholds documented","Sentiment granularity unclear — only positive/negative/neutral or more nuanced emotions?","REST API limited to 10 concurrent requests (no tier upgrade) — severe bottleneck for high-volume analysis","Pricing for Audio Intelligence not documented","No real-time sentiment streaming — only batch analysis after transcription complete"],"requires":["API key from Deepgram","Transcribed text or audio input","HTTP client for REST API"],"input_types":["text/transcript (transcribed speech)","audio/file (pre-recorded audio)"],"output_types":["JSON (sentiment label, confidence score)","structured metadata (sentiment per speaker, sentiment over time)"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_7","uri":"capability://data.processing.analysis.topic.detection.and.content.categorization","name":"topic-detection-and-content-categorization","description":"Audio Intelligence endpoint automatically identifies topics and themes discussed in audio conversations. Analyzes transcribed speech to extract key topics, categorize conversation content, and return topic labels with relevance scores. Enables automatic routing, content classification, and conversation summarization without manual tagging.","intents":["I want to automatically categorize support tickets by topic (billing, technical, account, etc.)","I need to route conversations to appropriate teams based on detected topics","I want to extract key discussion themes from meeting recordings","I need to build topic-based analytics dashboards from conversation data"],"best_for":["contact center routing and IVR systems","meeting intelligence and analytics platforms","content management and archival systems"],"limitations":["Topic taxonomy not documented — unclear which topics are recognized or how custom topics are defined","Topic detection accuracy not published — no benchmarks or confidence thresholds","REST API limited to 10 concurrent requests — severe bottleneck for real-time routing","Pricing for Audio Intelligence not documented","No streaming topic detection — only batch analysis after transcription"],"requires":["API key from Deepgram","Transcribed text or audio input","HTTP client for REST API"],"input_types":["text/transcript (transcribed speech)","audio/file (pre-recorded audio)"],"output_types":["JSON (topic labels, relevance scores)","structured metadata (topics per segment, topic timeline)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_8","uri":"capability://text.generation.language.automatic.summarization.of.audio.conversations","name":"automatic-summarization-of-audio-conversations","description":"Audio Intelligence endpoint generates abstractive summaries of audio conversations, condensing key points and action items from transcribed speech. Summarization operates on full transcript or speaker segments, extracting essential information and generating concise natural language summaries without manual review.","intents":["I want to generate meeting notes automatically from recorded calls","I need to extract action items and decisions from conversations","I want to create executive summaries of long customer interactions","I need to archive conversation summaries for compliance and knowledge management"],"best_for":["meeting transcription and note-taking platforms","contact center quality assurance and training","legal and compliance document management"],"limitations":["Summarization model and approach not documented — unclear if extractive or abstractive, or how length is controlled","Summary quality and accuracy not published — no benchmarks or user satisfaction metrics","REST API limited to 10 concurrent requests — bottleneck for batch summarization","Pricing for Audio Intelligence not documented","No streaming summarization — only batch analysis after full transcription"],"requires":["API key from Deepgram","Complete transcribed text or audio input","HTTP client for REST API"],"input_types":["text/transcript (full transcribed conversation)","audio/file (pre-recorded audio)"],"output_types":["text/summary (natural language summary)","structured metadata (key points, action items, participants)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__cap_9","uri":"capability://data.processing.analysis.keyterm.prompting.for.domain.specific.accuracy","name":"keyterm-prompting-for-domain-specific-accuracy","description":"Allows developers to provide domain-specific keywords or phrases that the STT model should prioritize during transcription. Keyterm prompting biases the model's decoding toward specified terms, improving accuracy for technical jargon, product names, or domain-specific vocabulary that might otherwise be misrecognized. Implemented as optional parameter in transcription requests.","intents":["I want to improve transcription accuracy for technical terms or product names in my domain","I need to ensure specific keywords are recognized correctly in medical or legal contexts","I want to reduce hallucinations of similar-sounding words in specialized vocabularies","I need to customize recognition for company-specific terminology or acronyms"],"best_for":["medical and legal transcription services","technical support and engineering teams","industry-specific voice applications (finance, pharma, etc.)"],"limitations":["Keyterm impact on accuracy not quantified — no metrics on improvement per term","Maximum number of keyterms not specified — unclear if there's a limit or performance degradation","Keyterm weighting mechanism not documented — unclear how strongly terms are prioritized","Works with all STT models but effectiveness may vary by model","Requires manual maintenance of keyterm lists — no automatic extraction or learning"],"requires":["API key from Deepgram","List of domain-specific keywords or phrases","STT request with keyterms parameter (format UNKNOWN)"],"input_types":["audio/stream or audio/file (speech to transcribe)","text/list (keyterms to prioritize)"],"output_types":["JSON (transcript with improved accuracy for keyterms)"],"categories":["data-processing-analysis","customization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"deepgram-api__headline","uri":"capability://voice.audio.ai.speech.to.text.and.text.to.speech.api","name":"ai speech-to-text and text-to-speech api","description":"Deepgram API is an advanced AI speech-to-text and text-to-speech service that offers real-time streaming, speaker diarization, and supports over 36 languages, making it ideal for developers seeking high accuracy in audio processing.","intents":["best AI speech-to-text API","text-to-speech API for real-time applications","AI audio processing solutions","top speech recognition APIs","best API for speaker diarization"],"best_for":["real-time audio applications","multilingual transcription","audio intelligence tasks"],"limitations":[],"requires":[],"input_types":["audio files","text"],"output_types":["transcriptions","audio output"],"categories":["voice-audio"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":58,"verified":false,"data_access_risk":"high","permissions":["API key from Deepgram (free tier includes $200 credit with no expiration)","WebSocket client library (native browser WebSocket or Node.js ws module)","Audio input source (microphone, audio stream, or hardware device)","Network connectivity with WSS (secure WebSocket) support","API key from Deepgram","Pre-recorded audio file (format and codec support not documented)","HTTP client library (curl, requests, axios, etc.)","File hosting or ability to send audio via multipart/form-data or URL reference","Large labeled audio dataset (size UNKNOWN)","Contact with Deepgram sales for 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