Comparing GetDone, HappyCo, and EliseAI's Maintenance App

We sell one of these three, so read the framing accordingly. Every capability below is something the vendor publishes about itself.

These are genuinely different bets rather than the same product at three prices, and knowing which bet you are buying matters more than a feature grid.

Each product answers a different question

HappyCo is the established full-stack play: maintenance plus inspections, PMS integrations across Yardi, RealPage, and Entrata, AI features, and Happy Force for staffed after-hours support. They claim 2.7-day unit turns. Enterprise posture and enterprise pricing.

EliseAI's Maintenance App is the newest entrant, coming at it from AI-first technician management: auto-assignment by skill and location, travel-time routing, automated resident notifications, clock-in and clock-out, and real-time Spanish translation of technician status updates. Integrates with Yardi, Entrata, RealPage, and ResMan.

GetDone is the operator's bet: make-ready depth, gated high-risk compliance workflows, procurement inside the work order, and AI phone triage, built and run inside a company managing 24,000 units. ResMan only.

Where GetDone wins

Make-ready depth, with a timestamp at every stage. Move-out, scope, paint, carpet, punch, cleaning, quality inspection, move-in ready. Turn time is the maintenance metric that lands directly in NOI, and without stage timestamps you know a turn took 11 days and nothing about where those days went. Ayla cut average make-ready time 51% and vacancy loss 55% against a $601,807 annual base.

High-risk work as a gated process, not a category tag. Water intrusion requiring an incident report number. Pool inspections producing an exportable log PDF. Multi-page light inspection reports. Mandatory before-and-after photos and supervisor approval before close, with no way to skip or reorder the checklist. Most maintenance software marks a work order as important. This one refuses to close it without the evidence you would need eight months later. $810K of potential claims exposure mitigated across the portfolio, which is a modeled risk figure rather than claims paid.

Move-out inspections that generate charges. Damage logged by location, category, and severity against a charge catalog with per-property and per-market overrides, then fanned out into real make-ready work orders. That is a finance workflow as much as a maintenance one, and it is unusual in this category.

Procurement inside the work order. Ordering from HD Supply, Sherwin-Williams, and Ferguson, with Coupa integration and PO matching. Most maintenance products stop at noting what you need.

Dispatch built in. An AI phone agent answering after-hours calls in English or Spanish, triaging emergency from routine, escalating through on-call trees, and auto-creating the work order with the recording and transcript attached.

Built by an operator, not sold to one. 94% technician adoption across 24,000 units and 86 properties. The reason that number is high is that the product was shaped by the people who had to use it at 7am.

Where HappyCo and EliseAI are stronger

Stated plainly, because you would find these out in a demo anyway.

PMS coverage. HappyCo covers Yardi, RealPage, and Entrata. EliseAI covers Yardi, Entrata, RealPage, and ResMan. We cover ResMan only. If you run Yardi, this evaluation is short and it does not end with us. This is the single most decisive line in the post.

Route optimization. EliseAI auto-assigns technicians using travel time and unit proximity. We attack the same problem differently: the work order lives on the technician's phone, so nobody drives back to an office to pick up the next job. At Ayla that recovered at least an hour of labor a day per tech. If you want the routing engine itself rather than the trip eliminated, they have one and we do not.

Time tracking. EliseAI has clock-in and clock-out with CSV timesheet export. We have none. If payroll and labor allocation run through your maintenance system, that gap is real.

Staffed after-hours support. HappyCo's Happy Force is people. Ours is an AI phone agent that triages, escalates, and creates the work order with a transcript attached. Some operators want a human voice at 2am, and that is a legitimate preference.

Two overlaps worth testing on all three

Both we and EliseAI address Spanish, and differently enough that it matters. EliseAI translates a technician's status update to and from Spanish in real time. GetDone runs its interface in Spanish and supports Spanish resident notes. Translation and a native-language interface solve different halves of the problem, so ask each vendor precisely which one they do.

Both we and EliseAI auto-create work orders from inspections. Ask what happens to the photos, and whether the resulting order inherits a required workflow or arrives as an ordinary ticket.

When each is the right choice

GetDone, if you are on ResMan, mid-market rather than enterprise, and the things costing you money are turn times, high-risk documentation you would need to defend a claim, and procurement leaking outside the work order.

HappyCo, if you are enterprise scale on Yardi, RealPage, or Entrata, you want inspections and maintenance from one vendor, and you want staffed after-hours coverage.

EliseAI's Maintenance App, if you already run EliseAI for leasing, you want route optimization as the core of the product, or you need timesheets out of your maintenance system.

When each might not fit

GetDone does not integrate with Yardi, RealPage, AppFolio, MRI, or Entrata. We have no time tracking, and we are a smaller vendor than either of the others.

HappyCo may be more platform than a mid-market portfolio needs, at enterprise pricing.

EliseAI's Maintenance App is the newest of the three in this specific category, so ask for named references at your portfolio size, and press on make-ready and compliance depth rather than watching the dispatch demo.

Run this test rather than a feature comparison

Bring your worst property, not your best.

Ask each vendor for a live view of its open backlog over 90 days. Then walk three real scenarios through each product with your own data: a water intrusion event from last quarter, a unit turn that ran long, and a resident ticket that generated a callback.

Then ask all three for their technician adoption rate, the denominator, and the lowest-adoption property in that portfolio. Ours is 94% across 24,000 units and 86 properties, with a lowest performer at 46%. A vendor who will not give you the low end either does not measure it or does not want to say.

Which PMS are you on? That answer settles most of this.