AI Services for HR

Buying AI is easy. Running HR on it is not.

Satori HR OS gives people teams governed AI agents that know your policies, control their own data access, and run routine work autonomously. We build it, wire it to your org, and keep it governed.

satori hr os · console
RecruitingOnboardingPolicy Q&A CompensationPerformanceAnalytics

ask Is this promotion increase within band?

The proposed 18% lands above the L4 band ceiling. Flagged for HRBP review before any letter is generated.
Compensation agent Band check: above ceiling Approval gate: HRBP
80% of enterprise AI pilots fail within 12 months. Not because the AI was wrong, but because no one governed it. Gartner, 2025
~40%of HRBP time goes to routine policy questions
2-3 hrs → 30 minperformance review prep, per manager
60%of organisations rate new-hire Day 1 as poor
The problem

Ungoverned AI in HR is a liability.

01

Compliance risk

Every AI hiring decision or policy action needs a documented trail. One ungoverned output creates legal exposure that takes months to unwind.

02

Data risk

Without access control, an agent can surface a colleague's salary, a disciplinary record, or a confidential exit package. Breaches happen silently.

03

Operational risk

AI-suggested offers acted on without review. Wrong comp bands applied. The same error repeated across twenty hires, with no way to audit or reverse it.

How it works

Every request takes the same governed path.

A plain-language ask goes in. It is routed, checked, gated, and logged. No step is optional, and nothing bypasses the audit trail.

The fleet

Eight specialists, one orchestrator.

You ask in plain language. The orchestrator routes the request to the right specialist. No manual selection, no prompt engineering.

AgentWhat it handles
RecruitingJD generation, screening, interview kits, offer drafts, pipeline status
OnboardingDay 1 checklists, access requests, buddy assignment, 30/60/90 plans
Policy Q&AInstant answers from the HR manual, flags edge cases, never invents policy
CompensationRevision drafts, band compliance, increment letters, benchmarking
PerformanceReview prep, manager talking points, normalisation, PIP documentation
L&DTraining plan drafts, learning paths, vendor coordination, budget tracking
Exit ManagementSeparation checklists, FnF calculation, knowledge transfer, clearances
HR AnalyticsHeadcount, attrition, hiring velocity, compliance dashboards

Not the full list. Agents are built to your requirements.

These eight cover the work most people teams repeat every week. The architecture is modular, so we build additional agents around how your organisation actually runs. Recent examples include Attendance and Leave, Payroll query handling, Employee helpdesk, Workforce planning, Compliance and audit reporting, and Benefits administration. Every new agent inherits the same governance: scoped data access, human approval gates, and a full audit trail.

How it is governed

Governance is not a setting. It is the architecture.

100%of AI actions written to an append-only audit log
Humanapproval gates on offers, salary revisions, PIPs, exits
Zeroedits to logs. The audit trail only grows
The architecture

Three layers under every call.

This is what makes it a second brain rather than a chatbot: the system knows your org, respects your permissions, and remembers what it has done.

01

Agent skills and memory

Domain rules, decision logic, and your org's institutional knowledge live in structured files per agent. Policies, decisions, and context are stored and retrieved by meaning, not reset on every session.

02

Data access control

Row-Level Security at the database, not the app layer. Agents inherit the requesting user's permissions on every call. An agent can only see what that user is allowed to see. This is a core part of what we deliver, not a setting you configure yourself.

03

Append-only audit log

Every AI action is written to a log that cannot be edited or deleted. No UPDATE, no DELETE. The trail only grows. Compliance, legal, and HR governance all have a single source of truth.

Governance in practice

"Show me Priya's salary revision history."

The same question, four askers, four outcomes. Confidentiality is enforced at the database, and the agent never invents a plausible answer it is not authorised to give.

Asked byThe agent returns
Priya's HRBPFull history, with context
A peer manager"Not authorised"
Priya herselfHer own record only
A recruiter"Not authorised"
The payoff

Where the hours go back to you.

Use caseTodayWith the OS
Repeated draftingJDs, letters, and checklists done by hand, every timeDrafted in minutes; your team reviews and approves
Policy questionsA steady stream of routine queries lands on HRBPsAnswered from your manual; HRBPs freed for real work
Review prepHours per manager, every cycleTalking points and data pre-generated; managers edit, not assemble
Knowledge retentionLeaves with the person when they resignPersists in the memory layer for their successor
Start here

Let's map your first three workflows together.

One conversation. Two hours of your team's time. A clear picture of what is worth automating first, and what should stay human.

Book a discovery call →