TL;DR

We built a workflow that ingests Energy Developer & Utility project packages—everything from PPA contracts and ROW permits to smart meter reports and supplier invoices—and routes each file through the right Retab extractor.

This workflow is inspired by existing Retab clients in the energy sector, who already run similar pipelines in production. By wiring Retab into their document flows, they’ve cut manual review, accelerated project financing, and ensured compliance across highly regulated processes.

The result? In minutes, you get structured, validated JSON across dozens of document types: power purchase agreements, O&M contracts, utility bills, compliance filings, inspection reports, emissions studies, and more.

Perfect for:

• Developers—streamline project finance and compliance

• Utilities—automate billing, reporting, and maintenance workflows

• Regulators & Auditors—gain transparent, audit-ready data

Why Energy Project Packs are so hard to process

When an energy developer or utility works on a project, the paperwork isn’t a neat single PDF. Instead, it’s a flood of heterogeneous files:

• Energy contracts (PPAs, gas supply agreements, O&M contracts)

• Regulatory docs (ROW filings, licenses, permits, compliance reports)

• Invoices (utility bills, supplier settlements, contractor invoices)

• Technical reports (inspection logs, engineering reports, maintenance logs)

• Environmental reports (emissions, impact assessments, sustainability filings)

• Meter data & generation reports

Each document follows its own schema. Traditional OCR or brittle RPA workflows quickly break when layouts shift, new templates appear, or a scanned image lands in the inbox.

How Retab streamlines the workflow

Retab’s approach matches the pattern we’ve seen across industries like insurance and financial filings: classify → route → extract → validate.

1. Classify Each Document

A classifier project trained on energy developer & utility document packs runs first.
It detects whether a file is a PPA contract, O&M contract, regulatory filing, meter report, invoice, etc.

2. Route to the Right Schema

Each label maps to a dedicated extractor optimized for that document type:

• PPA Contract → Energy contract schema

• O&M Contract → Technical contract schema

• Utility Bill → Invoice schema

• ROW Filing → Regulatory schema

• Meter Report → Smart meter schema

• etc.

This is just an example of label matching, do not take it for granted.

3. Extract Structured Data

Documents are parsed against strict JSON schemas. Field-level confidence scores flag uncertain extractions for human review.

Example output from a PPA contract:

{
  "contract_type": "Power Purchase Agreement",
  "effective_date": "2023-06-01",
  "parties": [
    {"name": "SolarCo LLC", "role": "Seller"},
    {"name": "City Utility Authority", "role": "Buyer"}
  ],
  "term_years": 20,
  "capacity_mw": 50,
  "pricing": {
    "rate_per_mwh": 42.75,
    "currency": "USD"
  }
}

Why Retab works well here

This isn’t regex scraping. Retab enforces schemas, applies k-LLM consensus for accuracy, and preserves reasoning traces for auditability.

• Schema Validation → Missing or invalid fields fail fast

• Confidence Scores → Route uncertain extractions to human review

• Consensus Layer → Multiple LLMs vote for near-production accuracy

• Auditability → Reasoning traces + source highlighting = regulator-ready

The Impact for Energy Developers & Utilities

By wiring Retab into the ingestion flow, operators can:

• Cut manual data entry costs by >50%

• Accelerate project finance approval cycles

• Ensure transparent, audit-ready outputs for regulators and auditors

• Unlock structured data for analytics — from emissions tracking to asset performance

Energy developers already deal with complex financing and compliance pipelines. Every misplaced permit date or invoice line item can delay construction, trigger compliance risks, or affect cash flow. Retab automates the messy middle.

Code snippet

You can find a Jupyter Notebook demo file here.

In essence:

client = Retab()

# --- Classify with Retab
    clf_res = client.projects.extract(
        project_id=CLASSIFIER_PROJECT_ID,
        iteration_id=CLASSIFIER_ITERATION_ID,
        document=str(doc),
    )

# --- Route to the right Extraction schema
    route_key = CATEGORY_TO_KEY.get(label)
    dest = DEST_PROJECTS[route_key]

# --- Extract with Retab
    extraction = client.projects.extract(
        project_id=dest["project_id"],
        iteration_id=dest["iteration_id"],
        document=str(doc),
    )

Closing thoughts

Automating energy project document packs isn’t just about efficiency — it’s about trust and scalability. With field-level likelihoods, schema validation, and transparent reasoning, Retab helps energy developers, utilities, and regulators work off the same structured, reliable data.

If you want to try the pipeline or adapt it to your use case, check out our documentation and the related Notebook on GitHub.

Join the discussion on X or Discord — we’d love your feedback.

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