Higher first-pass quality,optimized codebefore it runs.

Deadlines, power, memory, paths — the loop tells you too late.

LOCI predicts at /plan, as you code, and in CI/CD.

Fix it before the cycle is spent.

Powered by AI PhysicsAI Physics — deterministic models, bounded by the physics of the CPU/GPU.

Trusted by partners, customers and investors

Microsoft
Arm
Infineon
STMicroelectronics
NVIDIA Inception Program
Deutsche Telekom · T-Systems
NTT Data
Porsche SE
Toyota Tsusho
Maniv Mobility
FM Capital
UL
Microsoft
Arm
Infineon
STMicroelectronics
NVIDIA Inception Program
Deutsche Telekom · T-Systems
NTT Data
Porsche SE
Toyota Tsusho
Maniv Mobility
FM Capital
UL

How it works

Execution cost vs budget. ROI from the first session.

Engineering time back

LOCI cockpit

5.0 h per engineer per working day, measured on a real project (10.0 h over 2 days).

50 h

per sprint

325 h

per quarter

$32,500

back per quarter

Projection. LOCI cockpit weights: pushback 5.5 h, check 1.25 h.

loci-cockpit · BLE_TI live
LOCI6 catches · 27 checks · 69 fns

CONTRACT ENVELOPE · cost vs budget

Deadline · llProcessCentral✗ 107%
Power · llProcessCentral⚠ 93%
Stack · app task⚠ 96%

│ budget · bars past it are over

PREVENTED6 caught pre-merge · 77% first-pass clean
BABYSITTING≈8 hrs saved · 21/27 auto-verified
⚠ powerNotifyCb +164.7% (266 → 704 ns) — caught pre-merge

One engine, every domain

See LOCI across different engineering domains.

Same execution-aware guardian. Same interaction. Pick a domain.

In CI

10,294 functions checked. One comment on the PR.

The LOCI GitHub Action on a real upstream SPDK change: base against change, every function priced, the nine that moved explained — posted on the pull request before anyone reviews it.

GitHub Actions · auroralabs-loci/spdk PR #12 · job 2m 47s · 22 modified · 1 new · 1 removed

The engine

AI Physics, a small, fast foundation model for software execution on real silicon.

A small, fast model trained on real-silicon traces. Generalizes to new, unseen binaries at up to R² = 0.96 — catching what source-only LLMs miss.

  • Deterministic

  • Bounded by physicsiEvery prediction is a measurable physical quantity — cycles, ns, energy — checkable by running the binary on real hardware. It can't drift into invented numbers the way free-form text can.

  • Verifiable on hardware

  • Human-on-the-loop

patents
0+
patents
real-platform training
0 yrs
real-platform training
verified on real hardware
Silicon
verified on real hardware

Not a GPT wrapper — trained on execution, not text.

Read more: AI Physics for Physical AI

True vs predicted

Held-out · real silicon

Predicted = measuredTrue mean · measured nsPredicted mean

Up to R² = 0.96

Fit on unseen binaries

MAPE ≈ 8%

Held-out

Predicted vs measured on new, unseen binaries · matched to the real eval · up to R² = 0.96 · MAPE ≈ 8%.

Works with the tools your team already uses

  • Platformself-hosted · SaaS
  • GitGitHub · GitLab · Bitbucket
  • AzureDevOps · pipelines
  • AWSMarketplace listing
  • Claude CodeMCP plugin
  • GCC+ Clang · LLVM · MSVC
  • LanguagesC · C++ · Rust · Go · Cython

Safety-critical DNA

Built to the standards your compliance team already trusts.

8 years shipping into automotive and industrial systems. LOCI inherits the rigor.

ASPICE Level 2

Automotive software process maturity

ISO 26262 / ASIL-B

Functional safety for automotive

ISO 21434

Cybersecurity engineering for road vehicles

Autonomous Vehicles

Production AV programs · ISO 21448 / SOTIF aligned

ISO 27001

Information security management

120+ Patents

Binary analysis & execution modeling

Guard every coding agent decision with execution evidence.

Your coding agents are already shipping decisions. LOCI gives every one — plan, PR, merge — runtime-grade evidence the coding agent and reviewer can act on.

75% of AI coding agents introduce quality regressions during long-term maintenance. Source