Authenticating AI for
Trust and Accountability
TripleID isn't just a company. It's a stand.
For truth. For trust. For what's real.
Watch the film.
See why it matters.
Secure by Design.
Built for Trust. Built for Good.
In an era where artificial intelligence can fabricate reality in seconds, trust is no longer a given. It must be engineered. We believe in humanity’s drive to build and progress, but also recognize the responsibility to protect that vision from those who seek to exploit it.
TripleID emerges not to stop AI, but to ensure it serves with integrity. From hardware to intention, this is a call to re-center technology around its true purpose: people.
Built for Trust
Built for Good
Technology and Solutions
AuthentAI for Trust and Security
TripleID's AuthentAI is a foundational technology platform designed to tackle today’s critical AI governance and security challenges using Secure By Design. In an era where AI systems face issues like a lack of trust, regulatory scrutiny, security vulnerabilities, and limited auditability, AuthentAI provides a robust solution to foster trust, accountability, and transparency.
The Challenge
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Lack of Trust in AI Outputs: AI-generated content, such as misinformation or biased decisions, often lacks verifiable origins, eroding user and stakeholder confidence.
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Regulatory Compliance Gaps: Opaque AI processes hinder regulatory compliance, making accountability difficult for organizations.
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Security Vulnerabilities: AI systems are susceptible to attacks like data poisoning or adversarial inputs, which can compromise their reliability and safety.
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Limited Auditability: Black-box AI models obstruct error detection, bias mitigation, and system improvement, slowing ethical and technical progress.
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Stakeholder Disconnect: Regulators, developers, users, and insurers/insurees struggle to collaborate effectively due to the absence of a unified framework for AI oversight.
Our Solution
AuthentAI counters these challenges by utilizing proprietary, hardware-rooted intrinsic trust and evidence-based approaches to create unique digital signatures for AI systems and their outputs. These signatures act like secure, tamper-proof fingerprints, automatically generated to track and verify every AI action and result. They enable robust tracing, verification, and certification, creating a verifiable chain of custody for AI outcomes. This ensures:
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Trusted Outputs: Stakeholders can confirm the authenticity and integrity of AI results, combating misinformation and bias.
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Regulatory Alignment: Transparent audit trails support compliance with global standards, easing oversight for regulators.
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Enhanced Security: Hardware-based protections safeguard against tampering and attacks, ensuring system resilience.
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Actionable Audits: Developers can identify and address flaws, improving AI performance and ethics.
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Decentralized Verification: A shared platform empowers regulators, developers, users, and insurers/insurees to review, audit, and improve AI systems, providing insurers/insurees with confidence in AI reliability and risk assessment.
Tailored Secure-By-Design Platforms
Secure by Design (SBD) is paramount to building safety, security, and ethical alignment into AI systems from inception rather than treating them as add-ons. It calls for all stakeholders—developers, organizations, policymakers, researchers, and users—to collaborate in creating AI technologies that are inherently safe, resilient, and aligned with human values.
TripleID’s AuthentAI framework is a tailored SBD platform, engineered to embed uncompromised security into AI systems at the hardware level, customized for diverse ecosystems—from hardware/chip-level deployments to broad applications, especially for high-risk AI systems. Our approach hinges on three hardware-centric pillars:
1. Analysis and Design
Our SBD approach to the first analysis of AI’s security and governance risks is tailored to each deployment’s architecture. We dissect threats like unverified outputs fueling misinformation, non-compliant black-box processes, and vulnerabilities like data poisoning or adversarial exploits. We also target tracing bad intentions/actors—malicious entities leveraging AI for fraud or disruption—and weaponization, where systems are co-opted for harmful ends. By mapping these risks against audit gaps and stakeholder needs, we deliver a bespoke threat model, enabling targeted countermeasures and clear visibility for engineers and stakeholders alike.
2. Silicon-Level Trust Anchored in Hardware
At the core of our SBD lies proprietary, silicon-level intrinsic trust, engineered to root security directly in hardware, often at the chip itself. Unlike brittle software layers, our custom hardware modules are tamper-resistant and verifiably engineered for output. They generate unique digital signatures—cryptographically secure, hardware-bound markers tied to every AI operation and output—forming a robust chain of custody. Tailored to each system’s specs, this silicon-anchored approach ensures integrity, traceability, and compliance, giving engineers a dependable trust anchor across diverse AI pipelines.
3. Hardware-Agnostic, Embedded Solutions for Scalability
Our AuthentAI integrates flexible, embedded solutions into AI chips and systems, tailored to address foundational security and governance needs across heterogeneous environments. These hardware-agnostic modules—embedding in SoCs, GPUs, or ASICs, enable granular and evidentiary tracing, verification, and certification. This empowers engineers to audit and optimize systems while providing regulators, developers and insurers a decentrialzied, secured and scalable ways to validate AI integrity.
Use Cases
IoTs
Secure protocols
Autonomous Machine
Autonomous driving
Regtech
Compliance
Financial Services
Fraud prevention
Leadership Team
Support U.S. National Security policy and operational objectives in counter-terrorism, counter-intelligence, and cybersecurity.
John Felker
Chairman of the Board
Dr. Robert Riegle
Chief Executive Officer
Ernest B. Chambers Jr.
Chief Technology Strategy Officer