Join the Verifiable
AI (r)evolution.
We execute AI agents and operate data runtime in isolated hardware enclaves with continuous transparent auditing. Every operation is verifiable, every piece of data remains private, every execution is auditable.
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Generative AI demands your most valuable asset: your data. To unlock the true potential of LLMs, companies are forced to expose sensitive data and intellectual property to third-party infrastructures that operate as "black boxes."
The Unbalanced Scale
AI Capability
Requires Data
Data Security & Control
Requires Control
The current model is flawed. DOOOR corrects the imbalance, replacing social trust with mathematical proof.
We Replace Promises with Proofs.
Our architecture uses Verifiable Confidential Computing to create cryptographic certainty. Every step is protected in hardware, generating an audit trail that anyone can verify at any time.
The Old Model: Based on Trust
Contract
Relies on legal agreements to promise data protection, depending on contractual enforcement rather than automated, built-in security.
Privacy Policy
Depends on a company's stated rules for data handling, trusting that the policy is followed without providing a technical method for verification.
Brand Reputation
Uses a company's public image and history as the primary guarantee for operational integrity, relying on social trust rather than cryptographic proof.
The Dooor Model: Based on Proof
Hash Chain
Creates a tamper-proof, sequential record of operations. Each action is cryptographically linked, ensuring an unalterable and verifiable history.
Hardware Signature
Embeds a unique, unforgeable cryptographic signature from the processor itself into every action, providing physical proof of execution integrity.
Transparent Auditing
Allows any auditor to cryptographically verify the integrity of the code running inside our hardware enclaves, ensuring transparency where trust is normally blind.
The Architecture of Verification:
Our solution is based on four interconnected pillars
that replace promises with cryptographic proofs.
Foundation in Trusted Hardware (TEE)
Our workloads operate in Trusted Execution Environments (TEEs). They are hardware enclaves that isolate code and data in use, making them inaccessible even to the cloud provider. Security is etched into the processor.
CPU & GPU Protection: Secure execution on AMD SEV-SNP and NVIDIA H100.
Zero Trust Firewall: A hardware firewall prevents data exfiltration by blocking any unauthorized communication.
Active Privacy and Data Sovereignty
Use the most powerful LLMs on the market without ever exposing your raw data. Our architecture proactively ensures privacy within the TEE before any external interaction.
Pre-Call Anonymization: Sensitive data is identified and anonymized in the TEE before being sent to APIs like Gemini or GPT-4.
Zero-Risk Fine-Tuning: Our "Knowledge Distillation" process creates synthetic datasets for training. The LLM learns your business logic but never sees the original data.
Immutable Audit Trail
Build modular AI systems with the guarantee that every step is transparent and verifiable. We use a robust agent architecture to decompose complex tasks into auditable subtasks.
Supervisor-Worker Architecture: Orchestrate multiple specialized agents for maximum flexibility and control.
Immutable Audit Trail (Chain-of-Calls): Each action generates an immutable record, digitally signed within the TEE.
Hybrid Infrastructure and Verification
Our hardware-based security allows us to decouple trust from infrastructure, optimizing cost, resilience, and performance in ways impossible in a traditional model.
Infrastructure Independence: Deploy workloads on centralized cloud (GKE), decentralized networks (Akash), and use blockchain (ICP) for resilient backups.
Zero-Knowledge Proofs (zk-SNARKs): For deterministic processes, we generate mathematical proofs that a computation was executed correctly.
Remote Attestation:
The Technical Proof of Trust
Trust is replaced by a cryptographic process where the hardware acts as a neutral arbiter, proving the integrity of the environment and the code inside it. This is how you verify the execution remotely:
Measurement
Hardware calculates hashes (SHA256) of the firmware and application container.
Generation
The application requests an "attestation quote" that bundles the hashes.
Signature
The processor signs the report with an inaccessible private key.
Verification
You validate the signature and compare the hashes, obtaining irrefutable proof.
Real Applications for Critical Challenges.
Private Fine-Tuning for Regulated Industries
Train expert LLMs in healthcare, finance, or law using your proprietary data, with the cryptographic guarantee that no sensitive information will be leaked.
Verifiable Data Clean Rooms
Collaborate with partners to extract insights from combined datasets without either party exposing their raw data. Generate mathematical proofs of compliance for each query.
Auditable AI Compliance
Prove to regulators and customers that your AI systems operate exactly according to defined policies, with an immutable and third-party verifiable audit trail.
Multi-party Data Analysis
Consortiums can analyze collective data to identify fraud or market trends without centralizing or exposing each member's information.
Automated Compliance for Healthcare
Hospitals can deploy AI with built-in, automated HIPAA compliance. Analyze patient data to gain valuable medical insights, with the cryptographic guarantee that no Protected Health Information (PHI) is ever exposed.
Confidential Model Validation
Banks can validate complex risk models without exposing proprietary algorithms or trade secrets. Provide mathematical proofs of accuracy to auditors and regulators, ensuring your intellectual property remains completely secure.
Complete Technology Stack
Robust market-standard tools combined with cutting-edge innovations in security and decentralization.
Position Your Architecture
for the Future.
If you are ready to move beyond traditional vendor relationships and solve your most critical challenges with Verifiable AI, let's begin the conversation.