Invisible Metadata for AI-Generated Content

Embed invisible metadata in AI-generated content to verify authenticity, track provenance, and build trust.

What is EncypherAI in Simple Terms?

EncypherAI works like a digital watermark for AI text that you can't see or feel.

When AI creates text, we add an invisible signature using special Unicode characters that humans can't detect. This signature contains information about when and where the text was created, and who created it.

Unlike AI detectors that make guesses (and often wrong ones), our approach provides cryptographic proof of AI origin. It's like having a tamper-proof seal on a document that can be verified with 100% accuracy.

The best part? The text looks exactly the same to human readers, but computers can easily verify its authenticity.

Use Cases

Content Authenticity

Verify the source and authenticity of AI-generated content with embedded metadata that remains invisible to users.

  • Cryptographically secure verification
  • Tamper-evident signatures

Provenance Tracking

Track the origin and history of content across platforms while maintaining the integrity of the original text.

  • Model and timestamp information
  • Cross-platform compatibility

Compliance & Transparency

Meet regulatory requirements for AI content disclosure without disrupting the user experience.

  • Zero false positives in detection
  • Regulatory compliance support

Academic Integrity

For Educators

Protect students from false accusations with reliable verification of AI assistance.

  • Eliminate false positive accusations
  • Support transparent AI policies
  • Maintain academic trust

For Students

Use AI tools confidently with proper attribution that can be verified.

  • Avoid wrongful accusations
  • Demonstrate responsible AI use
  • Maintain academic integrity

Watch Our Introduction

Learn how EncypherAI works and see a demonstration of our invisible metadata embedding technology.

Key Features

Invisible Embedding

Metadata is embedded using Unicode variation selectors that are invisible to humans but detectable by machines.

Streaming Support

Works seamlessly with streaming responses from LLMs like OpenAI, Anthropic, and others.

Content Verification

Verify the integrity of content with built-in HMAC authentication to detect tampering.

Framework Agnostic

Integrates with any Python framework or application with minimal configuration.

Ready to Get Started?

Check out our documentation to get started or explore our features for more information.