InsightClip AI
Turn long-form video content into viral short-form clips with AI-driven speaker tracking and engagement scoring.
Transform raw footage into viral short-form content with AI-driven kinetic typography and retention-optimized editing.
Caption Knight is a high-performance AI video post-production platform designed to bridge the gap between raw video capture and high-retention social media distribution. Utilizing advanced Large Speech Models (LSM) like Whisper v3 for near-perfect transcription, the platform specializes in 'retention editing'—a technique that uses dynamic text, automatic emoji placement, and strategic B-roll insertion to maximize viewer engagement on platforms like TikTok, Instagram Reels, and YouTube Shorts. By 2026, Caption Knight has evolved from a simple subtitle generator into a comprehensive AI visual architect, capable of multi-track audio isolation to ensure caption accuracy even in noisy environments. The technical architecture leverages GPU-accelerated rendering in the cloud, allowing users to generate complex 4K kinetic typography without local hardware constraints. Positioned as a direct competitor to boutique editing agencies, it offers an automated pipeline for brand-consistent styling, automated re-framing for 9:16 aspect ratios, and semantic keyword highlighting. This enables creators and marketing teams to scale their content output by 10x while maintaining the creative quality typically associated with professional human editors.
Uses Natural Language Processing (NLP) to identify high-impact words and applies distinct CSS-like styles automatically.
Turn long-form video content into viral short-form clips with AI-driven speaker tracking and engagement scoring.
Automate viral short-form content generation and distribution from long-form video assets.
Transform long-form video into viral short-form assets with LLM-driven scene intelligence.
The #1 AI platform to extract the most impactful, viral-ready clips from your long-form videos.
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Distinguishes between different voices in a podcast format and assigns unique caption colors or positions per speaker.
Subtitles follow the movement of subjects within the frame using computer vision tracking.
Connects to Pexels and Storyblocks APIs to insert footage based on the context of the transcript.
Applies a pre-processing spectral subtraction filter to isolate vocals before the STT engine runs.
Uses face-tracking to ensure the speaker stays centered in 9:16 vertical exports even if the original was 16:9.
Translates both audio and visual text overlays while maintaining the same font styling and timing.
Podcasters spend hours finding 'clips' and subtitling them for social promotion.
Registry Updated:2/7/2026
User-Generated Content looks unprofessional without high-quality overlays.
Voiceovers are often unheard on social media (muted by default).