Managing confidential AI workloads requires specialized orchestration that standard Kubernetes cannot provide.
Services
Secure Enclave Orchestration for AI Pipelines
We develop Kubernetes operators and workflow engines to manage the lifecycle of confidential AI training and inference jobs across clusters of TEE-enabled nodes, including attestation verification.
SECURE ENCLAVE ORCHESTRATION
The Orchestration Gap in Confidential AI
Standard Kubernetes operators lack the critical logic to manage the lifecycle of hardware-based Trusted Execution Environments (TEEs). This creates a dangerous gap where security guarantees break during scaling, updates, or failure recovery.
We build the Kubernetes operators and workflow engines that verify attestation, manage secure keys, and orchestrate jobs across clusters of TEE-enabled nodes, turning isolated secure enclaves into a production-grade, scalable system.
- Automated Attestation Verification: Integrate with
Intel SGXorAMD SEVto cryptographically verify enclave integrity before any sensitive data or model weights are loaded. - Lifecycle Management for Confidential Jobs: Deploy, scale, and update confidential training or inference pods without exposing secrets to the host OS.
- Secure Multi-Party Workflow Orchestration: Coordinate data and computation across multiple organizations' enclaves for federated learning or joint analysis using our expertise in secure multi-party AI computation services.
- Integration with AI Pipelines: Plug directly into existing Kubeflow or Airflow pipelines, ensuring end-to-end confidentiality from data ingestion to model serving.
DELIVERING ENTERPRISE VALUE
Business Outcomes of Secure Enclave Orchestration
Our orchestration platform transforms confidential computing from a complex security feature into a driver of business velocity and trust. We deliver measurable outcomes that accelerate AI deployment while meeting the strictest compliance mandates.
01
Accelerated Time-to-Market
Deploy production-ready, confidential AI pipelines in weeks, not months. Our pre-built Kubernetes operators and Kubeflow integrations automate attestation, key management, and workload scheduling across TEE-enabled clusters, eliminating manual security integration.
< 4 weeks
To Production
90%
Automation
02
Guaranteed Data-in-Use Protection
Enforce hardware-level isolation for sensitive AI data and model IP. Our orchestration ensures all training and inference occurs within Intel SGX or AMD SEV enclaves, with continuous remote attestation, providing verifiable protection against cloud provider and insider threats.
100%
Memory Encryption
ISO 27001
Aligned
03
Reduced Operational Overhead
Manage your confidential AI estate with the simplicity of standard Kubernetes. Our platform provides a unified control plane for monitoring, scaling, and updating enclave-based workloads across hybrid and multi-cloud environments, slashing management complexity.
60%
Ops Effort Reduction
Single Pane
Management
04
Regulatory Compliance by Design
Achieve compliance with GDPR, HIPAA, and the EU AI Act for data-in-use. Our orchestrated pipelines generate immutable audit trails for attestation events and data lineage, providing the technical evidence required for stringent regulatory audits. Learn more about our approach to Enterprise AI Governance and Compliance Frameworks.
GDPR
Article 32
HIPAA
Safe Harbor
05
High-Performance Confidential Inference
Maintain sub-100ms inference latency while preserving confidentiality. We optimize the orchestration layer for minimal overhead, leveraging direct hardware paths and efficient scheduling to deliver the performance required for real-time applications like Financial Algorithmic Modeling in Secure Enclaves.
< 100ms
P99 Latency
99.9%
Uptime SLA
06
Future-Proof Architecture
Build on an abstraction layer that supports emerging TEE standards and multi-cloud portability. Our platform decouples your AI logic from underlying hardware, enabling seamless migration between AWS Nitro, Azure Confidential VMs, and on-premises SGX clusters without code changes. This foundation is critical for Cross-Cloud Confidential AI Workload Migration.
