Where is my data stored, and how do I know my content is safe?

Checkstep does not store your content. Media is accessed by link through delegated access, so it stays in your infrastructure and is read only while it is being assessed. That keeps data residency under your control and removes most of the data-transfer questions that come up in a security review. The case metadata needed for audit, appeals and transparency reporting is retained.

How are coordinated campaigns detected?

Taken one post at a time, brigading and coordinated abuse often look mild. Checkstep assesses each case with its surrounding context rather than in isolation, and example-driven models can be trained on campaigns your team has already confirmed, so the same pattern is recognized earlier. Moderators see user history alongside each case, which is what makes a coordinated pattern visible at all.

What does VLOP systemic-risk reporting involve?

A Very Large Online Platform (VLOP) under the Digital Services Act is a service with more than 45 million average monthly active users in the EU. VLOPs carry extra duties, including assessing systemic risks and reporting on them. Checkstep produces the underlying numbers: what was detected, what was actioned, under which policy, and what happened on appeal.

How does moderation scale during a spike?

Automated scanning absorbs the volume. The constraint is human review, and you control that with thresholds: widening the band that is actioned automatically reduces what reaches your team during a surge. AI agents can work queues alongside your moderators, and queues stay ordered worst-first, so severity rather than arrival order decides what gets seen.

Trust & Safety Platform for Social Networks

Protect your social platform. Empower your community.

Keep conversations open, safe, and authentic with AI-powered moderation designed for online communities.

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Online social interactions, real world consequences

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Every single day, social platforms face escalating challenges - from harassment and hate speech to disinformation campaigns, coordinated manipulation, and exploitation. These behaviors don’t just harm individuals; they undermine public safety and community trust.

Left unaddressed, these threats drive user churn, regulatory scrutiny, advertiser pullback, and reputational damage. To safeguard both communities and brand integrity, social platforms need proactive, scalable moderation solutions.

81%

of people report encountering misinformation, hate speech, or harassment on major social platforms in the past year.

Benefits

Stronger online communities start with trust and safety

With AI-powered moderation, you can provide safe, engaging, and trustworthy social media spaces for your users, free from harmful content and bad actors.

Real-time decisions at platform scale

Sub-50ms decisions across posts, comments, images and DMs, at the volume a social platform actually runs at.

Coordinated harm detection

Pile-ons, inauthentic behavior networks and disinformation cascades, detected as patterns rather than isolated posts.

DSA and VLOP reporting built in

Generate transparency reports and meet systemic-risk duties as a very large online platform, without a separate compliance workstream.

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Strengthening online communities with trust and safety solutions

Our AI moderation platform is designed to help social media platforms reduce harmful behavior, stop disinformation at scale, and build the trust that keeps your communities engaged.

Automate moderation to let human moderators focus on what matters most

Send ‘suspicious content’ to our sophisticated AI reasoning model, Advanced ModBot, to take decisions on content. Updates to your policies are immediately learned by the bot. Keep humans in the loop and allow the bot to escalate when it’s not sure.

Streamline case management from flag to resolution

Manage flagged posts, comments and accounts in one central place with full visibility into violations. Case management gives your team clear context, policy alignment and actionable options - so you can review, escalate, or resolve cases quickly and confidently.

Create custom detection models in minutes, not months

Our technology-forward approach allows you to create custom models to detect what matters to your platform - in a matter of minutes. Gone is the need to wait months for a machine learning team to train a model from scratch.

Take user-level action to ban or suspend repeat offenders from your platform

Moderate at a content or user level to keep your platform safe from bad actors. Checkstep tracks a user’s history with your social platform, flagging past violations and offences, letting you make a decision on whether to remove just the content - or the user themselves.

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FAQs

Most frequently asked questions about Checkstep for social platforms

Learn more about our AI content moderation platform

Where is my data stored, and how do I know my content is safe?

Checkstep does not store your content. Media is accessed by link through delegated access, so it stays in your infrastructure and is read only while it is being assessed. That keeps data residency under your control and removes most of the data-transfer questions that come up in a security review. The case metadata needed for audit, appeals and transparency reporting is retained.
How are coordinated campaigns detected?

Taken one post at a time, brigading and coordinated abuse often look mild. Checkstep assesses each case with its surrounding context rather than in isolation, and example-driven models can be trained on campaigns your team has already confirmed, so the same pattern is recognized earlier. Moderators see user history alongside each case, which is what makes a coordinated pattern visible at all.
What does VLOP systemic-risk reporting involve?

A Very Large Online Platform (VLOP) under the Digital Services Act is a service with more than 45 million average monthly active users in the EU. VLOPs carry extra duties, including assessing systemic risks and reporting on them. Checkstep produces the underlying numbers: what was detected, what was actioned, under which policy, and what happened on appeal.
How does moderation scale during a spike?

Automated scanning absorbs the volume. The constraint is human review, and you control that with thresholds: widening the band that is actioned automatically reduces what reaches your team during a surge. AI agents can work queues alongside your moderators, and queues stay ordered worst-first, so severity rather than arrival order decides what gets seen.