Problem

Cinder addresses the operational challenge of protecting digital platforms from abuse, fraud, manipulation, and AI-powered harms at internet scale. Trust and safety teams must make millions of high-stakes decisions across content, users, accounts, and networks, while threats evolve faster than conventional rules and classifiers. The economic pain is the cost of human review, slow investigations, inconsistent enforcement, and regulatory or reputational exposure; Cinder cites more than 100,000 hours saved through automation and 94% of human review automated for one customer.

The clearest use case is real-time content moderation: detecting and removing adult content, extremism, CSAM, non-consensual intimate imagery, and other policy violations. The same infrastructure extends to coordinated-abuse investigations, intellectual-property enforcement, account takeover and user-fraud detection, and other workflows where a platform must act quickly without sacrificing context or oversight.

Product / Service

Cinder is a trust and safety operations platform built around configurable AI agents and agentic workflows. Organizations connect their policies, data, review teams, enforcement paths, vendors, and AI systems in one operational surface. Agents monitor for anomalies, analyze content and user or entity history, apply policy-specific decisions, route edge cases to human reviewers, and record decisions and reasoning for audit. Teams can challenge or override actions, continuously improve the agents through review feedback, and benchmark both human reviewers and automated systems.

The delivery model combines software with expert services, including AI red teaming and evaluation, data labeling, managed operations, policy and AI support, and applicant-fraud detection. Customers can deploy Cinder standalone or integrate existing models and tools, with role-based access, SSO, encrypted data, explainability, audit trails, and compliance support. The intended benefit is a single command center that increases moderation accuracy and throughput while preserving human control and producing a durable system of record for safety decisions.

Market

Cinder competes in trust and safety operations software, spanning content moderation, digital-platform abuse prevention, fraud and account-takeover detection, copyright enforcement, and AI safety. The supplied research does not identify named direct competitors; instead, it contrasts Cinder with off-the-shelf classifiers and positions the company as infrastructure for organizations managing abuse and safety at scale. Its customer references and case studies include Synthesia, OpenAI, Stability AI, Character.AI, Midjourney, ElevenLabs, BeReal, Depop, Black Forest Labs, Zello, and Patreon.

Cinder is not presented as pre-revenue: it reports a $41 million Series B and multiple enterprise deployments, although the research does not provide revenue figures. Reported operating scale includes more than 3 billion end-users protected, more than 400 million events processed daily, more than 5 million pieces of content reviewed, greater than 97% AI moderation accuracy in a cited result, and reductions in moderation queues and repeat-offender abuse. These figures are company-reported case-study and marketing metrics, so they demonstrate traction and enterprise adoption rather than independently verified financial performance.