How we reduced our review time by 90%
Tags: opensource, webdev, python, ai
Published: 2023-05-11 21:30:47

At [Apollo](https://apolloapi.io), we use a no-code automation platform to allow users to manage their integrations & tasks. There are many debates over whether automating content moderation is a one-size-fits-all approach, it's not. AI powered content moderation has become table stakes in protecting and enhancing user experience at scale, but for us, visibility into other areas of enterprise/personal decision making led us to use tools like automation rules & workflow platforms. 

## TLDR;
One case study for content moderation from [YikYak](https://yikyak.com/), we migrated from [Retool](https://retool.com/). 

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/24ry4zjl0f19sok7moqf.png)

## The bigger, the slower
With all the advantages, there are a few drawbacks to using retool and a standalone automation system for task monitoring/completion. We noticed a particular drawback when scaling the number of users and amount of activity with each one: The time it takes to detect bad actors accurately and then investigate. So a typical task for a investigation would run anywhere between 3 minutes to 4 days. And that's for each time an automated flag was created or a user report was sent.

More than that, truly having accurate data was a nightmare. Standalone automation systems (environments with one AI model) would score correctly only a fraction of the time.

This amount of time spent investigating and analyzing to make an informed decision reduced the moderator efficiency and wasted collectively so much talented people's time. Being a social app dedicated to curating safer community, this was unacceptable.

## Debugging the slowest tasks
Inspecting a typical 4 day case/support ticket, it was clear that two specific steps took almost 70-80% of the overall time:

- Gathering metadata from existing platform policy, account information and community guidelines: 4 Hours
- Connecting historical data to recent events: ~1 day

## Migrating from Standalone Automation Systems to Integrated Automation System
Retool coupled with our standalone automation system provided a fast, efficient infrastructure as a service toolkit, and from some of the benchmarks, there was a massive improvement in active response time when migrated off of a independent automation system to an integrated automation system like [Apollo](https://apolloapi.io).

Moving from Retool + Standalone automation took around 2 minutes, the migration to integrated automation ([Apollo](https://apolloapi.io)) was effortless: Just adding metadata about your internal databases and a click of a button, that's all. The aggregation and integration for each database/api resource were efficiently synced, in... wait for it... just milliseconds! And that's without any code at all! After integrated automation tools like [Apollo](https://apolloapi.io) increases the accuracy of the scored content, it takes less than 40 seconds to deploy and integrate multiple AI models under one API.

Reducing ~3 minutes to 13 seconds from the standalone's system time for every investigation and accuracy for moderators is a HUGE win. 

## Summary
Reducing our active response times from 3+ minutes to around 13 seconds significantly impacts the user experience of our community. It also reduces the overhead incurred by regulatory violations or non-compliance, which can run a bill up to $400k a month! You can checkout our beta on our Github repository.