How to design a Content Moderation Service using AWS Rekognition, AWS Lambda and Python 3.8

This is a design question. I am trying to implement a Content Moderation Service in python 3.8 which uses AWS Rekognition to detect moderation labels. This service will be implemented using Serverless framework and will execute as AWS Lambda Function. The trigger to this lambda function would be an s3 bucket.

So I have already created a lambda function which gets triggered at every image upload on s3 bucket. And I am able to trigger the AWS Rekognition service with that image as input and fetch the output.

My question is regarding the design of this service. Imagine a web app like LinkedIn, where there are users and organisations who upload images as posts, profile pictures, business pictures, etc. All of these components already have the APIs which upload these images and store the reference in the DB.

This service that I am implementing should receive any kind of image first and should detect moderation labels on it, if everything looks fine than store the reference in db otherwise delete.

What is the best way to implement this?

Limitations:

1). We don't want to rework on the existing legacy code and put a check in every API.

2). This service should not call all the other APIs to store or re-trigger etc.