HRIS Integration

HRIS integration for the feed your scorecard is waiting on.

Your headcount and payroll data sits inside the HRIS while the reports wait. We build the AI-managed feed that pulls it out — refreshed every month, with no manual exports.

  • AI implementation services
  • AI-managed feed out of your HRIS
  • Refreshed monthly, no manual exports
  • Your HRIS stays the system of record

Built with the leading AI platforms

NVIDIAAnthropic
Peter Enestrom, founder of Zaigo

Led by Peter Enestrom and the Zaigo AI & engineering team

YaleColumbia UniversityMicrosoft

The broken Friday

Headcount reporting someone rebuilds by hand, every month.

From HR and operations leaders we have sat with: contract-staffing operators tracking budgeted vs actual FTE across dozens of sites, where the numbers live in the HRIS and every report starts as a manual export.

  • The actual number is a moving target

    The budgeted FTE is written into the contract; the actual hired count moves month to month. By the time someone pulls the export and rebuilds the report, the number has moved again.

  • The custom report, rebuilt by hand

    The HRIS has a report builder, so the workflow is: go in, build the report, export it, reformat it, paste it into the scorecard. Every month. By hand.

  • The HRIS knows who is hired — nothing else

    Headcount and hires live in the HRIS. Locums utilization after the initial contract term and overtime utilization by contract live somewhere else entirely. Nobody has one view.

  • The feed request, waiting on IT

    "Can we get a feed that lets us pull data out?" becomes a ticket, a queue, and a quarter of waiting — while the scorecard ships late or ships stale.

  • The built-in AI that can’t see your contracts

    The HRIS’s own AI features answer generic HR questions. They don’t know your contract denominators, your budgeted FTE lines, or what a miss looks like — so the real reporting still lands on a person.

What manual costs

The real cost of manual payroll reporting is a month of lag.

What the manual way looks like at a clinical-staffing company tracking dozens of hospital contracts. An AI-managed feed removes the rebuild; what it can’t recover is the month you spent acting on stale numbers. Tracing one reporting cycle puts figures on yours before anything gets built.

Every monthThe manual rebuild — open the HRIS report builder, export, reformat, paste the headcount into the scorecard
DozensHospital contracts under management at one clinical-staffing company — each with a budgeted FTE line and an actual that moves
One stale numberWhat a month-old export does to contract reviews — misses surface after the month closes, not while there’s time to act

From an anonymized engagement — a clinical-staffing company tracking budgeted vs actual FTE across hospital contracts

How it works

The feed your scorecard waits on, built and run for you.

No new HRIS, no integration project your IT team has to absorb. AI agents pull the data out of the system you already run, on the schedule your reporting needs — and keep the feed running when things change.

  1. 01

    Trace the numbers you actually need

    Which fields, which contracts, which cadence — actual FTE per contract, hires, hours — documented with the person who owns the scorecard, not guessed from a data dictionary.

    Weeks 1–2
  2. 02

    Build the feed

    Through the vendor’s API where access is granted; through scheduled exports where it isn’t. Either way, the pipeline lands clean, validated data where your scorecard can read it — in your cloud.

    Your cloud
  3. 03

    AI keeps it fresh

    Every month the feed refreshes on its own. When a field changes or a column goes missing, AI agents flag it and we fix it before the scorecard reads it — not after the review meeting.

    Every month
For the person Googling this

The Paylocity API is documented for developers. We build and run the feed.

Paylocity’s developer documentation is real and reasonably complete — if you have developers. The Paylocity API tells an engineering team which endpoints exist; it does not map your contracts to fields, schedule the refresh, validate the output, or own the feed when something changes. That work is the actual integration.

We build the Paylocity integration around what your reporting actually needs, run it in your cloud, and keep it running — AI agents watching the feed, people accountable for it. Headcount and payroll reporting flows every month without a manual export, Paylocity stays the system of record, and you own everything we build.

Peter Enestrom, founder of Zaigo
Who builds it

Led by Peter Enestrom.

Co-Founder — leads AI & Engineering

Pete Enestrom

Every engagement is led personally by Pete, working with the Zaigo AI & engineering team from the two-week audit through the production handover. The person who scopes the work is the person who builds it.

Education
Yale & ColumbiaGraduate
Background
Microsoft & IntelFormer
Experience
Exited FounderVenture-Backed

Background

Questions

Asked by HR and operations leaders.

The straight answers, before you book anything.

What’s holding your business back?

A workflow ready for automation. An AI product you want to build. A problem that has sat on the roadmap for years. Let’s talk about what it would take to solve it.

Talk to Zaigo