People Ops

AI for people operations

Give the HR team back the hours that go into coordination, and give every employee an answer in seconds instead of a ticket.

People operations carries an enormous administrative load that scales linearly with headcount and geography: scheduling across timezones, chasing documents, answering the same policy question two hundred times a month, and keeping multi-country payroll accurate. Magnigent automates the coordination and the lookup, and deliberately does not automate the judgement — employee relations decisions stay with people, documented by agents.

Use cases

Where people ops gets automated first

Candidate screening and coordination

Structured screening against the scorecard, interview scheduling across timezones, and debrief packet assembly.

Hiring

Offer and pre-boarding

Offer letter generation and approval routing, background check chasing, and right-to-work document collection.

Compliance

Onboarding orchestration

IT provisioning coordination, equipment logistics, access requests, and a day 1 / 30 / 60 / 90 plan generated from the role, not a template.

Experience

HR helpdesk tier 1

Policy, benefits, leave balances, payroll questions and verification-of-employment letters, answered from your own documents with citations.

Volume

Payroll operations

Multi-country input preparation, timesheet exception handling, anomaly detection before submission, and contractor invoice reconciliation.

Multi-country

Leave and accommodation administration

Case tracking, documentation currency and jurisdictional deadline management, with the decisions left to the case manager.

Regulated

Performance cycle operations

Calibration preparation, review nudging, feedback synthesis and promotion packet assembly.

Cycle

Compliance and training tracking

Mandatory training completion, certification and licence renewal watch, and policy attestation campaigns.

Audit

Offboarding and knowledge capture

Access revocation coordination, asset recovery, exit interview synthesis, and structured capture of what the departing person knew.

Knowledge

Agent lifecycle management

The AI-native mirror: scoping an agent's job description, provisioning its access, reviewing its performance and retiring it.

AI-native

How it works

From tacit process to supervised operation

Every engagement follows the same four moves, whichever function it starts in — run by a forward deployed engineer embedded with the team that owns the process.

Ground in your policy corpus

Handbooks, benefits documents, local employment policies and prior answers become a governed knowledge base with jurisdiction awareness.

Enforce data boundaries first

People data is the most sensitive data you hold. Deployment is inside your perimeter, with field-level controls and residency guarantees before a single agent runs.

Automate coordination, not judgement

Scheduling, chasing, drafting and looking up are agent work. Employee relations outcomes, performance decisions and accommodations remain human decisions.

Measure the service, not the tool

Time to answer, ticket deflection, onboarding cycle time and payroll error rate — reported per process.

Let's talk about the first process

Tell us the operation that costs the most and is documented the least. We will tell you honestly whether it is a good first candidate.