Contact info on product images
Sellers embedding phone numbers and off-platform links in listings

Moderate text in images. Lasso's OCR moderation detects contact information, watermarks, and circumvention by hidden text in images.
Lasso reads rotated, colorized, tiny, and stylized text across 200+ languages.
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Filter out anything your specific platform rules do not allow.
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Catches policy violations in meme captions and overlays. Routes to auto-remove, flag for review, or approve.
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Each item shows: extracted text, original image, AI reasoning, and suggested action. Every human decision trains the system.
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Lasso detects 99.9% of text in images.
200+ languages including CJK, Arabic, Cyrillic, from one unified model.
Lasso extracts text the moment an image is uploaded, with predictable latency even at millions of images a day.
Three AI layers absorb the volume, enforce your rules, and surface only the grey areas. Your team reviews what is left, and each call sharpens the model.
Customizable moderation that lets you find the right balance between safety and user experience. So you protect your community without suppressing the culture that makes it worth joining.
One API. Clear dashboards. A moderation pipeline built around one-click actions and the right context, right where you need it.



OCR moderation extracts text baked into images, such as phone numbers, URLs, social handles, and slurs hidden in memes. Lasso then runs that text through the same moderation rules and AI that govern any other text on your platform, so image-borne text gets caught like a typed message. It covers the channel users reach for when they want to slip past text filters.
Text moderation reads the text fields users type into your platform. OCR moderation reads the text embedded inside images, which is the channel users use to bypass typed-text filters. Lasso runs both through the same four-layer pipeline, so a phone number in a photo is treated the same as one in a chat message.
It runs in four layers. Lasso's OCR first extracts text from the image across 200+ languages, then your custom rules filter anything your platform does not allow. The AI Moderator weighs context in captions and overlays and routes each item to auto-remove, flag, or approve. Anything in a grey area queues for human review with the extracted text, original image, AI reasoning, and a suggested action.
Yes. Lasso extracts rotated, colorized, tiny, and stylized text, including meme overlays and obfuscated leet speak. It also detects QR codes that redirect to external sites and reads payment addresses embedded in images. Your custom models define what counts as a violation.
Yes. Lasso reads phone numbers, social handles, Telegram usernames, and payment addresses hidden inside profile photos, listings, and avatars. Once extracted, that text runs through your rules so off-platform solicitation is flagged before it reaches your users. You decide per platform which contact patterns to block.
99.9% detection accuracy on policy violations. 99.9% text extraction accuracy across 200+ languages.
Yes. Confidence scores range 0–100. Set your automation threshold per policy: high-confidence flags auto-action, borderline flags route to human review. You tune it per policy and per industry.
Lasso's OCR extracts text in 200+ languages and scripts. CJK, Arabic, and Devanagari are individually optimized. You can configure different moderation rules per language if needed.
Yes. Common techniques detected: leet speak (c0d3 for code), homoglyph substitution (Cyrillic vs Latin lookalikes), strikethrough formatting, tiny text, QR codes redirecting to external sites, payment addresses in images. Your custom models define what counts as evasion.
Text extraction in realtime, no delay experienced by users. At millions of images, Lasso maintains predictable latency for real-time moderation.
Lasso's OCR moderation catches the text that bypasses every other filter. One pipeline, one API.
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