Your guide to selecting the best Trust and Safety tools Download the Buyer's Guide to Trust and Safety 2.0

ActiveScore

Automated AI
content detection
fueled by intelligence

Empower your team to make faster decisions
with greater accuracy

Trusted by these companies and more

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Brave Software Content Moderation Case Study
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ActiveFence Clients
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Seamless integration for a streamlined moderation process

Quick Setup

Integrate one API to start using our AI-driven automated detection. Add risk thresholds aligned to your policy, so that high-risk items will be automatically removed and benign items ignored: allowing you to reduce violation prevalence while reducing human review to only those items that require it.

Custom policy thresholds bar showing levels from automatically keep at 0% to automatically remove at 100% with manual review between 50% and 75%.

Automated Scoring

Send text, images, audio, or video for analysis based on our contextual AI models, fueled by intelligence of 150+ in-house domain and linguistic experts. For each item, our engine will generate a risk score between 1-100 indicating how likely it is to be violative, providing indicators and a description of the identified violations to make human decisions easier and faster.

ActiveScore Automated Scoring

Ongoing Optimization

Improve accuracy with a continuous, adaptive feedback loop that automatically trains our AI and adjusts risk scores based on every moderation decision.

Download our Solution Brief

ActiveFence Findings: Contextual AI in Action

Illustration of a mobile phone screen displaying a job opening for a part-time job for students. Indicators highlight the post image, description text, and URL, with a warning that the URL is detected as a malicious CSAM group link.
Eliminating Blindspots

Uncovering CSAM group promoted in a seemingly harmless profile

ActiveScore child safety models automatically flagged a seemingly benign picture and description as high risk due to a promotion of a link to a malicious CSAM group with 67K members within the profile itself. By analyzing it against our intel-fuelled database of millions of malicious signals, including the profile’s complete metadata, the profile was immediately flagged to the platform and removed.

A smartphone screen showing a profile for a seller named Javi88, who is selling soaps. The profile has a high hate speech detection score of 98%, with annotations indicating 0% for profile image and description.
Multilingual coverage

Detecting malicious
content in Spanish in a
benign context

ActiveScore identified racial slurs in the review comments of a listing appearing to promote sales of artisanal soaps. By analyzing the post’s full metadata against 100+ languages, ActiveScore detected Spanish text as violative, saying: “Here comes Chaca down the alley killing Jews to make soap” and the review was automatically removed.

Mobile phone screen showing a song flagged as hate speech in a proprietary database.
Media Matching

Catch more violations with automated media matching

ActiveScore hate speech models automatically detected multiple white supremacist songs with media matching technology when compared to ActiveFence’s proprietary database that contains the largest database of hate speech songs. Within seconds, it found matched duplicates and similarities to provide a high risk score.

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