AWS APIs
148 APIs6,711 Endpoints16 Categories
Categories
API Catalog(17 of 148)
Amazon Augmented AI Runtime
Jentic publishes the only available OpenAPI specification for Amazon Augmented AI Runtime, keeping it validated and agent-ready. Amazon Augmented AI (A2I) is the human-in-the-loop layer for ML predictions — when a model's confidence falls below threshold, A2I routes the prediction to a configured workforce (private, vendor, or Amazon Mechanical Turk) for human review. The runtime API starts, monitors, stops, and deletes individual human review tasks (called HumanLoops) tied to a flow definition you create in the SageMaker console.
5 endpointsAmazon Bedrock Runtime API
Jentic publishes the only available OpenAPI specification for Amazon Bedrock Runtime API, keeping it validated and agent-ready. Amazon Bedrock Runtime is the inference plane of Amazon Bedrock, AWS's managed service for foundation models from Anthropic, AI21, Cohere, Meta, Mistral, Stability, and Amazon's own Titan and Nova families. The runtime API lets you invoke a model with a request body in the model's native format, stream tokens as they are generated, run a unified Converse loop across providers, and apply Bedrock Guardrails to inputs and outputs for safety filtering.
5 endpointsAmazon Comprehend
Jentic publishes the only available OpenAPI specification for Amazon Comprehend, keeping it validated and agent-ready. Amazon Comprehend is a managed natural language processing service that extracts insights from unstructured text. It detects entities, key phrases, sentiment, targeted sentiment, dominant language, syntax, and personally identifiable information, and supports custom classification and entity recognition models trained on your data. Both real-time analysis and large-scale asynchronous batch jobs are supported, along with topic modeling, document classification, and PII redaction.
84 endpointsAmazon Forecast Query Service
Jentic publishes the only available OpenAPI specification for Amazon Forecast Query Service, keeping it validated and agent-ready. The Forecast Query Service is the runtime side of Amazon Forecast and exposes only the operations needed to query trained predictors. The API returns point and quantile forecasts for a specific item, and serves what-if forecasts that compare baseline predictions against scenario adjustments. It is built for application teams that want to embed pre-computed Forecast predictions into customer-facing demand, capacity, or pricing flows.
2 endpointsAmazon Kendra
Jentic publishes the only available OpenAPI specification for Amazon Kendra, keeping it validated and agent-ready. Amazon Kendra is a managed enterprise search service that ingests documents from S3, SharePoint, Confluence, Salesforce, ServiceNow, and many other sources, then answers natural-language queries with passage-level results. Its 65 endpoints cover index lifecycle, data source connectors, query and suggestion APIs, FAQ ingestion, access control mappings for tenant-aware results, query suggestions, and featured-results experiences. Kendra is a frequent retrieval layer for enterprise RAG pipelines that need permission-aware document search.
65 endpointsAmazon Lex Model Building Service
Jentic publishes the only available OpenAPI specification for Amazon Lex Model Building Service, keeping it validated and agent-ready. The Lex Model Building Service is the v1 control plane for designing conversational bots: defining intents, slot types, slots, and bot aliases that route conversation traffic to specific bot versions. Its 42 endpoints cover intent and slot type lifecycle, bot version management, channel associations for Facebook and Slack, import and export jobs, migration to Lex v2, and tagging. The runtime API for end-user conversations is separate.
42 endpointsAmazon Lex Model Building V2
Jentic publishes the only available OpenAPI specification for Amazon Lex Model Building V2, keeping it validated and agent-ready. Lex Model Building V2 is the authoring control plane for Amazon Lex conversational bots — it manages bots, bot versions, locales, intents, slot types, slots, custom vocabulary and aliases, and orchestrates the build, import, export and tagging of those resources. The 71 endpoints cover the full bot lifecycle from CreateBot through BuildBotLocale, intent and slot configuration, custom vocabulary upload, version pinning and alias-based deployment.
71 endpointsAmazon Lex Runtime V2
Jentic publishes the only available OpenAPI specification for Amazon Lex Runtime V2, keeping it validated and agent-ready. Lex Runtime V2 is the conversational dataplane for Amazon Lex V2 bots — it exchanges user text or audio with a deployed bot alias and returns recognised intents, slot values, and the bot's next response. The runtime carries session state across turns, supports both text and streaming utterance recognition, and is the integration point for chat widgets, IVR systems, and voice assistants built on Lex V2.
5 endpointsAmazon Lookout for Metrics
Jentic publishes the only available OpenAPI specification for Amazon Lookout for Metrics, keeping it validated and agent-ready. Amazon Lookout for Metrics uses machine learning to detect anomalies in business and operational metrics — sales drops, conversion changes, traffic spikes — without requiring data science expertise. Anomaly detectors ingest data from sources such as Amazon S3, Amazon Redshift, Amazon CloudWatch, and Amazon RDS, then surface deviations along with severity scores and grouped contributing dimensions. Alerts route findings to channels like Amazon SNS or AWS Lambda so downstream systems can respond automatically.
