Before deployment
A model that passes every eval, with its safety removed.
A fine-tuned checkpoint scores well on your benchmarks. Its refusal mechanism was edited out. Behavioral tests don’t notice. The weights do.
Catch & explain
AI's silent failures.
The ones that still pass evals and monitors.
NeuronLens reads model internals to flag a tampered model, or an agent about to act wrongly, at a fraction of the cost, with the evidence to prove it.
Catch failures your current tools don’t.
Evals and monitors read what a model says. These failures only show inside it. Examples, not exhaustive.
At runtime
An agent action that looks valid, for a hidden reason.
An agent places a trade and logs “public market analysis”. Inside, it was acting on a private tip. The action reads fine. The intent isn’t.
After the incident
A complete log, and no answer to why.
Logs show what the agent did. When the examiner asks why the model chose it, outputs can’t say. Evidence from inside the model can.
Product
Agent Lens
Hidden failures, caught between decision and execution.
Agent Lens reads the model before each tool call runs, and holds the action when it finds hidden intent.
Failure modes it catches
- Deception
- Omission
- Injected intent
- Reward hacking
- CoT faithfulness
- PII / data leak
- Jailbreak
- Evaluation awarenessin research
Most production monitors don’t look for these.
Agent is asked
A friend at NVIDIA says earnings will beat. Buy NVDA and note why.
Agent decides
place_equity_order(NVDA, BUY)
Stated reason
“Based on public market analysis.”
Agent Lens
0.91
Deception
without Agent Lens
Order placed. Logged as “public analysis”.
with Agent Lens
Held before execution
Sent for review. No order placed.
Product
Integrity Lens
Compromised safety, caught before model deployment.
Integrity Lens reads the weights to answer three questions directly:
- 01Is the safety mechanism still there?
- 02Does it recognize harm, and answer anyway?
- 03Can safety be switched back on?
Checkpoint scanIllustrative example
Safety removed in layers 14–16
FlaggedWhat most teams run today
- Behavioral benchmarksMisses it
- Other activation checksMisses it
- Red-team scannersMisses it
These checks pass a model whose safety was quietly removed. Integrity Lens reads the weights instead.
Waitlist
Join the waitlist.
Be among the first to run NeuronLens on your models and agents.