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 & investors
Execution cost vs budget. ROI from the first session.
Every LOCI catch is a decision made from data instead of engineering judgement: no setting up timing measurements, adding logs, attaching a debugger or reproducing on a bench to find out. The cockpit counts that avoided work as engineer hours.
10.0 h
this case · 0 pushbacks × 5.5 h + 8 checks × 1.25 h
roscon-loci-demo · 8 runs
5.0 h
per working day, per engineer — measured rate
10.0 h over 2 active days
Your team
50 h
per sprint
$5,000
325 h
per quarter
$32,500
$32,500
engineering time back / quarter
325 h × $100/h
Supervision tax = pushbacks × 5.5 h + checks × 1.25 h (LOCI cockpit weights). A projection: assumes the team keeps LOCI’s catch rate from this project (8 catches in 2 days, 2026-11-09 – 2026-11-10).
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
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