Veritone

Converts audio and video content into accurate text transcripts across multiple languages and audio conditions. Handles various audio quality levels, accents, and background noise with industry-leading accuracy.

Analyzes media files to automatically extract and generate metadata including topics, entities, sentiment, and content classification. Enables rich indexing and organization of unstructured media data.

Identifies and catalogs objects, scenes, and visual elements in video content. Provides frame-level understanding of visual content for indexing and analysis.

Extracts text from video frames and images, including captions, graphics, and on-screen text. Enables searchability of text-based content within visual media.

Automates complex multi-step workflows combining media processing, analysis, and data extraction. Enables conditional logic, error handling, and integration with external systems.

Monitors incoming media streams and content for specific conditions, triggering alerts and actions when criteria are met. Enables proactive content management and compliance monitoring.

Allows users to combine and chain multiple AI engines from the aiWARE marketplace to create custom processing pipelines. Enables flexible workflow design without vendor lock-in by mixing best-of-breed engines.

Provides robust REST and webhook APIs that enable deep integration of Veritone's AI capabilities into existing enterprise systems and applications. Supports batch processing, real-time requests, and custom application development.

Processes large volumes of media files in batch mode, optimizing for throughput and cost efficiency. Handles queuing, scheduling, and parallel processing of thousands of files without manual intervention.

Automatically converts and normalizes diverse audio and video formats into standardized formats suitable for processing. Handles codec conversion, resolution scaling, and audio normalization.

Identifies and separates different speakers in audio and video content, labeling segments by speaker. Useful for understanding who said what in multi-speaker recordings.

Creates searchable indexes of media content based on extracted metadata, transcripts, and semantic understanding. Enables full-text search across audio and video archives.

Translates transcribed or text content across multiple languages, enabling global content distribution. Works with transcripts and extracted text to provide translated versions.

Analyzes audio and text content to detect sentiment, emotion, and tone. Provides insights into emotional context and audience response patterns in media.