Image MIME Reference
FACTI
BlockFact Image
image/vnd.blockfact.facti
VS
JPEG AI Image Sequence
image/jais
JPEG-AI-Sequence
A complete technical comparison of BlockFact Image and JPEG AI Image Sequence — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.
Equal browser support
Feature Support
| Feature | FACTI | JPEG-AI-Sequence |
|---|---|---|
| Transparency (Alpha) | Yes | Yes |
| Animation Support | ✕ No | Yes |
| Progressive Loading | ✕ No | Yes |
| HDR Support | Yes | Yes |
| EXIF Metadata | Yes | Yes |
| ICC Color Profile | Yes | Yes |
BlockFact Image
image/vnd.blockfact.facti
Extension
.facti
Container
BlockFact Authenticated Container
Compression
Container (Inherits payload compression, e.g., JPEG/PNG)
Algorithm
None (Pass-through to embedded payload)
Color Depth
Inherited from payload
Developed by
BlockFact
Released
2025
Magic Bytes
Unknown (Proprietary Container)
JPEG AI Image Sequence
image/jais
Extension
.jais
Container
ISOBMFF / HEIF Image Sequence
Compression
Lossy (Variational Autoencoder / Neural Network)
Algorithm
Deep Neural Network (Variational Autoencoder with Hyperpriors)
Color Depth
8-bit, 10-bit, 12-bit, 16-bit, Wide-gamut & HDR
Developed by
Joint Photographic Experts Group (ISO/IEC JTC 1 / ITU-T)
Released
2025
Magic Bytes
.. .. .. .. 66 74 79 70 6A 61 69 73 (Size + ftypjais)
Browser Support Comparison
| Browser | FACTI | JPEG-AI-Sequence |
|---|---|---|
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✕ | ✕ |
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✕ | ✕ |
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✕ | ✕ |
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✕ | ✕ |
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✕ | ✕ |
FACTI
FACTI Strengths
- Provides undeniable, mathematically verifiable proof of a photo's origin (time, location, and device) via the StarkNet blockchain [1.3.1]
- Privacy-first design utilizes zero-knowledge proofs (Groth16), meaning the actual image is never uploaded to a central server or blockchain
- Invisible watermarking ensures that even if the image is screenshotted or cropped, tampering can be detected
Limitations
- Lacks native rendering support in web browsers and standard image viewers, requiring specialized software to view
- Requires blockchain registration at the moment of capture, making it incompatible with existing legacy photos
- The proprietary nature of the container limits integration to environments supporting the BlockFact SDK
JPEG-AI-Sequence
JPEG-AI-Sequence Strengths
- Extends the state-of-the-art compression efficiency of JPEG AI to multi-frame image sequences and short animations
- Allows machine vision algorithms to process temporal sequences (like surveillance bursts) directly in the compressed latent domain, saving immense computational power
- Utilizes the robust, industry-standard ISOBMFF container for metadata, timing, and multi-track encapsulation
Limitations
- Lacks native decoding support in current web browsers, operating systems, and video players
- Decoding neural-network-compressed sequences requires significant compute overhead on hardware lacking dedicated AI accelerators (NPUs/GPUs)
- Adoption is hindered by competition with established sequence formats like AVIF, HEVC (HEICS), and modern video codecs
When to choose which format
FACTI
Use FACTI when…
- Journalism and Media Authentication
- Legal and Insurance Evidence
- AI Deepfake Prevention
- Content Provenance and Authorship
JPEG-AI-Sequence
Use JPEG-AI-Sequence when…
- Machine Vision and AI Video/Burst Workflows
- Cloud Storage Animation Optimization
- Focal Stacks and Medical Volumetric Slices
- Visual Surveillance Sequences