Pull the provider, account number, service address, billing period, amount due, taxes and line charges off a utility bill and into a spreadsheet, instead of keying them one field at a time. Electric, gas, water, telecom, and waste bills all read through the same engine, whatever the layout. Upload a batch below and read the fields back as Excel, CSV, or JSON.
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A utility bill is a bill: a provider, an account, a service address, a period, and a stack of charges. The trouble is that no two utilities lay it out the same way, so the property manager splitting costs across units and the energy analyst benchmarking spend both end up retyping the same handful of numbers off a hundred different templates.
The account number sits top-right on one bill, boxed on the back of another, and printed sideways on a third. A rules-based parser tuned to one utility returns garbage the moment the next provider prints their bill differently.
Bills come as portal PDF downloads, emailed statements, and scanned paper from tenants. A scan has no text layer, so a spreadsheet import returns nothing until something reads the pixels first.
Amount due is easy. The delivery charge, the supply charge, the taxes, the fees, and the usage that a landlord actually needs to allocate are scattered across the bill in a different order every time.
A property manager with forty units or an ESG consultant benchmarking dozens of sites is not extracting one bill. They are doing the same keying a few hundred times a month, which is exactly the work worth deleting.
ReceiptOCR reads a utility bill the way it reads a vendor invoice: it recognizes text on scanned pages, finds the fields that matter regardless of where the provider printed them, and returns consistent columns you can total, allocate, or import.
No per-utility template to build. The engine locates provider, account number, service address, and billing period on a layout it has never seen, so a new provider in the batch is not a new configuration project.
Supply and delivery charges, taxes, fees, and the amount due come back as separate labeled values where the bill lists them, so you can allocate real cost components instead of one lump sum.
When a bill states meter reads and consumption, kWh, therms, or gallons come through with the charges. Where a provider omits usage, the page never invents it.
Upload a month of bills across every site and get one stacked sheet. Each file is read on its own, so accuracy holds whether the batch is five bills or five hundred.
Every extracted value is visible and editable before the file leaves. A wrong account number on an allocation is expensive to unwind, so you confirm rather than trust.
Excel and CSV for allocation and benchmarking spreadsheets, JSON when the data feeds an application, and QuickBooks-ready files when the bills post to a ledger.
From a folder of statements to a spreadsheet you can allocate or benchmark, with no template and no retyping.
One statement or a whole month across every site. Portal PDF downloads, emailed bills, and scanned paper from tenants all go in the same batch, and mixing providers is fine.
Tip: Include your ugliest bill, the scanned one from the tenant who photographed it on a kitchen counter. That is where weak tools fail and a real one shows.
Review provider, account, service address, period, and the charge breakdown on screen. Correct anything the engine flagged, which on faded or handwritten paper is where a person still earns their keep.
Download Excel or CSV for your allocation model, or call the same extraction over a REST API and skip the spreadsheet entirely.
Built for US teams whose real requirement is utility charges and usage in a spreadsheet, not an energy-management platform and not a data-entry temp.
Utilities get allocated back to tenants, units, or common areas. That means reading account, service address, period, and charges off dozens of bills a month, then splitting them, without a rules engine per provider.
Benchmarking spend and consumption across a portfolio needs usage and cost in clean columns. A bill per site, every month, is a data-entry problem before it is an analysis problem.
Utility bills are recurring payables. Reconciling them across many locations means the same fields off every statement, coded to the right account, ready to post.
Phone and internet bills carry line charges, taxes, and surcharges that need auditing against contract. Extraction gets the line detail into a sheet where the audit can actually happen.
Last updated July 2026.
Utility bill data extraction reads the structured fields off an electric, gas, water, telecom, or waste bill, the provider, account number, service address, billing period, amount due, taxes, and the individual charges, and returns them as spreadsheet columns instead of a PDF you retype. Because a utility bill is a bill, it extracts the same way an invoice does: header fields plus itemized charges, with usage included where the provider prints it.
Upload the bill as a PDF or an image, let the engine read the fields, review them, and export to Excel or CSV. There is no template to build for each utility. The engine locates the provider, account number, service address, billing period, and charges wherever that particular company printed them, so a bill from a provider you have never processed comes back in the same columns as the rest.
