Extract usage amounts, charges, meter readings, rate schedules, and account details from utility bills—electric, gas, water, telecom—without templates.
Upload any document — PDF, scan, or photo — and get structured data back immediately. No setup, no templates, no waiting.
Drag and drop files, connect a cloud drive, or set up email auto-forwarding. Any file format works—PDF, JPEG, PNG, TIFF, or digital documents.
The AI identifies fields by context and meaning, not fixed coordinates. Names, dates, amounts, and custom fields are extracted automatically.
Get structured output in Excel, Google Sheets, CSV, or JSON. Use the REST API for direct integration into your systems.
“We manage 120 commercial properties. Processing 500 utility bills per month was a full-time job for one person. OCR automation freed up that position for actual energy analysis work.”
“Our ENERGY STAR benchmarking required utility data in a specific format. The OCR extracts exactly the fields we need and maps them to the right columns for direct upload to Portfolio Manager.”
“Catching billing anomalies required having all utility data in a spreadsheet, which we never had time to build manually. Now we spot rate errors and usage spikes the same month they occur.”
Property managers, energy consultants, and sustainability teams process utility bills at scale. A commercial property portfolio with 50 buildings might generate 200 to 400 utility bills per month across electric, gas, water, sewer, and telecom services. Each bill contains usage data, demand charges, rate schedule information, meter readings, and account details that need to be captured for cost allocation, benchmarking, and sustainability reporting. Manual data entry from utility bills is tedious, error-prone, and creates reporting delays.
Utility bill format diversity makes automation difficult. Every utility provider uses a different bill layout, and even the same provider may change its format when billing systems are updated. An electric bill from Con Edison looks nothing like one from Pacific Gas and Electric, which looks nothing like a municipal water bill from a small regional provider. Template-based OCR requires a separate configuration for each utility provider, creating a maintenance burden that scales with the size of the property portfolio.
AI-powered utility bill OCR reads each bill contextually, identifying usage amounts, demand peaks, charges by rate tier, meter numbers, billing periods, and account identifiers regardless of provider format. Lido extracts this data into structured spreadsheets where it can be analyzed for cost trends, benchmarked across properties, and fed into energy management or sustainability reporting platforms.
Property managers and energy teams evaluating utility bill OCR should prioritize multi-provider format support, accuracy on usage and charge amounts, batch processing for monthly bill volumes, and integration with energy management software. Lido provides all of these along with custom field extraction for provider-specific data points like demand charges and time-of-use rate tiers.
Audited controls over a sustained period, not a point-in-time check.
Bank-grade encryption at rest and TLS 1.2+ in transit.
Documents deleted within 24 hours. No copies retained.
Utility bill OCR handles electric bills, natural gas bills, water and sewer bills, and telecom invoices from any provider. The AI reads each bill contextually, extracting usage amounts, charges, meter readings, and account details without per-provider templates.
AI-powered extraction identifies fields by meaning rather than position. Whether a bill labels a field as “kWh Used,” “Total Consumption,” or “Metered Usage,” the AI recognizes the semantic meaning and maps it to the correct output column.
Yes. For bills with tiered or time-of-use rate structures, the system extracts usage and charges for each tier or time period. This level of detail is essential for energy cost optimization and demand response analysis.
AI-based extraction achieves 95 to 99 percent accuracy on clearly printed utility bills. Confidence scoring flags uncertain values, which is critical for financial data where a misread digit in a charge amount directly impacts cost allocation accuracy.
Extracted data exports to Excel, Google Sheets, CSV, and JSON. Common downstream systems include ENERGY STAR Portfolio Manager, energy management platforms, property management software, and ESG reporting tools. The REST API enables direct integration.
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Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine
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