Human Resources
Provable, fair AI for the most sensitive data you hold
HR agents touch compensation, background checks, performance, and personal data, and any automated employment decision now has to withstand a bias audit and an adverse-action challenge. NuDay keeps employee data encrypted and access minimum-necessary, cryptographically binds your fairness guardrails so they cannot be bypassed at runtime, and produces a per-decision, tamper-evident record your legal, compliance, and works-council reviewers can examine.
Employee data never sits in plaintext for a breach to take.
Every automated decision is on the record, with the fairness rules cryptographically enforced.
Why it stalls
Why HR AI stalls in review
The pilots work. What blocks them is four things legal, privacy, and employee representatives cannot get comfortable with, and what changes each conversation:
Compensation, background, and performance data leaks into the agent's memory and context. NuDay encrypts the agent's data layer, so a breach yields unreadable ciphertext.
Agents over-reach across the entire HRIS, well beyond the task at hand. Zero-credential, on-behalf-of access, scoped and minimum-necessary, bound to the HR user.
No way to show an automated employment decision was fair, or to explain an adverse action. Per-decision, tamper-evident provenance, plus signed fairness guidelines the agent cannot silently bypass.
Regulators, auditors, and works councils want evidence, not assurances. A tamper-evident record of every decision, exportable for bias audits and adverse-action review.
Data sovereignty
Keep a global workforce's data in the right place
Employee data crosses borders and works-council agreements draw hard lines. NuDay is built to keep that data where policy requires.
Residency by region
Run in-region or on-prem so employee data stays inside the jurisdictions your policies and agreements allow.
You hold the keys
Bring your own keys on hybrid; on-prem keeps key custody entirely in-house.
The model stays yours
Run the LLM on-prem so sensitive employee data and the reasoning over it never leave.
The evidence
The evidence your frameworks ask for
NuDay does not certify fairness or grant compliance. It produces the concrete, provable evidence your teams map to each obligation.
EU AI Act, high-risk employment
Tamper-evident logging and cryptographically bound guardrails for high-risk employment systems, so behavioral limits cannot be rewritten at runtime.
NYC Local Law 144
A per-decision record that supports the bias audit and transparency an automated employment decision tool requires.
EEOC and Title VII
Signed fairness guidelines the agent cannot bypass, and an auditable trail to evidence how a decision was reached.
GDPR and CCPA
Employee and candidate data is encrypted in agent memory; cryptographic deletion of a key satisfies erasure requests.
FCRA and adverse action
Where agents use background-check data, per-decision provenance supports the explanation an adverse-action notice requires.
Works councils and co-determination
Scoped access and a transparent, tamper-evident record give employee representatives something concrete to review and agree to.
What review gets
What legal, privacy, and compliance get
Not a promise that the AI is fair, but the evidence to examine it and the guarantee that the rules stay enforced.
Per-decision provenance
What the agent did, on whose behalf, and against which signed guidelines, on every decision.
Employee data encrypted
Memory, RAG, and shared context are ciphertext, per record, with independent keys.
Fairness rules enforced
Anti-bias guidelines are cryptographically bound, so an agent cannot quietly drop them mid-task.
For talent, people ops, and HR tech
Get your stuck HR AI moving.
Bring your pilot and your reviewers. We will walk through how employee data is encrypted, how fairness rules stay enforced, and the evidence your legal and compliance teams receive.