LOCI Catcheswhat you, and coding agentsmight miss.
Pre-run execution prediction for compiled software.
Plan, code, test, fix, repeat — every loop costs a cycle.
LOCI predicts inside the loop, so you fix before it costs you.
Powered by AI PhysicsiAI Physics — deterministic models trained on real-world workloads and platforms. They predict how your compiled code actually runs — timing, energy, memory, software behavior — from the binary, not the source, and generalize to binaries they have never seen — up to R² = 0.96 on unseen code. Built for robotics software — humanoids, drones, industrial robots, ADAS — on the silicon robots ship on: NVIDIA Jetson and Orin, STMicroelectronics and NXP microcontrollers. · Built for Robotics
Trusted by partners, customers & investors
Fewer loops. Higher first-pass quality.
Deadlines, power, memory, paths — the loop tells you a cycle too late.
LOCI predicts at /plan, at code write, in CI/CD. Fix before the cycle is spent.
- Fewer iterations
- 6 caught pre-merge — found before the loop spent a cycle
- Less agent back-and-forth
- 21 of 27 auto-verified — the agent stopped asking you to check
- Higher first-pass quality
- 77% first-pass clean — landed right the first time
Testing still has the final word. It just stops being where you find out.
CONTRACT ENVELOPE · cost vs budget
│ budget · bars past it are over
See LOCI across different engineering domains.
Same execution-aware guardian. Same interaction. Pick a domain.
Control loops that hold their deadline on the target.
Humanoids, drones, industrial robots, ADAS. LOCI models the compiled binary for the silicon it ships on and predicts whether each change stays inside its timing, power, memory and behavioral budget.
- Control-loop worst case against its deadline
- Power and memory inside their envelopes
- No instrumentation — runs from the binary
Every change gets a pre-merge verdict against its envelope.
Same gate. Five different ways to be wrong.
Each domain leans on a different gate, and every gate here is green. None of these is visible in the source.
Automotive · ECU
agent: “simplify the CAN frame parser”
unit tests ✓ · review ✓ · HIL slot next week
handler worst case runs past the frame window
WCET exceeds the arrival period — frames dropped under burst, not under test
Security · crypto
agent: “tighter constant-time compare on the auth path”
sast ✓ · sca ✓ · crypto review ✓
constant-time property lost
timing variance correlates with secret-bit count · CWE-208 pattern
Cloud · service
agent: “cleaner buffer handling in the encrypt path”
load test green at tested concurrency
allocation introduced on the hot path
per-request alloc/free moves p99 well past its budget under load
Robotics · control
agent: “offload the filter to the accelerator”
simulation ✓ · review ✓
CPU waits on the handoff, buffers held across the wait
control-loop jitter widens and in-flight work is unbounded
Battery · IoT
agent: “poll the sensor more often for accuracy”
review ✓ · power last measured a release ago
energy per cycle rises against a fixed budget
duty cycle breaches the power envelope before it breaches timing
Each is a mechanism LOCI models — worst-case timing, variance, allocation on a hot path, energy per cycle — reported as a verdict against a declared budget.
AI Physics, a small, fast foundation model for software execution on real silicon.
AI Physics is a software execution model learned from real workloads and platform traces — not source. LOCI’s model, LCLM, realizes it, generalizing to new, unseen binaries at up to R² = 0.96 — it predicts what code will do, not just what it says.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
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
- TargetsJetson · Orin · aarch64 · Cortex-M · TriCore
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.
of AI coding agents introduce quality regressions during long-term maintenance.Source