Execution Guardian for Agentic Workflows
AI writes the code.LOCI knows how it will run.
LOCI is a vertical agent that predicts execution worst-cases from the binary - power, latency, throughput, memory vs. budget - at plan, PR, and merge. Before code ships.
Trained on 5 years of real CPU and GPU workloads, no runtime, no instrumentation.
AI TRiSM | Guardian Agent | Multiagent Systems | Platform Engineering
89% of teams already hit this wall. Here's why — and what changes.
How It Works
43% of AI-generated code changes need debugging in production, even after passing tests. Source
That's the workflow. Here's what it looks like inside the binary.
Four views into your binary.
No runtime, no instrumentation, execution-aware modeling.
LOCI caught a 5,000 ns loop from the binary, before code was written. But don't AI coding tools already analyze code?
AI agents write the code.LOCI checks how it runs.
The agents in your workflow reason from source code. They don’t know how the compiler transforms it. LOCI reads what the compiler actually produced, the binary, and predicts execution behavior. Different input. Different output. They work best together.
AI coding tools
Generates code from prompts
Input: source code + context
Output: code suggestions
Trained on text corpora
Works during coding
Helps write faster
Probabilistic - varies per run
LOCI
Predicts behavior from binaries
Input: compiled ELF / binary
Output: latency, power, throughput, stack
Trained on real CPU / GPU workloads
Works before and after coding
Helps decide what ships
Deterministic - same binary, same signals
LOCI reads a compiled binary and predicts execution behavior. How?
A small, specialized model trained on what general LLMs never see.
LCLM is a small, specialized code language model, not a general LLM. It’s trained on 3 billion+ assembly blocks and real-time execution traces from open-source projects running on real hardware, IoT, networking, industrial, and safety-critical systems. Purpose-built for binary files. ~220× cheaper per query than general LLM tokens. Aurora Labs internal benchmark
The result: given a compiled binary, LCLM predicts latency, throughput, power consumption, and stack depth per function. These are measurable values you can verify against actual hardware — not confidence scores or probabilistic estimates.
The model exists. The predictions work. Now — where does it plug in?
LOCI plugs into your agentic workflow.At any stage. No new build steps.
Your agents already plan, code, and open PRs. LOCI adds an execution signal layer alongside your existing pipeline, no instrumentation, no profilers, no runtime.
LOCI SIGNAL LAYER
Plug in at
one stage
or
the full pipeline
Code
incremental .so
fn-level signal as you type
Build
full binary pass
all 5 signals, whole program
Test
tail & edge cases
paths your suite never reaches
Merge
PR verdict
blocks if signal exceeds baseline
Each stage is independently useful — or run the full layer for continuous coverage.
No instrumentation required.
No runtime overhead added.
No profilers to set up.
No new build steps.
No changes to your CI.
No code changes needed.
LOCI plugs into your pipeline in minutes. But who owns it internally?
Who owns execution signals in your org?
LOCI maps to existing Gartner budget lines, no new category to justify: AI TRiSM, Guardian Agent, Multiagent Systems, Platform Engineering.
SaaS works for most teams. But what if your data can't leave your network?
Need execution signals in a regulated environment?
Same guardian agent, deployed where your data stays. Private cloud, on-prem, or hybrid. SSO, RBAC, audit trails, and patent indemnification.
Built from safety-critical DNA
Aurora Labs earned these certifications from 8 years of shipping into automotive and industrial systems. LOCI inherits that rigor, execution signals grounded in the standards your compliance team already trusts.
INVESTORS & STRATEGIC PARTNERS
ECOSYSTEM
You've seen the problem, the solution, the engine, and the team. One question remains.
75% of AI coding agents introduce regressions during long-term maintenance. Source
Your agentic workflow is already shipping code. The regressions aren’t going to stop on their own. LOCI adds the execution signals that turn production fire drills into PR comments.