LOCI Catcheswhat coding agentsmiss.
“” · AI coding agent
Coding agents write code. LOCI thinks ahead.
Learned from real workloads and platform traces — not source code alone.
Less babysitting • Fewer regressions • Higher first-pass accuracy
Powered by AI PhysicsiAI Physics — deterministic models trained on real-silicon execution traces. They predict how your compiled code actually runs — timing, energy, memory — from the binary, not the source, and generalize to code they’ve never seen (R² = 0.96 on held-out). — trained on real workloads and platform traces
Trusted by partners, customers & investors
See LOCI think ahead.
Coding agents write code.
LOCI predicts what happens next.
What will happen when this code runs?
Catch regressions before testing and production.
Help the agent choose a better implementation before merge.
No runtime. No instrumentation. From Plan to Merge — works beyond code, models your execution files.
AI has solved software generation. LOCI solves software understanding.
The bottleneck is no longer writing software. It’s knowing what that software will do when it runs.
LOCI is the execution-intelligence layer between AI code generation and production.
Without LOCI vs With LOCI.
Without LOCI
- AI writes code.
- Developers test it.
- Problems are found later.
- Teams babysit coding agents.
With LOCI
- AI writes code.
- LOCI predicts the outcome immediately.
- The coding agent fixes itself.
- Teams review less, ship with more confidence.
LOCI turns coding agents from
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 unseen code at 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 unseen code at 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 held-out code · matched to the real eval · R² = 0.96 · MAPE ≈ 8%.
Could you ask a frontier LLM instead?
You could. It would cost up to ~220× more per query and predict from patterns, not execution. Behavioral prediction needs real execution traces, not source code alone.You could — at up to ~220× the cost, predicting from patterns, not execution.
- Trained on
- Source code
- Predicts from
- Patterns
- Accuracy
- Prediction drift
- Cost per query
- up to ~220× more
- Trained on
- Real workloads & platform traces
- Predicts from
- Execution behavior
- Accuracy
- Trace-validated
- Cost per query
- Small specialist · efficient
Small specialist + real execution > frontier LLM + source code.
See LOCI across different engineering domains.
Same execution-aware guardian. Same interaction. Pick a domain.
Your Graviton services, measured on real silicon.
Natively-compiled services on AWS Graviton, measured in the units your cloud team lives in — p99, $/request, cost & carbon.
- NativeAOT .NET, Go, Rust, C/C++ — measured per function
- Caught pre-merge by the same guardian
- No instrumentation — runs from the binary
Illustrative · grounded in documented patterns — gRPC #6619 · OpenSSL #22189
LOCI in the loop, not in the way.
An independent validation layer at every stage of the Claude Code agentic loop — plan, write, PR, and merge. It surfaces the catch; it never blocks the flow.
Agent-agnostic · Claude Code · Cursor · Copilot
Works with the tools your team already uses
- Platformself-hosted · SaaS
- GitGitHub · GitLab · Bitbucket
- AzureDevOps · pipelines
- AWSMarketplace listing
- Claude CodeMCP plugin
- CopilotCLI hook · skills
- GCC+ Clang · LLVM · MSVC
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