Proof, NotPass / Fail
Most agent evals hand you a score. Krv hands you proof — turning an agent's data, reasoning, and code into an evidence package that justifies every decision and flags where it's uncertain. Everything you need to deploy safe, compliant agents.
Verification Across
Three Dimensions
An agent's final answer can look right for the wrong reasons. Krv assembles an evidence package from three angles: the data it relies on, the reasoning inside the model, and the code it generates. Every decision comes backed by proof, not a single pass/fail score.
Data
Every agent decision is downstream of its data. Pulsar maps the multiscale structure of your dataset, validating new instances against known regions to expose thin coverage and failure clusters.
Models
Passing lab tests doesn't guarantee real-world safety. Pasteur stress-tests models under extreme conditions, probing their internal reasoning to surface hidden failure modes. The result shows exactly when an agent can be trusted, and when it can't.
Code
Agents write code faster than humans can review it. Topos audits AI-generated software by its structure and logic, not just whether it runs. It catches critical security bugs at the source and documents why the code is sound.
The Mathematics of Verification
Krv evaluates the structure beneath an agent's answer: the representation space it moves through, the boundary where behavior leaves the safe envelope, and the proof obligations its code must preserve.
Krv's representation-guided data fidelity algorithms are currently in use at Childrens Hospitals in California. Manuscript pending.
Evaluating agentic systems isn't about average-case scores. It's about mapping the exact mathematical coordinates where reliability ends, replacing black-box autonomy with mathematical proof of behavior you can audit, deploy, and defend.— Krv Labs Mission
Prevent Hallucinations
Catch the moment an agent reasons over data it doesn't understand. Evidence pinpoints where confidence breaks down, before a fabricated answer ever reaches a customer.
Stop AI Code Debt
Automatically audit agent-generated software for security vulnerabilities and structural flaws, with a documented record of why each change is safe to merge.
Prove Compliance
Hand auditors and regulators an evidence package that certifies agent behavior against your safety, compliance, and business-critical operational standards.
Built in Public
AI safety and reliability demand absolute transparency. Our core verification libraries are entirely open source under the BSD 3-Clause License, so anyone can inspect, audit, and reproduce our work.
Named from our first shared work in Riemannian curvature. Kepler, Riemann, and von Neumann mark the standard we build toward: mathematical taste, structural rigor, and systems that hold up under pressure.
Kepler
Heavens
Mapped with equations.
1571–1630 · Found the three laws of planetary motion — the first time the heavens obeyed exact equations, not philosophy.
Riemann
Geometry
Rebuilt its foundations.
1826–1866 · Built the geometry of curved space — the language Einstein later used to describe gravity itself.
von Neumann
Logic
Codified its architecture.
1903–1957 · Designed the architecture nearly every computer still runs on, and founded game theory along the way.