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Wideframe

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Wideframe serves as an AI-driven assistant for video production teams, automating the tedious prep work that occurs before the final edit begins. Instead of functioning as a standalone creative suite, …

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May 19, 2026
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About Wideframe

TL;DR

Wideframe serves as an AI-driven assistant for video production teams, automating the tedious prep work that occurs before the final edit begins. Instead of functioning as a standalone creative suite, …

Wideframe serves as an AI-driven assistant for video production teams, automating the tedious prep work that occurs before the final edit begins. Instead of functioning as a standalone creative suite, this tool acts as a layer of intelligence that sits over raw footage and integrates directly with professional software like Premiere Pro and DaVinci Resolve. By indexing every frame of a library, it enables editors to locate specific moments using natural language queries—such as searching for specific emotions or shot types—eliminating the need for manual tagging or scrubbing through hours of tape. The platform's core strength is its ability to handle the logistical "grunt work" of post-production, including organizing bins, building rough cuts, and drafting project briefs based on existing assets. It can read and write native project files, allowing for a smooth transition into a traditional timeline for final polishing. Unlike many generative tools that produce disconnected assets, this software’s generated content is informed by the specific context of the user's local media library. For agencies handling large volumes of footage, it effectively serves as a digital assistant editor that handles the data-heavy organization so humans can focus on narrative and style.

Use Cases

Real-world scenarios where Wideframe saves time.

Use Case 1: Semantic Footage Search Problem: Editors spend hours scrubbing through terabytes of raw files to find specific moments or visual 'vibes.' Solution: Wideframe indexes footage so editors can search for content using natural language descriptions. Example: A documentary editor searches for "wide shots of a sunset with a lone bird" and gets instant results from 40 hours of footage.

Use Case 2: Automated Rough Cut Assembly Problem: The initial stage of building a rough cut is repetitive and time-consuming for creative leads. Solution: The AI agent can pull selects and assemble basic sequences based on a written brief or script. Example: A social media manager describes a 30-second highlight reel, and the tool builds the initial timeline in Premiere Pro.

Use Case 3: Context-Aware B-Roll Generation Problem: Traditional AI generation tools often create assets that don't match the lighting or style of the original project. Solution: Wideframe generates complementary assets (briefs, copy, or images) that are grounded in the specific context of the indexed library. Example: A producer generates a shot list for a pick-up shoot that perfectly matches the existing scene detection data.

Key Features

What you get out of the box.

  • Natural language semantic video search. * Native integration with Premiere Pro and Resolve. * Non-destructive media indexing. * Automated sequence assembly and rough cuts. * Contextual generation of briefs and b-roll. * Support for M1 Mac and Apple Silicon.

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