Human-in-the-loop comment approval at scale
When you need a human to approve before anything goes live: configurable approval queues, per-role permissions, bulk actions, and a full audit log. Regulated industries and high-stakes brands use this flow.
Commencer l'essai gratuitAvg comments needing human review after AI triage
Regulated industries (finance, healthcare, pharma) and high-stakes brands cannot let AI act without human approval. At the same time, manual review of every comment is impossible at scale. Teams need a workflow that lets AI do the triage and humans do the approval — without the queue becoming unmanageable.
FeedGuardians routes borderline comments to an Approval Queue with one-click decisions, per-role permissions, SLA tracking, and a full audit log. The AI triages the 97% of clear decisions automatically, and your human reviewers handle the 3% that require judgment.
Tout ce que le workflowincludes
One-click approval decisions
Each queued comment shows the classification, confidence score, and the rule that flagged it. Reviewers click approve, hide, delete, escalate, or allow-always in one tap.
Per-role permissions
Different reviewers can have different approval scopes. Junior reviewers can handle spam, senior reviewers handle brand-sensitive cases, only leads can handle escalations.
SLA tracking per queue
Set response SLAs per queue (e.g., "approve within 15 minutes"). Alerts fire when items are about to breach SLA.
Bulk approvals
Select 50 similar comments, approve them all with one click. The AI learns from the bulk decision and improves future classification.
Audit log for every decision
Every decision is logged with reviewer identity, classification, confidence, timestamp, and rule. Exportable for compliance and regulatory audit.
Mobile approval app
Reviewers approve from their phone via the FeedGuardians mobile web app. Good for after-hours and weekend coverage.
Du commentaire à resolution
AI triages incoming comment
New comment arrives. AI classifies it in under 2 seconds. Clear cases (spam, scams, obvious hate speech) are handled automatically.
Borderline comments queue
Anything the AI is not confident about — plus anything matching your manual review rules — routes to the Approval Queue with full context.
Human reviewer decides
Reviewer opens the queue (web or mobile), sees comment + AI suggestion + reason, clicks a decision. SLA clock tracks response time.
Decision logged and learned
Decision applied to the comment, logged in audit trail, and used to refine the AI's classifier. Similar comments in the future are less likely to need manual review.
S'intègre avec
Idéal pour
- Regulated industries (finance, pharma, healthcare)
- Enterprise brands with approval requirements
- Brand safety teams with compliance needs
- Agencies with client-side approval flows
- High-stakes launches needing human oversight
Commun questions
Yes. Create multiple queues with different routing rules. For example: legal-sensitive comments → legal team queue; brand-voice edge cases → marketing lead queue; everything else → general moderation queue. Each queue has its own SLA and audit log.
Configurables. Par défaut, les commentaires non approuvés restent dans l'état "retenu" indéfiniment et déclenchent des alertes au seuil SLA. Vous pouvez également configurer un délai d'escalade (par exemple, "après 60 minutes, escalader au responsable de la file d'attente") ou un délai d'action automatique (par exemple, "après 24 heures, appliquer automatiquement la suggestion de l'IA").
Oui. Chaque commentaire en attente montre la classification, le score de confiance, la règle spécifique qui l'a signalé, et un échantillon de commentaires historiques similaires. Ce contexte rend les décisions d'approbation beaucoup plus rapides et cohérentes.
Oui. Le journal d'audit inclut tous les champs requis pour la conformité SOC 2 et RGPD : identité de l'examinateur, horodatage, classification, règle, décision et toute note manuelle. Les journaux sont immuables après création et exportables au format CSV ou JSON pour un audit externe.
Oui. Sélectionnez plusieurs commentaires similaires (par classification, mot-clé ou compte) et approuvez-les en une seule action. L'IA utilise la décision en masse pour améliorer les classifications futures, réduisant ainsi le volume de la file d'attente au fil du temps.
Oui. FeedGuardians dispose d'une application web optimisée pour mobile afin que les examinateurs puissent approuver des commentaires depuis leur téléphone. Idéal pour la couverture en dehors des heures de bureau et le week-end. Des applications natives iOS et Android sont prévues.
Expédier le flux de travail
en quelques minutes
Configurez une fois, déployez sur chaque compte, laissez l'équipe se mettre au travail.
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