30 endpointsAmazon Mechanical Turk
Jentic publishes the only available OpenAPI specification for Amazon Mechanical Turk, keeping it validated and agent-ready. Mechanical Turk (MTurk) is AWS's human-in-the-loop crowdsourcing platform — Requesters publish Human Intelligence Tasks (HITs), Workers complete them, and Requesters review the resulting Assignments. The 39 endpoints cover the full Requester lifecycle: CreateHIT and CreateHITWithHITType, ListHITs, accept/reject Assignments, send bonuses, manage Qualifications and QualificationRequests, and notify or block Workers.
39 endpointsAmazon Personalize Runtime
Jentic publishes the only available OpenAPI specification for Amazon Personalize Runtime, keeping it validated and agent-ready. Amazon Personalize Runtime serves real-time personalized recommendations and re-ranked item lists from machine learning models trained in Amazon Personalize. The service exposes two inference endpoints that consume a deployed campaign or recommender ARN and return ranked itemIds tailored to a specific user, context, or input list. It is designed for live serving paths inside e-commerce, media, and content discovery applications where models built in Personalize need to be queried at request time.
2 endpointsAmazon Polly
Jentic publishes the only available OpenAPI specification for Amazon Polly, keeping it validated and agent-ready. Amazon Polly is a managed text-to-speech service that turns text into lifelike audio across dozens of voices, languages, and speech engines (standard, neural, long-form, and generative). The API exposes synchronous synthesis via SynthesizeSpeech for short clips, asynchronous synthesis tasks for long-form audio written to S3, and pronunciation lexicon management for fine-grained word-level control. It supports plain text and SSML input and returns MP3, OGG Vorbis, PCM, or JSON speech-mark output.
9 endpointsAmazon Rekognition
Jentic publishes the only available OpenAPI specification for Amazon Rekognition, keeping it validated and agent-ready. Rekognition is a managed computer-vision service for image and video understanding: face detection, comparison, and search; object, scene, and label detection; text-in-image (OCR); content moderation; celebrity recognition; PPE detection; and stream-based video analysis. The API surfaces 65 operations across synchronous image analysis, asynchronous video jobs, face-collection management, custom Rekognition Custom Labels project lifecycle, and live-stream processors. It is the canonical AWS API for adding vision intelligence to applications.
65 endpointsAmazon SageMaker
Jentic publishes the only available OpenAPI specification for Amazon SageMaker, keeping it validated and agent-ready. Amazon SageMaker is AWS's end-to-end machine-learning platform — it provides training jobs, hyperparameter tuning, model packaging, real-time and batch inference endpoints, feature stores, data labelling, AutoML, MLflow-style experiment tracking, model monitoring, and pipeline orchestration. The control-plane API exposed here covers all 300+ operations across the ML lifecycle, from launching a training job to deploying a multi-model endpoint behind production traffic.
302 endpointsAmazon Textract
Jentic publishes the only available OpenAPI specification for Amazon Textract, keeping it validated and agent-ready. Amazon Textract extracts printed text, handwriting, forms, tables, signatures, and ID and expense fields from scanned documents and PDFs. It returns structured JSON with bounding boxes and confidence scores for each detected element, supporting both synchronous calls for single-page documents and asynchronous jobs for multi-page PDFs stored in Amazon S3. Specialized analyzers cover invoices, receipts, identity documents, and lending packages.
25 endpointsAmazon Textract
Jentic publishes the only available OpenAPI specification for Amazon Textract, keeping it validated and agent-ready. Amazon Textract uses machine learning to extract printed text, handwriting, form key-value pairs, table cells, identity-document fields, and expense receipt data from scanned documents and images. It supports both synchronous calls for single-page JPEG/PNG inputs and asynchronous jobs for multi-page PDFs and TIFFs stored in S3. The 13 operations span document analysis, expense analysis, ID analysis, lending document analysis, and the start/get pairs that drive its async job pattern.
13 endpointsAmazon Transcribe
Jentic publishes the only available OpenAPI specification for Amazon Transcribe, keeping it validated and agent-ready. Amazon Transcribe converts audio into text using automatic speech recognition. It supports three batch transcription modes (Standard, Medical, Call Analytics), custom language models trained on domain-specific text, custom vocabularies for proper nouns, and vocabulary filters for redaction. The 39 operations cover the full lifecycle of transcription jobs, custom vocabularies, language models, and call-analytics categories, plus tagging for cost allocation.
39 endpointsConnect Your Agent
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Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.