Kinnovation Index
06 · Creator tools · AI

Trendify

You already shot it. You just cannot find it.

Nobody actually has nothing to post. They have eleven thousand photos and no idea which one fits the format that is working this week. Trendify watches the trends, indexes what you already own, and puts the two together.

Talk about it All ventures
The problem

You are not short of footage

People sitting on thousands of photos and videos still open the app and decide they have nothing worth posting. The footage is fine. What is missing is knowing which clip fits the structure that is currently going viral.

  • 01Trends move fast, and using the audio early is most of the advantage. By the time something is obviously a trend, it is finished.
  • 02The real bottleneck is finding the right eight seconds inside a library of forty thousand files.
  • 03Trend research is unpaid analytics work done by scrolling. Which audio is climbing, what the view to like ratio looks like, which themes cluster, where the cuts land.
  • 04So people film something new instead. The library keeps growing and the account stays quiet.
The match

What you have becomes what is working

  1. Travel clipsRising nostalgic montageAudio velocity ↑
  2. Gym footageHigh-retention transformationRetention 92%
  3. Clips with friendsComedic POV formatPeaking this week
  4. Food and cafésAesthetic slow-cutEarly, low saturation

Going viral is far more structural than it is aesthetic. Structure is a pattern, patterns can be detected, and most people are already sitting on the raw material.

What the engine watches
  • Audio adoption velocity
  • View-to-like ratio
  • Structural format
  • Theme clusters
  • Cut timing
  • Trend decay
Inside

Five moving parts

01

Live trend tracking

Watches audio across TikTok and Reels, measures how fast adoption is climbing, tracks engagement ratios, and identifies the structures underneath. Transformation, POV, montage, storytelling, where the cut lands on the beat.

02

Indexing what you own

Tags your media by subject, motion, pacing, lighting and scene changes, then cuts it into reusable segments. The gallery becomes searchable by what is in it rather than the date it was taken.

03

Matching trend to footage

This is the part that matters. Audio structure, pacing requirements and the clip types that keep working, scored against what you actually have. Those gym clips from March fit the transformation audio climbing this week.

04

One shoot, several posts

The same footage across different trends by changing the audio, the pacing, the structure or how the caption frames it, so a good afternoon of filming keeps paying out.

05

It suggests, you decide

Nothing posts by itself. Reorder the clips, trim them, swap the audio, filter language, set the tone anywhere from funny to stripped back. Every suggestion is a starting point.

The loop

Index, match, assemble, learn

  1. 01

    Index

    Your gallery gets tagged and cut into reusable segments.

  2. 02

    Monitor

    Trend velocity tracked continuously, so dying formats drop out.

  3. 03

    Match

    Formats scored against clips you already own.

  4. 04

    Assemble

    A bundle arrives. Clip order, audio, caption idea, hashtag cluster.

  5. 05

    Learn

    Linked post analytics sharpen what gets suggested next time.

Keeping up with formats without living inside the app, and without shooting a single new frame.

On device
Where the processing happens
No auto post
You review everything
No pressure
Zero viral shame metrics