AI Inference Cost Optimization Demo at Austin AWS User Meetup

At the Austin AWS User Meetup, ISIRO presented a technical talk and live demo titled Cost Optimization for AI Inference on AWS with ISIRO Runtime. The session focused on why inference cost is tied to memory movement, how GPU memory traffic affects throughput and latency, and how ISIRO Runtime improves efficiency while preserving exact model behavior.

During the live demo, ISIRO Runtime demonstrated ~30% reduction in model footprint with associated reduction in memory traffic on a demonstrated LLM workload. Output stayed bit-exact, with no quantization and no approximation. Many efficiency approaches trade accuracy for speed; ISIRO Runtime is built for teams that need both.

The talk also covered model security with TIC Shield™: KMS-backed protection for artifacts at rest and in transit, TIC Lock for software-based in-use protection, and support for hardware-backed confidential computing where available.

Benchmark results showed up to 2× lower latency than cuBLAS baseline in the evaluated workload.

ISIRO is onboarding teams for AWS GPU inference pilots on Amazon EC2 GPU instances, Amazon SageMaker, and related stacks. Pilots compare ISIRO Runtime against your baseline.

Thank you to the Austin AWS User Group for the opportunity, and to everyone who attended and engaged with the demo.