A Community Platform operating in Delhi (NCR region)
Built a toxic comment filter to reduce moderator workload on a large community forum.
Headline Result
Automated moderation on 70% of flagged content, cutting moderator backlog significantly.
01.The Challenge
A small volunteer moderation team was overwhelmed by the volume of flagged posts and comments as the community grew.
02.The Solution
Built a toxicity classification model that auto-actions clear-cut cases and routes ambiguous ones to human moderators. Keeping the interface simple enough for Community Platform's non-technical staff to use directly was as much a design constraint as the underlying model itself.
03.How It Went
- 1Began by auditing what Community Platform already had in place, thier platform had video , image & text based data that needed moderation, text moderation was kind of easy compared to others
- 2Built and validated an initial version for Community Platform using Python, testing it against real historical data before anything went near production.
- 3Once the core system was working, the focus shifted to integration — making sure it fit into how Community Platform's team already worked, not the other way around.
- 4Closed out the engagement with Community Platform with a handover session covering how the system worked and what to watch for as usage scaled.
04.Results
- Automated moderation on ~70% of flagged content
- Cut moderator backlog significantly during peak activity
- Kept humans in the loop for all ambiguous cases
- Community Platform engaged for a smaller follow-on scope after seeing the initial results
“Communication throughout the Platform engagement was clear the whole way through, even when the scope shifted slightly once we saw the first version working.”
— Head of Data, A Community Platform ( GYM ) operating in NCR region