The reliable header fields are provider name, account number, service address, billing or statement date, service period, amount due, and the tax and fee lines. Where the bill itemizes charges, the supply charge, delivery charge, and individual surcharges come through as separate values. Where the bill states consumption, usage figures such as kWh, therms, or gallons and the meter reads behind them are extracted alongside the charges. What a given provider does not print, the extraction does not invent.
| Field group | Typical values | What you do with it |
|---|---|---|
| Account identity | Provider, account number, service address | Match the bill to a unit, site, or tenant |
| Dates | Statement date, service period, due date | Assign the cost to the right month |
| Charges | Supply, delivery, taxes, fees, amount due | Allocate real cost components, not one lump sum |
| Usage | kWh, therms, gallons, meter reads (when printed) | Benchmark consumption across sites |
Yes, when the extraction is AI field detection rather than a fixed template. Plain OCR turns the bill into text but leaves you to find the account number in that text, which fails the moment the next provider moves it. Field extraction identifies what each value means regardless of position, which is the only approach that survives a portfolio of bills from many different utilities. This is the same difference we cover in OCR versus IDP.
A portal PDF download and a scanned paper bill are handled the same way: upload the file, the engine reads it, and you export Excel or CSV. A digital PDF has a text layer the engine reads directly. A scan or a phone photo has no text layer, so the engine runs recognition on the image first, then extracts the fields. You never have to work out which kind of PDF you are holding before you start, a point we explain in PDF data extraction.
When the bill prints them, yes. Most electricity and gas bills show the current and previous meter reads and the resulting consumption, and those come through with the charges. Some suppliers, especially fixed-rate resellers, print only the amount and omit the reads entirely. The extraction returns what is on the page and flags nothing as usage that the provider did not state, because an invented meter read is worse than a blank one.
Upload them as a batch and get one stacked spreadsheet, a row per bill. Each file is read independently, so a five-hundred-bill portfolio extracts at the same per-document accuracy as a single statement. Teams running recurring monthly batches use the bulk upload path, and developers feeding the data into an allocation system call the extraction API instead of downloading files.
Accuracy depends far more on the input than on any headline percentage. A clean portal PDF extracts close to perfectly. A creased, low-contrast phone photo of a folded bill is harder, and that is exactly why every extracted value is shown for review before export. Treat any single accuracy number, from any vendor, as a claim to test on your own worst bills rather than a promise. Count the rows that needed a correction and decide from that.
Yes. The output is built to be imported, not just looked at: Excel and CSV for allocation and benchmarking, a QuickBooks-ready file when the bills post as payables, and JSON over a REST API when the data feeds software. Because a utility bill reads as a vendor bill, the same path that handles invoice OCR and invoice PDF to Excel conversion handles the utility statement. For the wider category, see intelligent document processing.
Upload the bill as a PDF or image, let the engine read the provider, account number, service address, billing period, and charges, review the values, and export to Excel or CSV. There is no per-utility template to configure, so a provider you have never processed returns in the same columns as the rest.
Provider name, account number, service address, statement and service dates, amount due, taxes and fees, and the itemized supply and delivery charges. Where the bill prints consumption, usage figures such as kWh, therms, or gallons and their meter reads come through too. Fields a provider omits are not invented.
Yes, when it is AI field extraction rather than a fixed template. Plain OCR gives you the text but leaves you to find the account number in it, which breaks when the next provider moves that number. Field detection identifies each value by meaning regardless of where it sits on the page.
The same way as a digital one: upload the scan or photo and export Excel or CSV. A scan has no text layer, so the engine runs recognition on the image first and then extracts the fields, which means portal PDFs and photographed paper bills go through the same upload.
When the bill states them, yes. Most electricity and gas bills print current and previous meter reads and the resulting consumption, and those come back with the charges. Suppliers that omit usage return no usage, because the extraction reports what is on the page rather than estimating it.
Upload them as a batch and get one stacked spreadsheet with a row per bill. Each file is read independently, so a large portfolio extracts at the same per-document accuracy as a single statement. Recurring monthly batches use the bulk upload path and integrations use the API.
Clean portal PDFs extract close to perfectly; creased or low-contrast photos are harder, which is why every value is shown for review before export. Treat any headline accuracy figure as something to test on your own worst bills, and judge it by counting the rows that needed a correction.
Yes. Export Excel and CSV for allocation or benchmarking, a QuickBooks-ready file when bills post as payables, or JSON over a REST API when the data feeds an application. A utility bill reads as a vendor bill, so it uses the same export paths as invoice extraction.
Read vendor bills into header fields and line items.
Any bill layout straight into spreadsheet rows.
Pull tables and fields out of any PDF, scanned or digital.
Batch a folder of documents into one sheet.
What the IDP category includes, and which parts you need.
The same extracted fields as structured JSON.
