SAMPLE: Agilitas Energy × BI Consulting Services

One P&L, every asset — portfolio to state to site, straight from Snowflake.

A standardised Profit & Loss board for a distributed solar, storage and hydro fleet across PJM, ISO-NE, NYISO, ERCOT and CAISO. Revenue lines, opex lines, EBITDA and performance for any single asset or any aggregation — every measure calculated in Power BI, no ETL layer, database already in place.

Prepared for SiddharthSeptember 2026Source pattern: Snowflake → Power BI DirectQuery / import, DAX measures onlyWakefield, MA

Portfolio sun-and-cell map

Every operating asset as a cell — sized by MWdc, coloured by EBITDA margin, grouped by ISO. Click a cell to drill to that asset's P&L.

What this board answers

Three questions from the discovery call, answered with the numbers currently in scope.

P&L waterfall

Revenue lines → operating costs → EBITDA

Revenue vs budget, trailing 24 months

Monthly actual revenue (bars) against budget (dashed). Highlighted band = selected period.

Actual revenueBudgetSelected period

EBITDA by state

Revenue bar with EBITDA share filled; click to drill.

Asset P&L ranking

Every asset in scope, lowest EBITDA margin first. Click a row to open that asset.

Asset	MWdc	Revenue	vs budget	EBITDA	Margin	PR	Avail.

Ask the data

Natural-language questions over the same Snowflake model — answers cite the measure and the visual they came from.

Which Massachusetts assets are below budget EBITDA this quarter?

SOURCE · EBITDA vs Budget EBITDA [Q2 2026] · visual: Asset P&L ranking · grain: asset × month

Which state has the widest gap between PR and budget PR?Rank storage assets by capacity revenue per MWShow O&M cost per MWdc by O&M contractor

Private AI on your own server

The "ask the data" panel above is built to run on a GPU server inside your own network: an open-weight model over your own documents, with every answer citing the file it came from. No per-seat licence, works offline, and nothing leaves the building.

How it sits in your environment

One appliance-class server on your rack or in a secured closet. Your files are indexed where they already live; the model runs locally; answers come back with the source page attached.

What that means in practice

1
Your data only, on your hardwareAn open model over your own documents and exports. No third-party AI processor, no data-transfer agreement to review.
2
Every answer cites its sourceReplies point to the file and page they were drawn from, so people check the answer instead of trusting it blind.
3
No per-seat licenceThe whole team can ask questions. Cost is the server and our build, not a monthly number that grows with headcount.
4
Works offlineIf the internet connection goes down, the answers still come. Nothing depends on a vendor's uptime or pricing changes.