GPT-Rosalind CERTIFIED

Independent AI research

We study what models can do before capability outruns control.

Boundary Signal evaluates frontier AI systems across capability, alignment, biosecurity, and adversarial robustness—then turns evidence into decisions.

Research surface / 01 Active
Boundary Signal research map Four research domains connected across a shifting evaluation boundary. CAPABILITY CONTROL ALIGNMENT BIOSECURITY RED TEAMING EVALUATIONS
Observed Emerging Controlled
00 / Thesis

The gap we work in

Power is measurable. Safety has to be, too.

Frontier models are becoming capable in domains where failure is consequential and conventional benchmarks are thin. We build evaluations that expose the boundary: what a system can accomplish, where safeguards break, and which interventions hold.

Evidence
Reproducible over rhetorical
Threat model
Realistic over theatrical
Disclosure
Useful without enabling misuse
01 / Research

Four connected programs

Research at the capability–control boundary.

We pair empirical measurement with operational threat modeling so results are useful to model builders, auditors, and public-interest institutions.

01Active

Capability evaluations

Task-grounded tests for autonomy, scientific reasoning, tool use, and long-horizon execution.

  • Agentic behavior
  • Scientific uplift
  • Evaluation integrity
02Active

Alignment science

Behavioral and mechanistic studies of control, oversight, deception, and goal-directed behavior.

  • Control evaluations
  • Scalable oversight
  • Model organisms
03Controlled access

AI & biosecurity

Measurements of biological problem-solving uplift, safeguard reliability, and misuse pathways.

  • Dual-use uplift
  • Safeguard stress tests
  • Risk mitigations
04Active

Adversarial testing

Structured red teaming that maps failure modes without turning findings into a misuse manual.

  • Attack surfaces
  • Jailbreak resilience
  • Defense validation
02 / Method

From concern to evidence

Test the claim.
Map the boundary.
Change the decision.

Every project begins with a decision someone needs to make—not a benchmark looking for a purpose. Our methods are designed around consequence, reproducibility, and clear uncertainty.

  1. 01

    Threat model

    Define the actor, access, objective, constraints, and real-world consequence.

    Frame
  2. 02

    Measurement design

    Build elicitation-aware tasks with controls, baselines, and independent review.

    Measure
  3. 03

    Adversarial validation

    Stress the protocol and the safeguard—not only the model under ideal conditions.

    Challenge
  4. 04

    Decision translation

    Report findings, uncertainty, mitigations, and the evidence that would change the conclusion.

    Act
Read our evaluation method
03 / Briefs

Open work

Research notes and operating standards.

Responsibility

Useful, not enabling

Some findings should travel with friction.

Dual-use research creates an obligation beyond ordinary publication. We separate public evidence from operational detail, coordinate disclosure, and use controlled access when release could materially lower the barrier to harm.

Read our standard
04 / About

Boundary Signal Research

Independent by design.
Collaborative by necessity.

Boundary Signal is an independent AI research company focused on the empirical gap between model capability and reliable control. We work across disciplines because consequential AI risk does not respect disciplinary borders.

We welcome research collaborations, evaluation partnerships, and careful criticism from people working on the same hard problems.

01 / Independence 02 / Scientific rigor 03 / Responsible disclosure