AI Dashboards
Describe the report.
Get the dashboard.
AI Dashboards build custom portfolio reporting from a plain-English request: the cross-property views that normally take your team weeks, or a data warehouse you'd have to buy and staff.
Show revenue, operating expenses and GOP for each hotel, with the total.
| Property | Revenue | Opex | GOP |
|---|---|---|---|
| Harborview Suites | $1.42M | $0.88M | $0.54M |
| Maple Ridge Lodge | $1.19M | $0.76M | $0.43M |
| Cedar Point Inn | $0.96M | $0.63M | $0.33M |
| + 77 more properties | |||
| Portfolio total | $38.4M | $24.1M | $14.3M |
A live 80-hotel portfolio,
queried on camera
Real requests
Two dashboards, as they were asked for
No report builder, no field picker, no ticket to the BI team. These are the requests customers typed, in the words they typed them.
Show revenue, operating expenses and GOP for each hotel, with the total.
Every property down the rows, the portfolio total at the bottom: the view most management companies rebuild by hand every month.
Debt service coverage by property, January through August.
A calculated ratio, per asset, across eight periods. The kind of request that normally starts with “can we even pull that?”
Requests taken verbatim from live customer sessions.
What it takes
Twenty minutes, not two weeks
One customer came to us with a complex cross-property report they needed. They typed the request into AI Dashboards. The system built it and it was ready: exactly the report they'd asked for.
You describe what you need
In a sentence. Name the metrics, the properties and the periods the way you'd say them out loud.
Docyt computes across the portfolio
Eighty hotels is a great deal of data. It takes the system a few minutes to work through it: the same job that takes a finance team days, and sometimes weeks, to assemble by hand.
The dashboard is live
Yours to keep, rerun and share. Next month's version is a click, not another project.
What you get
Portfolio reporting without a data team
Any metric you can name
Revenue, operating expenses, GOP, debt service coverage, and the calculated ratios in between, asked for in plain English rather than built in a query tool.
Any slice of the portfolio
One property, one brand, one region, or all of them. Multi-entity structures are already mapped in Docyt, so cross-property reporting needs no modeling work.
Straight off your books
Dashboards read the ledger Docyt already maintains. What the board sees ties to what the close produced, because it's the same data.
Why it matters
The stack you don't have to build
Portfolio-level BI has historically meant assembling infrastructure: a cloud data warehouse, a BI layer on top, connectors into every system, and analysts to maintain all of it. That's a budget line and a hiring plan before anyone sees a number.
The traditional path
License a data warehouse. Add a BI tool. Build and maintain the pipelines. Hire or contract the people who keep it running. Wait a quarter or more for the first dashboard.
With Docyt
Turn on Business Intelligence. The books are already in Docyt, so the data layer exists on day one. Type the request and the dashboard builds itself.
Bring us the report you can't get.
Start with a handful of properties rather than the whole portfolio. The first dashboard makes the case better than we can.
Want an answer rather than a report?See BooksGPT →