The Technology

Why LOCI Thinks Ahead.

LOCI predicts software behavior from real workloads and platform traces — not source code alone.

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Inputs

Real workloads
Platform traces
Compiled binaries
↓

Execution Model · LCLM

Powered by AI Physics

↓

Outputs

Timing
Power
Memory
Cache
Latency
System effects
↓

Engineering judgment

Source code

what the engineer intended

↓

Unknown runtime behavior

what actually happens on hardware

Why source code isn’t enough

Source code explains intent. Execution reveals reality.

  • Cache misses
  • Memory pressure
  • Power spikes

Source code cannot reveal runtime behavior by itself.

Why LOCI works

Four reasons the predictions hold.

Real execution traces

  • Years of traces from open-source software on real hardware
  • Real workloads — not synthetic benchmarks
  • Billions of execution traces, and growing

Binary-first

  • Reads the compiled binary — ELF, Mach-O, PTX/SASS, Wasm
  • The source language is an input, not a constraint
  • The binary encodes how the code will run

Physics-bounded

  • Every prediction has a measured floor and ceiling
  • Numeric, physical quantities — ns, watts, cycles
  • Cannot hallucinate a value outside observed bounds

Hardware-validated

  • Predictions match measured silicon
  • Verified against Lauterbach (TRACE32) hardware
  • Reproducible — same binary in, same signals out
Execution Intelligence

Frontier LLM vs LOCI.

Frontier LLM

  • Reads source
  • Predicts text
  • General reasoning
  • Internet training

LOCI

  • Reads binaries
  • Predicts execution
  • Real workloads
  • Platform traces

General intelligence writes code. Execution intelligence predicts what it will do.

The signals

What LOCI predicts.

Timing

Per-function response time before it runs.

Latency

p95 / p99 bounds, predicted from the binary.

Power

Per-function energy cost, ahead of time.

Memory

Worst-case stack depth and pressure.

CPU

Throughput and scheduling behavior.

GPU

Occupancy, register spills, kernel cost.

Cache

Modeled miss-rate on the hot blocks.

System effects

Wake cadence and power-state cost.

true vs predicted · held-out real silicon
predicted = measuredtrue mean · measured nspredicted mean
R² = 0.96MAPE ≈ 8%held-out

Predicted vs measured on held-out code · matched to the real eval · R² = 0.96 · MAPE ≈ 8%.

The engine behind LOCI

Execution intelligence, by the numbers.

LCLM — a small code-language model with a ModernBERT backbone and FlashAttention kernels, domain-trained on real execution traces. Powered by AI Physics.

0 yrs

Of real-workload traces

Billions

Of execution traces

R² 0.00

On code it has never seen

Real silicon

Verified on hardware

0+

Granted patents · US · EU · JP

ISO 27001

Certified · SOC 2 in progress

ARM architecture coverage

ARMv4TARMv5ARMv6ARMv6-MARMv7-MARMv7E-MARMv8-MARMv7-AARMv8-AARMv9ARMv9.2ARMv7-RARMv8-RNeoverse

Cortex-A · Cortex-M · Cortex-R · classic ARM7 / ARM9 / ARM11 — validated on real silicon. + Infineon TriCore · more ISAs expanding.

Where LOCI fits

The execution-intelligence layer in your existing loop.

Engineer

asks for a change

↓

Claude

writes the code

↓

LOCI

predicts execution

↓

CI

guards every PR

↓

Merge

within contract

↓

Production

no surprises

LOCI augments the workflow you already have — it doesn’t replace it.

Binary
↓
LOCI
↓
Verdict
Zero runtime overhead

Runs from the binary. Nothing to deploy.

  • No runtime
  • No instrumentation
  • No simulator
  • No profiler
  • Works offline

Built on real software.

0 yrs

Of real workloads

0+

Granted patents

On silicon

Validated on hardware

Mission-critical

Safety & industrial

Trained on real workloads and platform traces · validated on real silicon

Know how your software behaves before it runs.

LOCI is the execution-intelligence layer for AI coding agents.

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