Dimension scores are derived from public data and fields; weighted into the composite. Reference only.
ForensiCode is a “human authorship evidence” tool designed for academic integrity and assessment scenarios. It does not perform traditional AI text detection or analyze submitted content. Instead, it records the student’s writing process and generates a verifiable process report, providing supplementary evidence when authorship is in question.
The product uses a lightweight Word add-in. As students write normally, the add-in records high-level writing activity on the local device. It then generates a process report that is cryptographically linked to the document. Upon submission, students provide both the main document and the report to their institution. If a dispute arises later, staff can verify the authenticity of the report locally without uploading anything to an external server.
The source material does not disclose pricing, free trial availability, payment methods, or licensing model. In terms of integration, it only clearly supports a Word add-in and file submission through existing institutional workflows. It does not specify whether LMS, Moodle, Canvas, Turnitin, Google Docs, API, SSO, or bulk administration capabilities are supported. Its readiness for large-scale deployment therefore needs to be confirmed with the vendor.
Its biggest advantage is that it avoids the false-positive issues associated with probabilistic AI detection. It does not draw conclusions about the text content or directly accuse students, making it more aligned with fairness, transparency, and due process. Its design—local recording, local verification, and no external servers—is also relatively privacy-friendly. The limitations are clear as well: it cannot determine whether a text was generated by AI, and can only provide process-based evidence. Public information also does not explain the details of recorded metrics, resistance to circumvention, admin console features, or compatibility with Chinese-language environments.
ForensiCode is suitable for university academic integrity offices, assessment design teams, instructors, and teaching improvement staff, especially institutions that want to reduce harm from AI-detection false positives while still handling authorship disputes. Access, payment, and deployment availability in mainland China are not specified, so their status is currently unknown. If it cannot be used, alternatives or complements may include local version control, document revision history, LMS submission workflows, or other academic integrity tools.
⚠ This review is compiled from public sources and does not constitute a purchase recommendation. Verify all facts on the vendor's official site. Verify on forensicode.com official site.
forensicode.com is an United States AI Apps provider. TG4G tracks its product information, an overall rating of 7.0/10, and a China-accessibility score of Workable. Click "Visit Official Site" to reach forensicode.com directly.