modTriage

Inspiration

Reddit moderators deal with an overwhelming number of reports every day, ranging from spam and harassment to coordinated abuse and misinformation. Most moderation queues are chronological, meaning moderators often waste time manually sorting through low-priority reports while critical threats remain buried.

We wanted to build a system that reduces moderation fatigue and helps moderators focus on the most dangerous content first. Instead of replacing moderators with AI, we focused on augmenting moderator decision-making through intelligent prioritization, behavioral analysis, and workflow automation.

ModTriage was inspired by the idea that moderation tools should act like an intelligent assistant — surfacing risk, providing context, and accelerating response time while still keeping humans fully in control.

What it does

ModTriage is an AI-assisted moderation triage system built on Reddit’s Devvit platform.

When a post or comment is reported:

The app analyzes the content using Claude AI Evaluates behavioral risk signals from the author’s history Measures reporter credibility and prior reporting accuracy Generates a composite severity score from 0–100 Prioritizes the moderation queue based on threat level

The dashboard provides moderators with:

Real-time prioritized moderation queue AI-generated risk analysis User history and behavioral signals Similar past moderation cases One-click moderation actions (remove, ban, warn, approve, skip) Audit logs for accountability and transparency

Low-priority reports are automatically grouped into daily digests to reduce moderation overload and improve workflow efficiency.

How we built it

We built ModTriage entirely on Reddit’s Devvit platform using TypeScript.

Core Technologies Devvit triggers for real-time moderation events Devvit custom posts for the interactive moderation dashboard Devvit KV Store for persistent report storage and audit logging Devvit Scheduler for automated daily digests Reddit moderation APIs for moderation actions Anthropic Claude API for AI-powered content analysis Architecture

The system follows an event-driven architecture:

A report trigger activates when content is reported The app gathers: content text report reason user moderation history reporter credibility data Claude AI evaluates the reported content A weighted scoring engine calculates severity Reports are stored and ranked in the moderation queue The dashboard updates in real time for moderators

We also implemented:

explainable AI signals score breakdown visualization moderation audit tracking fallback scoring for API failures configurable moderation thresholds Challenges we ran into

One of the biggest challenges was balancing automation with moderator trust. Fully automated moderation can lead to false positives and lack of transparency, so we focused heavily on explainable scoring and human-in-the-loop workflows.

Another challenge was designing a scoring system that combines:

AI semantic analysis behavioral trust signals reporter credibility

in a way that feels reliable and practical for real moderation scenarios.

Working with real-time event-driven moderation flows also introduced challenges around:

queue consistency sorting priority synchronization of moderation actions handling API failures gracefully

We also spent significant time designing a UI that could surface large amounts of moderation context without overwhelming moderators.

Accomplishments that we're proud of

We are proud that ModTriage feels like a real moderation product rather than just a hackathon prototype.

Some highlights include:

A fully interactive Reddit-native moderation dashboard Real-time AI-assisted threat prioritization Explainable moderation signals instead of opaque AI decisions Integrated user behavioral analysis One-click moderation workflows Automated low-priority batching to reduce moderator fatigue Persistent audit logging for moderation accountability

We are especially proud that the system improves moderator efficiency while still preserving moderator control and transparency.

What we learned

This project taught us that moderation is not just a technical challenge — it is a workflow and trust problem.

We learned:

AI works best as a decision-support system, not a replacement for moderators Explainability is critical for moderation tools UX matters just as much as model quality in operational tooling Small workflow optimizations can dramatically reduce moderator fatigue Event-driven systems are extremely powerful for community infrastructure

We also gained hands-on experience building native Reddit applications with Devvit, including triggers, custom posts, scheduling systems, and moderation APIs.

What's next for ModTriage

Next, we want to expand ModTriage into a more adaptive moderation intelligence platform.

Future plans include:

Community-specific moderation models Reputation systems for reporters and trusted contributors Cross-subreddit spam and brigading detection Moderator analytics and queue performance metrics AI-generated moderation summaries Smart escalation workflows for repeat offenders Multi-moderator collaboration features Fine-tuned scoring thresholds per subreddit category

We also want to improve onboarding and configuration so moderators can install and customize ModTriage in just a few clicks.

Our long-term goal is to help moderators spend less time fighting moderation overload and more time building healthy communities.