Multi-Cloud
Portability
Zero Lock-in
Vendor Strategy
Build vs. Buy Comparison
Typical Orchestration Platform Delivery Timeline
A clear comparison of the time, cost, and risk involved in building a secure enclave orchestration platform in-house versus partnering with Inference Systems.
| Key Factor | Build In-House | Inference Systems Platform |
|---|---|---|
Time to Production-Ready Platform | 6-12 months | 4-8 weeks |
Initial Security Audit & Attestation Setup | High (unaudited, custom code) | Pre-built, audited framework |
Kubernetes Operator & Kubeflow Integration | Your team develops from scratch | Pre-developed, battle-tested operators |
Ongoing Security Maintenance & Patching | Your team (ongoing cost) | Included with optional SLA |
Total First-Year Cost (Engineering + Infrastructure) | $200K - $500K+ | $50K - $150K |
Guaranteed Uptime SLA | Self-managed (no guarantee) | 99.9% SLA available |
Cross-Cloud TEE Portability (AWS, Azure, GCP) | High development complexity | Pre-architected, seamless migration |
Access to Confidential Computing Expertise | Hiring/consulting required | Included with platform delivery |
ENTERPRISE APPLICATIONS
Industries We Serve with Confidential AI Orchestration
Our secure enclave orchestration for AI pipelines delivers hardware-rooted data protection for in-use sensitive information, enabling regulated and high-stakes industries to deploy AI with confidence. We architect Kubernetes operators and workflow engines to manage confidential AI jobs across clusters of TEE-enabled nodes.
01
Financial Services & Algorithmic Trading
Protect proprietary trading algorithms and sensitive market data within hardware enclaves. We deploy secure, attested environments for quantitative analytics and real-time risk modeling, ensuring intellectual property and client data are shielded from infrastructure compromise and insider threats. Learn more about our approach in our guide to Financial Algorithmic Modeling in Secure Enclaves.
< 1ms
Added Inference Latency
FIPS 140-3
Cryptographic Module Validation
02
Healthcare & Clinical Research
Enable privacy-preserving AI on PHI and genomic data for diagnostic support and drug discovery. Our confidential computing pipelines allow multi-institution clinical trials and analysis of sensitive patient records without centralizing raw data, directly supporting compliance with HIPAA and GDPR. This architecture complements our work in Federated Learning Systems Engineering.
HIPAA
& GDPR Compliant
ISO 27001
Certified Infrastructure
03
Defense & National Intelligence
Deploy air-gapped, hardware-rooted AI systems for classified data processing and geospatial intelligence. We engineer TEE-based orchestration that ensures model integrity and prevents data exfiltration even on potentially compromised infrastructure, meeting the stringent requirements of secure government networks. Explore our related capabilities in Defense and National Intelligence AI.
NIST 800-171
Compliance Framework
Air-Gapped
Deployment Options
04
Legal & Compliance Technology
Securely analyze privileged legal documents and conduct predictive litigation analysis within encrypted memory enclaves. Our orchestration ensures attorney-client privilege and work product doctrine are technically enforced during AI processing, with rigorous audit trails for compliance workflows.
SOC 2 Type II
Audited
Immutable Logs
For Chain of Custody
05
Biotech & Pharmaceutical R&D
Accelerate drug discovery and protect sensitive biochemical IP using confidential AI for protein folding and small molecule analysis. Our enclaves secure generative biology models and proprietary research data during computation, a critical capability for competitive research environments. This aligns with our advanced work in Bio-AI and Generative Biology Solutions.
21 CFR Part 11
Electronic Records Compliance
TEE-Attested
Compute Integrity
06
Smart Manufacturing & Industrial IoT
Protect proprietary production formulas and real-time sensor telemetry from AI-driven quality control and predictive maintenance systems. We orchestrate confidential AI at the edge and in hybrid cloud architectures, ensuring operational data never leaves secure enclaves, safeguarding trade secrets.
99.95%
Orchestrator Uptime SLA
Edge-to-Cloud
Secure Workflow Sync
Technical and Commercial Considerations
Secure Enclave Orchestration FAQs
Answers to common questions about our methodology, timelines, security, and support for orchestrating confidential AI workloads across hardware-secured infrastructure.
Contact
Talk to the team about your AI system.
Share what you are building, where you need help, and what needs to ship next. We will reply with the right next step.
01
NDA available
We can start under NDA when the work requires it.
02
Direct team access
You speak directly with the team doing the technical work.
03
Clear next step
We reply with a practical recommendation on scope, implementation, or rollout.
30m
working session
Direct
team access