Integrum.one builds the safety layer for modern AI — verifying that the data models learn from is accurate, and that the models themselves behave safely at scale.
Provenance, accuracy and bias checks on every record.
Red-team evals & alignment checks before you ship.
Traceable, signed reports your team and regulators can trust.
Red-team & alignment tests probe models before they ship.
As models grow larger and more autonomous, the cost of bad data and unsafe behavior compounds. Safety can't be bolted on at the end — it has to be built into the data and measured continuously. These are the failure modes Integrum.one is built to catch.
Corrupted or malicious records slip into training sets and quietly steer model behavior. We detect and quarantine them before they spread.
Powerful models can optimize for the wrong objective. We test whether a model actually does what you intend — not just what you asked.
Skewed data produces skewed decisions. We surface representational and outcome bias before it ever reaches your users.
Models invent facts and degrade over time. We benchmark factual accuracy and keep tracking it long after launch.
Adversarial prompts slip past guardrails. Our red teams probe for exploits the way real attackers would — then help you close them.
Systems you can't inspect can't be trusted. We produce signed, traceable evidence for every check we run.
From the raw data your models ingest to the behavior they exhibit in production, Integrum.one keeps every layer accurate, accountable, and safe.
We validate provenance, detect mislabeled and poisoned records, surface bias, and certify that your training data is exactly what it claims to be — dataset-accurate, end to end.
Rigorous red-teaming, alignment testing, and guardrail evaluation for large models — so unsafe behavior is caught before deployment, not after an incident.
Live monitoring, drift detection, and signed audit reports give your team — and your regulators — a verifiable record of safety over the entire model lifecycle.
Everything you need to ship AI that's accurate by data and safe by design — from raw records to live, monitored models.
Validate provenance, detect poisoned and mislabeled records, and certify that every dataset is exactly what it claims to be.
Red-team your models against thousands of adversarial scenarios and measure alignment before anything reaches production.
Watch live models for drift, regressions, and unsafe behavior — with signed reports you can hand straight to auditors.
Map your AI to emerging standards and regulations, with the evidence to prove compliance the moment anyone asks.
A clear, repeatable pipeline that turns messy data and opaque models into something you can actually trust — and prove.
We connect to your datasets, pipelines, and models, then map full provenance so nothing stays a black box.
Automated and expert review flags errors, duplication, bias, and poisoned or mislabeled records — and quarantines whatever fails.
We red-team the model against adversarial prompts and run alignment tests to expose unsafe or out-of-policy behavior.
You receive a signed integrity report detailing every check, result, and remediation — evidence your team and regulators can trust.
Once you're live, we watch for drift and new failure modes around the clock, alerting you the moment integrity slips.
Join the safety teams building AI that's accurate by data and safe by design. Be first in line when we open the platform.