
Deep Research integrates as a native skill inside Computer: search as code generation, long-running sandboxes, connectors, and tools.
The Hook
“(No spoken dialogue — subtle riser builds anticipation with arpeggiated synth and sub-bass.)”
Product Reveal
“(No spoken dialogue — pronounced sweep and sub-bass drop, driving synth melody continues.)”
Feature Teaser
“(No spoken dialogue — another sweep and drop, maintaining energetic synth melody.)”
Call to Action
“(No spoken dialogue — impactful sub-bass drop with a sustained synth pad, fading out.)”
Synthesizable in Remotion · key components of the ai-agent-data-insights template.
Text appears character by character within a search bar, simulating real-time user input, often followed by a full query reveal.
Use `Sequence` and `spring` for character-by-character opacity and scale, or `interpolate` for a linear typing effect. Implement a `delay` for the full query reveal.
Multiple UI cards or data panels animate into view sequentially, often with a slight delay and a subtle bounce or slide effect.
Utilize `spring` for position and opacity, with `delay` props on individual components within a `Sequence` or `Series` to create the staggered effect. Apply `z-index` for layering.
Bar charts and line graphs animate their values, with bars growing from the base and lines drawing themselves across the screen.
Animate SVG `rect` heights or `path` `stroke-dasharray` and `stroke-dashoffset` properties using `interpolate` or `spring` for smooth transitions. Coordinate with `delay` for sequential data points.
Purpose. Introduce the core capability of the AI agent through a realistic user interaction.
Execution. Typing animation in a search bar, revealing a complex research query against an abstract, evolving background.
Purpose. Demonstrate the AI's internal workflow and its ability to delegate and execute tasks.
Execution. On-screen text indicating parallel task execution and skill loading, followed by a detailed, scrolling view of the AI's generated research plan.
Purpose. Showcase the quality and depth of the AI's research output, including data visualizations and verified sources.
Execution. Presentation of a well-formatted research report with charts, tables, and explicit source citations, emphasizing thoroughness.
Purpose. Broaden the scope of the product's capabilities beyond research to include coding and building, culminating in brand reinforcement.
Execution. Rapid succession of various UI dashboards and applications, highlighting 'Computer codes' and 'Computer builds', ending with a dynamic logo reveal.
Objective
Demonstrate QuantumFlow's ability to analyze real-time financial market data and predict trends.How the recipe adapts
The TypingSearchInput primitive would show a user typing a query like 'Analyze real-time stock market volatility for tech sector'. StaggeredCardReveal would then display various data modules, such as 'Sentiment Analysis', 'Volume Trends', and 'Predictive Indicators'. The DataChartBuild primitive would animate a line graph showing predicted stock movements and a bar chart comparing sector performance, all against a subtly animated background of flowing data streams. The overall pacing would remain precise, with impactful sound design cues for each data insight reveal.Scene durations (4 scenes, 63s)
Key Remotion components
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