AI Inference Efficiency Layer
Lower AI inference cost
without affecting model accuracy
ISIRO Runtime™ reduces memory traffic, lowering inference cost while preserving model accuracy.
- No quantization
- No precision change
Representative results
30%
Lower memory traffic on BF16 LLM workloads
Exact
Weights preserved bit for bit (no quantization)
Up to 2×
Lower latency vs cuBLAS baseline (evaluated workloads)
The problem
AI inference cost is a memory-traffic problem.
Inference workloads are often limited by the cost of moving model data through memory. Quantization reduces that cost, but it changes numerical representation and output behavior, which affects model accuracy. ISIRO takes a different path: reducing memory traffic without quantization or approximation while preserving model accuracy.
How it works
Two steps. No rip-and-replace.
Compile once
One-time compile into compact .tic file with smaller footprint. Bit-exact weights.
Deploy
ISIRO Runtime integrates the same inference frameworks you already use as targets.
Product
ISIRO Runtime™
An AI inference efficiency layer for your existing inference stack.
Efficiency
Memory traffic reduction with model accuracy preserved. No retraining. No quantization.
Security through TIC Shield™
Protects .tic files at rest and in transit with support for confidential computing where available.
Ready to evaluate ISIRO Runtime?
Evaluate in your environment without sharing your model. Compare model accuracy, memory traffic, and cost against your baseline.
Prefer email? hello@isiro.ai