Local AI Inference. Zero Cloud Cost. Total Privacy.
Aura SDK is the high-performance local inference engine engineered for Windows-ARM64 systems, unlocking the power of Qualcomm Snapdragon X Series co-processors for secure, offline-first applications.
10x Cost Reduction
Eliminate recurring cloud GPU server bills and pay-per-token API fees. Run your AI workloads directly on client laptops at zero marginal cost.
Absolute Compliance
Ensure 100% data residency and GDPR compliance. Sensitive customer prompts and document enclaves are processed strictly local, isolated from third-party networks.
Instant Responses
Ditch web network latency. Direct hardware co-processor scheduling delivers microsecond token generation, bypassing internet dropouts entirely.
Aura SDK vs. Cloud-Based AI APIs
| Metric | Aura Local Engine | Conventional Cloud APIs |
|---|---|---|
| Data Security | 100% Local Enclave | Shared Public/Private Servers |
| Monthly Pricing | Fixed Licensing / Zero token cost | Variable Pay-per-Token API Fees |
| Internet Requirement | None (Works fully offline) | Required (Subject to network drops) |
| Inference Scheduling | Microsecond native co-processor paths | Variable network roundtrip delays |
| Device Integration | Native Windows driver access | Web-sockets and HTTP integrations |
Enterprise Capabilities
Aura SDK provides a robust interface to deploy production-ready local AI models within existing business applications.
- Hybrid Engine Architecture: Automatically routes heavy compute tasks to the Hexagon NPU and uses the ARM64 Oryon CPU cores as a seamless fallback.
- Advanced Weight Compression: Employs proprietary 4-bit weight compression templates, minimizing device RAM footprints while retaining high output quality.
- Hardware-Level Security: Maps model contexts into page-locked local memory segments to guarantee process isolation and prevent memory leakage.
Empower Your Apps with Local Intelligence
Aura SDK is fully open-source and free to deploy under the MIT license. Explore the source code, review integration workflows, or contribute to the co-processor runtime on GitHub.