About
Attestiv is an AI-powered media authenticity and forensics platform that detects deepfakes, manipulated images, videos, audio recordings, and fraudulent documents. It uses machine learning and computer vision algorithms to analyze digital content for signs of tampering, synthetic generation, or AI-based manipulation, providing a confidence score and detailed forensic report on each asset analyzed. The platform also offers proactive media notarization, enabling users to authenticate content at the point of capture via mobile apps or embedded SDKs. This creates a tamper-evident digital fingerprint and chain of custody, making it suitable for industries where evidence integrity is critical — such as insurance claims processing, legal proceedings, journalism, and financial KYC workflows. Attestaiv exposes its capabilities through a REST API and SDK, allowing enterprises to integrate deepfake detection and media authentication directly into their existing applications and workflows. Primary customers include insurance companies combating claims fraud, news organizations verifying source footage, legal and law enforcement teams validating digital evidence, and financial institutions verifying identity documents.
Key Features
- Deepfake & Manipulation Detection: Analyzes images, videos, audio, and documents using AI to identify signs of synthetic generation, digital manipulation, or tampering, returning a detailed forensic report and confidence score.
- Media Notarization at Capture: Allows users to authenticate media at the moment it is created via mobile app or embedded SDK, establishing a tamper-evident digital fingerprint and verifiable chain of custody.
- REST API & SDK Integration: Provides a developer-friendly API and SDK so organizations can embed deepfake detection and media authentication capabilities directly into their own applications and workflows.
- Document Fraud Detection: Scans identity documents, contracts, and other files for signs of alteration or forgery, supporting KYC, insurance, and legal verification use cases.
- Audit Trail & Reporting: Generates detailed audit logs and reports for analyzed media, giving organizations a defensible record of authenticity assessments for compliance and legal purposes.
Pros
- Multi-Media Coverage: Handles images, video, audio, and documents in a single platform, reducing the need for multiple point solutions to address different media types.
- Proactive Authentication: The notarization feature lets organizations authenticate content at capture rather than only after the fact, providing a stronger chain of custody for high-stakes workflows.
- Enterprise API Access: The REST API and SDK make it straightforward to integrate forensics capabilities into existing enterprise systems without requiring manual uploads to a standalone portal.
- Industry-Specific Use Cases: Directly addresses fraud prevention scenarios in insurance, legal, journalism, and financial services, with workflows and reporting tailored to those verticals.
Cons
- Enterprise-Only Pricing: Pricing is geared toward business and enterprise customers with no publicly listed self-serve or free tier, making it less accessible for individuals or small teams.
- Detection Accuracy Limitations: Like all deepfake detection tools, accuracy can vary with novel or highly sophisticated manipulation techniques, meaning results may require human review for high-stakes decisions.
- Limited Public Documentation: Detailed technical documentation, API references, and benchmark performance data are not easily accessible without engaging the sales process, making evaluation harder upfront.
