Social media decision
FeedGuardians
A technical user can build a functional comment-moderation prototype (ingest, classify, reply) in a few weeks, but reproducing partner-level API access, SOC2 compliance, and enterprise services that FeedGuardians sells is impractical for a solo builder.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All FeedGuardians alternatives, with the arithmetic →
What a replacement has to do
- Ingest comments/DMs from social platform APIs, classify intent/spam, apply action (hide/reply/route), persist events and metrics, surface a small admin UI for review and rule tuning.
What it still won’t have
- Official Meta and TikTok business partner status / direct partner-grade API access
- SOC 2 compliance and associated audit evidence
- Done-for-you setup and white-glove onboarding
- Enterprise features (SLAs, SSO, dedicated success manager, crisis playbooks)
- Scale-tested moderation accuracy and labeled training data used for product tuning
What remains hard
- Compliance and regulation
We're a certified Meta Business Partner, ensuring complete compliance with automation standards across Instagram and Facebook.
- Compliance and regulation
FeedGuardians is a TikTok Business Partner
- Compliance and regulation
SOC 2 compliant.
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 2 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal FeedGuardians replacement as a hosted service using: Django + Postgres, React admin UI, Celery workers, and OpenAI (or similar) for classification and reply generation. In scope: OAuth/connectors for Instagram, Facebook, TikTok, and Bluesky (webhook or polling), webhook ingestion endpoint, normalized event DB schema, classification pipeline that tags spam/toxicity/intent/sentiment, auto-reply templating and outgoing API integration to post replies or hide comments, an admin dashboard to review/autorespond/escalate, basic analytics (counts, avg reply time), and configurable moderation rules. Out of scope: SOC2 audit, formal Meta/TikTok partner onboarding, white-glove onboarding services, multi-tenant enterprise SLAs, and advanced crisis playbooks. Include error handling for API failures, retries, idempotency, tests for ingestion/classification/reply flows, and a Docker Compose deployment and a small Terraform script for a single-node production on a cloud VM.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 3 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-3
- Evidence score64
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 3
Every page the run actually retrieved.
- official productFeedGuardians – AI Comment Moderation for Social Media
- official pricingPricing – FeedGuardians AI Comment Moderation
- open sourcenz-m/SocialEcho
Integrity checks
What held up, and what did not.
