Product

From hidden signals to deployable lenses.

NeuronLens turns internal model signals into four product layers: runtime control, discovery, domain intelligence, and targeted repair.

  • Runtime Lens controls what happens live.
  • Concept Studio discovers what is inside.
  • Domain Lenses apply internal signals to high-stakes domains.
  • Model Design Studio repairs what repeatedly fails.

01 — Runtime Lens

Runtime Lens: beyond logs, inside the model

  • Reads activation signals inside the model, not just outputs
  • Finds root causes of failures, not just symptoms
  • Acts before the action fires: allow, block, or reroute
Prompt / context
hidden signal forms
Runtime Lens evaluates
review / block / reroute
evidence stored

Runtime Lens · Agent Lens

Agent Lens: internal oversight for tool-using AI

Connect in 2 lines · works with LangChain, CrewAI, Claude Agents, AutoGen, OpenAI Agents, and more

Finds model-internal signals that drive agent behavior

Catches risky tool calls before execution

Detects tool-call hijacking, goal drift, and privilege escalation

Tool omissionWrong tool choiceLoop riskAction mismatchGoal driftPrivilege escalation

Runtime Lens · Safety Lens

Safety Lens: internal signals for grounding and policy risk

Detects grounding and policy risk while responses form

Catches prompt injection, RAG poisoning, unsafe output, and red-team patterns

Supports block, review, reroute, or steer, with evidence before delivery

Unsafe generationGrounding riskSensitive leakagePrompt injectionRAG poisoningHigh-impact decisions

02 — Concept Studio

Discover what the model has learned.

Concept Studio is the discovery layer of NeuronLens. It helps teams search, inspect, and test internal concepts before turning them into runtime controls, repairs, or domain lenses.

Concept Search

Find internal concepts linked to behaviors, risks, domains, or failure modes.

Activation Checks

Create conditional checks when specific internal signals activate.

Search-and-Steer

Experiment with how internal concepts influence model behavior.

Lens Export

Turn useful concepts into Runtime Lens controls, Model Design Studio repairs, or Domain Lenses.

concept_studio

Search

“grounding risk”

Results

unsupported claim
citation missing
speculative answer
weak retrieval support
Inspect examplesCreate checkExport lens

03 — Domain Lenses

Apply internal signals to high-stakes domains.

Domain Lenses package validated internal signals into specialized products for workflows where hidden failure modes, domain concepts, and decision evidence matter.

Trading / Risk Lens

Track internal concepts behind market stress, guidance uncertainty, liquidity risk, event behavior, and model drift.

Credit Lens

Surface borrower-risk concepts, evidence gaps, and rationale mismatch in credit workflows.

Cyber Lens

Detect high-risk action intent, missing evidence, and escalation patterns in security workflows.

Science / Healthcare Lens

Track uncertainty, grounding gaps, and domain-specific failure signals in scientific or clinical workflows.

Domain Lenses are not separate tools. They are specialized products built from the same internal signal engine.

04 — Model Design Studio

Repair failures from inside.

When the same failure keeps appearing, Model Design Studio helps diagnose the internal features behind it and guide targeted repair — without blunt retraining.

01

Failure Slice

Group recurring errors into a focused repair set.

02

Feature Diagnosis

Identify internal features associated with the failure.

03

Targeted Repair

Guide adaptation toward the failure-driving signals.

04

Before / After Evidence

Measure whether the repair fixed failures while preserving what already worked.

Fix the failure mode, not the whole model.

One loop. Four product layers.

1

Control

Runtime Lens

2

Discover

Concept Studio

3

Apply

Domain Lenses

4

Repair

Model Design Studio

The same research engine powers all four: activation analysis, sparse features, probes, and causal validation.

Start with one workflow. Build reusable lenses.

NeuronLens is looking for design partners deploying high-stakes AI systems where surface monitoring is not enough.