What we do
Continuously collect infringement-related links and images across platforms, building an actionable lead pool for your team.
Automatically locate trademark positions and variant features to improve pre-screening hit rates for trademark infringement cases.
Auto-remove non-infringing samples, then classify remaining items as 'Infringing' or 'Suspected'—enabling fast human review.
How it works
Five structured steps that transform raw infringement signals into review-ready evidence—reducing expert dependency while maintaining decision quality.
Continuously harvest infringement-related links and product images across major e-commerce platforms and marketplaces. Every listing is captured and indexed for downstream processing.
We build a comprehensive lead pool from Amazon, Temu, eBay, TikTok Shop, Shopee, and 25+ other platforms—no manual searching required.
Automatically eliminate non-infringing samples from the pool. Visual AI compares product images against registered brand assets, filtering out clear negatives before human review.
Traditional keyword matching misses up to 60% of infringements. Our Visual Language Model (VLM) catches logo variants, modified packaging, and design replicas that text searches can't find.
Remaining samples are classified into 'Infringing' and 'Suspected Infringing' tiers, with structured evidence points attached to each item for rapid human confirmation.
Each labeled item includes confidence scores, visual comparison data, and seller metadata—everything a reviewer needs to make a fast, defensible decision.
Reviewers work through pre-labeled, evidence-rich queues instead of raw listings. A single glance is often sufficient to confirm or dismiss each case.
This workflow delivers 10-20x productivity gains compared to traditional manual screening—without sacrificing decision quality or auditability.
Confirmed cases are packaged with platform-compliant evidence and handed off to your agency or law firm for takedown filing and enforcement action.
Evidence packages include timestamped screenshots, image comparison reports, and seller data summaries formatted for Amazon, eBay, and major IP registries.
Book a demo to assess the improvement potential of your current manual process.
核心能力
跨平台持续采集侵权相关链接与图像，构建可运营的线索池，为团队提供稳定的工作输入。
自动定位商标位置与变体特征，提升商标侵权初筛命中率，减少漏查与误判。
自动剔除非侵权样本，并将余下样本标注为'侵权'与'疑似侵权'，便于人工快速复核确认。
工作流程
五个结构化步骤，将原始侵权信号转化为可复核的证据队列——降低经验依赖，同时保持判断质量。
持续采集主流电商平台上的侵权相关链接与商品图像。每条商品上架后数小时内即可被捕获并索引，进入下游处理流程。
我们覆盖亚马逊、Temu、eBay、TikTok Shop、Shopee 等 25+ 个平台，构建完整的线索池——无需手动搜索。
从线索池中自动剔除非侵权样本。视觉AI将商品图像与注册品牌资产进行比对，在人工复核前过滤掉明显的非侵权项。
传统关键词匹配会漏掉高达 60% 的侵权行为。我们的视觉大模型（VLM）能够识别Logo变体、修改过的包装以及文字搜索无法发现的设计仿冒品。
剩余样本被分类为'侵权'和'疑似侵权'两个层级，每条记录附带结构化证据点，供人工快速确认。
每条标注记录包含置信度评分、视觉对比数据和卖家元数据——复核人员做出快速、可追溯决策所需的全部信息。
复核人员处理预标注、证据丰富的队列，而非原始商品列表。通常扫一眼即可确认或排除每个案件。
相比传统人工筛查，此工作流程可实现 10-20 倍的人效提升——同时不牺牲判断质量与可审计性。
已确认案件附带符合平台规范的证据包，交接给您的机构或律所进行下架申请与维权执行。
证据包包含带时间戳的截图、图像对比报告，以及按亚马逊、eBay 和主要知识产权登记机构格式整理的卖家数据摘要。
预约演示，基于真实样本规模评估现有人工流程的可提升空间。