Synthesia

Converts plain text input into video content by synthesizing photorealistic or stylized AI avatars that deliver the text as spoken dialogue. The system uses deep learning models to generate natural lip-sync, facial expressions, and head movements synchronized to text-to-speech audio, rendering the final video at specified resolutions and frame rates without requiring human actors or filming.

Generates natural-sounding speech audio in 140+ languages and regional dialects by routing text through language-specific neural vocoder models that preserve prosody, intonation, and cultural speech patterns. The system selects appropriate phoneme inventories and prosodic rules per language, then synthesizes audio that matches the avatar's lip movements through a synchronized rendering pipeline.

Provides pre-built video templates (intro sequences, transitions, lower-thirds, background layouts) that automatically adapt to generated avatar video and text content. The system uses constraint-based layout engines to position avatars, text overlays, and background elements while maintaining visual hierarchy and brand consistency, with real-time preview rendering to show composition changes before final export.

Enables programmatic submission of multiple video generation jobs through REST API or CSV upload, with asynchronous processing, job status tracking, and webhook callbacks when videos complete. The system queues jobs across distributed rendering infrastructure, applies rate limiting per subscription tier, and stores generated videos in cloud storage with configurable retention policies and CDN delivery.

Allows users to customize avatar appearance (skin tone, hair, clothing, accessories) from a library of pre-built components, or upload custom avatar models trained on branded character designs or real people. The system uses modular avatar architecture where each component (head, torso, clothing) is independently renderable, enabling rapid iteration and A/B testing of avatar variations without retraining models.

Provides in-browser video editor for trimming, cutting, adding transitions, adjusting playback speed, and inserting additional media (images, video clips, music) into generated videos. The system uses WebGL-based rendering for real-time preview and exports edited videos through the same rendering pipeline as original generation, maintaining quality consistency and enabling iterative refinement without regenerating avatar content.

Generates synchronized captions and subtitles from video audio using speech-to-text models, with automatic language detection and optional translation to additional languages. The system timestamps each caption to audio segments, applies speaker identification if multiple voices present, and exports captions in standard formats (SRT, VTT, WebVTT) with customizable styling for font, color, and positioning.

Tracks video playback metrics (views, watch time, completion rate, drop-off points) when videos are embedded or shared through Synthesia's player or integrated into external platforms via tracking pixels. The system aggregates metrics by video, campaign, or avatar variant and provides dashboards showing viewer engagement patterns, enabling data-driven optimization of video content and messaging.

Provides native integrations or API connectors to marketing automation platforms (HubSpot, Marketo, Salesforce) and CRM systems, enabling video generation to be triggered by workflow events (new lead, customer milestone) and personalized with CRM data (name, company, purchase history). The system maps CRM fields to video template variables and handles authentication/data synchronization automatically.

Provides cloud hosting for generated videos with automatic CDN distribution, adaptive bitrate streaming (HLS, DASH), and configurable access controls (public, private, password-protected, expiring links). The system automatically transcodes videos to multiple resolutions and bitrates, caches content at edge locations, and tracks bandwidth usage against plan limits.