Geodd eliminates trust gaps in AI workloads with custom silicon, isolated execution, and customer controlled keys delivering secure, privacy first inference where data remains protected from chip to interface.
From silicon to API interface, every layer is engineered for confidentiality, no blind spots, no shared components.
Inference requests and results are never stored. Nothing persists beyond runtime, even in memory.
Decryption keys stay with you. Your data and models cannot run or be accessed without your release.
Dedicated single-tenant nodes and secure enclaves deliver consistent inference under 100ms.
Today’s inference providers rely on staff-level access, shared infrastructure and persistent storage. Compliance checkmarks don’t equate to security. SOC 2 or HIPAA-certified clouds can still leak your inference data. Even the most compliance-heavy platforms leave attack surfaces open: logs can be subpoenaed, shared GPUs leak through side channels, and staff may access decrypted payloads.
Our stack is engineered from the silicon upward to eliminate these risks. The result is an inference environment where all data is ephemeral, fully isolated, and accessible only to its rightful owner.
Data remains encrypted while in use inside secure enclaves. Even staff with root or hypervisor access cannot read prompts, weights, or results.
You hold the decryption keys, not us. Inference cannot run without your explicit key release, preventing unauthorized use of your data or models.
Inference requests, responses, and intermediate states are never stored. Once processed, nothing remains. Even a future breach cannot expose past workloads.
Every customer runs on isolated GPU/CPU nodes. Performance is predictable, and no “noisy neighbour” workloads interfere. Each runtime is ephemeral, with all memory wiped on restart. Verifiable infrastructure ensures you can validate where it’s actually running.
All traffic remains inside private links via VPC peering or PrivateLink. Mutual TLS authentication ensures that both endpoints verify each other before communication begins.
Custom AI silicon provides hardware-level isolation and backdoor resistance. From chip to API interface, every layer enforces data confidentiality and integrity.
Fine-grained, container-aware traffic policies are enforced within orchestration layers without relying on perimeter firewalls.
Rapid inference responses are delivered without compromising security guarantees.
Geodd’s security model is built on a full-stack approach from custom silicon through enclave execution to API design, eliminating trust gaps at every stage. To see the details, explore our technical whitepaper, integration docs, and latency benchmarks.
Technology Deep DiveGeodd was created for teams that cannot compromise on confidentiality:
Detect malware and phishing without exposing client datasets.
Run fraud analysis without leaking proprietary heuristics.
Whether its patient data, test results and diagnosing, keep them private and tamperproof.
Process sensitive documents and contracts with zero retention and only you can see your data.
Deploy fraud detection AI without risking customer data exposure.
Run classified or critical infrastructure workloads with hardware-level protection against insiders.
