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Senior living · Software vendors

The analytics your customers want.Live in your product in weeks.

Querri is the white-label AI analytics layer for senior living software. Your customers ask questions in plain English and get accurate answers, under your brand, inside your product. You skip the year of building the data layer underneath it.

YourBrand Residents Census Billing Analytics Which communities are below budget on occupancy this quarter? 6 of 42 communities are running below budget Ranked by variance to plan · Q3 to date · every user sees only their communities Cedar Ridge Maple Grove Oakview Stonebrook Two more below plan, and the rest are on or ahead POWERED BY QUERRI Your metric definitions, applied Your permission model, enforced Accuracy tested continuously Your brand, end to end Engineering lift 2 tickets. Data access + embed SDK

Their question, your product, an accurate answer. Querri does the data work underneath.

The talent gap, and your way forward
56%
of mid-market senior living software vendors have zero data or BI staff. Most market analytics today.
54%
of the largest US operators have zero data staff. They can't build this. So they ask you.
6 to 12 mo
to build this in-house, and $150K to $340K in year one before the maintenance tail starts.
2 tickets
to solve your problem. A branded analytics product your sales team demos as yours.
The ask that won't go away

Every QBR ends with the same question

Your customers run 20, 50, sometimes 100 communities on your product. Their data lives with you. Their answers don't, yet.

VP Ops
"Can we see this across all our communities?"Every QBR, this year
CFO
"I need occupancy against budget I can put in front of the lender. One number, not four exports."Renewal call
Regional
"Can my team just ask the system instead of exporting to Excel every Monday?"Support ticket, again
You
"It's on the roadmap."The answer that wins nothing
What that costs youEvery "on the roadmap" is a bake-off point for the competitor who has it, a churn risk at renewal, and another overnight CSV your team ships to someone else's BI tool.
What answering it earnsThe vendor who answers first stops being one of nine logins and becomes where decisions happen. That's retention, expansion, and the demo moment that wins the bake-off.
What the market actually looks like

The leading companies built it.The mid-market is still promising it.

Querri mapped roughly 100 software companies selling into senior living. PointClickCare, Yardi, and Aline have real analytics capability. Of the mid-market vendors, 56% have zero data or BI staff, and most of them have the word analytics on their homepage right now. That gap is what prospects notice in every bake-off. The question is no longer whether your product gets a serious analytics layer. It's whether you build it or embed it.

Category leaders Built or bought real analytics Mid-market 44% with data staff 56% with zero Where that 56% stands in a bake-off: "Analytics" on the homepage Dashboards a release behind the ask No one on staff to close the gap Embedding is how that 56% catches the leaders, this quarter.
The last 20% is the whole game

The demo takes a weekend.Keeping it accurate is the real job.

A capable engineer can wire chat-with-your-data in a sprint, and it'll look great in the Friday all-hands. Production is a different sport, and the difference is exactly what Querri exists to own for you.

"We watched our offline accuracy drift from ~95% at launch to ~65% over a month before we treated this as an engineering problem."
Anthropic, on its own internal analytics agent. The cause: documentation going stale as the data model changed underneath it. Read the post

Right answers, every time

An occupancy number can feed a financing covenant or a family conversation. Querri applies your product's metric definitions at query time, every time, so the answer is defensible. Wrong once and the customer distrusts every answer after.

Permissions that survive AI

Your permission model already knows a regional sees her region. Querri enforces it on every path the AI can take to the data, in a market that handles resident health information.

Evals, forever

Models change under you and schemas drift. Querri runs a standing regression suite for answers, not just code, so a model upgrade never silently changes what your customers see. This is the line item that kills in-house builds after the demo.

SOC 2 Type II ISO 27001 HIPAA-ready Viewing and sharing free
The embed path

2 tickets from your engineers.Analytics under your brand.

Provision data access, drop in the embed SDK. Your instance is live with your data in about a week; customer-facing after tuning, typically two to four weeks, and the tuning needs no engineers. It costs less than one of the engineers the build path requires.

Better than a chat wrapper. Smarter than a BI tool.

The AI layer is a fraction of what you're white-labeling. Underneath it sits the data foundation that separates 21% accuracy from 95%+. On top of it ship the things launch day actually needs: dashboards, embeddable chat, exports, and a tuning interface your product team drives without filing engineering tickets.

No rebuild

Connects to the database you already have. No rip-and-replace, no six-month data project first.

Your definitions

Occupancy is defined by you, and applied on every question, so answers stay consistent and defensible.

Your rules

The AI inherits your access model and can never answer beyond what the user is allowed to see.

Your brand

Ships in your UI under your name. Your sales team demos it as yours, because it is.

Find out if your data is AI-ready today, for free
Get your free assessment

Your product already has the data.Find out what it can support.

Start with one export, or challenge us with as many sources and connectors as you'd like. In 3 to 5 business days you get a branded 4 to 5 page report: what's clean, what's broken, and the questions your customers could already be asking your product. Free, and yours to keep.