Catch Performance Issues Before Deployment with LOCI AI Agent

Building performance-critical software? Static analysis and observability tools miss subtle hardware bottlenecks that impact production.

LOCI AI Agent changes the game.

Powered by Aurora Labs’ Large Code Language Model, LOCI AI Agent is the industry’s first hardware-aware detection agent for accelerating software validation and optimization. LOCI delivers real-time insights directly from your executables, detecting timing delays, power spikes, and throughput drops as you code.

Why Teams Choose LOCI

Predict. Decide. Deliver.

Download the LOCI AI Agent Solution brief to learn how LOCI exposes issues before they hit production.

Download LOCI AI Agent Solution Brief

LOCI AI Agent for Accelerating Software Validation & Optimization

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How LOCI Helps

By predicting hot spots before test or inference and optimizing at the opcode/basic-block level, LOCI reduces excess server provisioning, smooths power spikes, and delivers more throughput per watt.

Predictive Analysis

Forecast performance issues before they impact production systems

Opcode-Level Optimization

Deep hardware understanding enables precise efficiency improvements

Power Efficiency

Maximize throughput per watt while reducing infrastructure costs

LOCI Core Capabilities

Pre-test insight

Predict hotspots, thermal spikes, and bottlenecks before execution.

CI/CD integration

Optimize batching, tune serving layers, and simulate workloads.

Runtime resilience (RAS)

Dynamic power recommendations and reliability trade-offs.

Hardware-dialect aware LCLM

Understands CPUs & GPUs at the opcode level.

Evidence-based

Every change is re-measured, validated, and tracked.

Our Partners

Use Cases

Timing & response time

Reduce P95/P99 spikes before deployment.

Bottleneck analysis

Identify hot paths and stalls across serving layers and kernels.

Worst-case execution path

Flag tail-heavy basic blocks pre-release; visualize basic block energy spikes.

Power spikes

Forecast & smooth GPU/CPU power under load; manage thermals.

Power-per-basic-block optimization

Instruction-level efficiency guided by LCLM.

LLM serving

Token budgeting, KV cache, smart batching; tokens throughput metric.

Vision / Edge

Kernel fusion, memory layout; thermal guard-banding.

Training

Step-time variance, data loader stalls, gradient hotspots.

About Aurora Labs

Aurora Labs is a domain expert in ML, NLP, and model tuning, pioneering data-driven innovation since 2017, developing a proprietary vertical large language model (LLM) known as Large Code Language Model (LCLM). This LCLM specializes in comprehensive system workload analysis focusing on power and performance for observability and reliability, accelerating the development of embedded systems, AI, and Data Center infrastructures.

Founded in 2016, Aurora Labs has raised $97m and has been granted 100+ patents. Aurora Labs is headquartered in Tel Aviv, Israel, with offices in the US, Germany, North Macedonia, and Japan.