We extract FOAs, technical reports, grid statistics, and policy updates across energy.gov subdomains. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Funding Opportunities (FOAs) objects from energy.gov. All fields typed and schema-versioned.
"foa_id": "DE-FOA-0003107", "title": "Clean Energy Manufacturing", "agency": "EERE", "issue_date": "2023-10-15", "due_date": "2024-01-12", "funding_amount": 25000000.0, "eligibility": "For-profit entities, National Laboratories"
| # | foa_id | title | agency | issue_date | due_date | funding_amount |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Technical Reports (OSTI) objects from energy.gov. All fields typed and schema-versioned.
"osti_id": "1823491", "title": "Next-Gen Battery Chemistries", "authors": "['Smith, J.', 'Doe, A.']", "publication_date": "2023-08-22", "doi": "10.2172/1823491", "abstract": "Analysis of solid-state lithium structures...", "pdf_url": "https://www.osti.gov/servlets/purl/1823491"
| # | osti_id | title | authors | publication_date | doi | research_org |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Policy & Directives objects from energy.gov. All fields typed and schema-versioned.
"directive_number": "DOE O 414.1D", "title": "Quality Assurance", "category": "Management", "status": "Active", "effective_date": "2011-04-25", "responsible_office": "Office of Environment", "sunset_date": "2025-04-25"
| # | directive_number | title | category | status | effective_date | sunset_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Energy Metrics & Grid Data objects from energy.gov. All fields typed and schema-versioned.
"dataset_id": "EIA-ELEC-01", "region": "ERCOT", "metric_type": "Net Generation", "timestamp": "2023-10-24T12:00:00Z", "value": 45200.0, "unit": "MW", "source_agency": "EIA"
| # | dataset_id | region | metric_type | timestamp | value | unit |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Press Releases objects from energy.gov. All fields typed and schema-versioned.
"article_id": "pr-2023-10-12", "headline": "DOE Announces $7 Billion for Hydrogen Hubs", "publish_date": "2023-10-13", "tags": "['Hydrogen', 'Infrastructure', 'Bipartisan Infrastructure Law']", "body_text": "Today, the administration announced historic investments...", "media_urls": "['https://energy.gov/sites/default/files/hydrogen-hub.jpg']"
| # | article_id | headline | subheadline | publish_date | authors | tags |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Government websites present unique extraction challenges including legacy DOM structures, fragmented subdomains, and heavily nested PDFs. Our infrastructure handles these edge cases natively.
Crawl across eere.energy.gov, osti.gov, arpa-e.energy.gov, and other departmental silos using a unified schema.
Parse nested tables, metadata, and unstructured text from Funding Opportunity Announcements and technical reports.
Track grant deadlines, eligibility criteria, and document amendments with automated change detection.
Extract OSTI metadata, author citations, DOIs, and full-text abstracts from national laboratory publications.
Receive diffs for policy updates and directive modifications rather than redundant full-text downloads.
Execute complex state transitions to extract grid data and EV infrastructure statistics from interactive dashboards.
Extract and normalise energy market data from legacy HTML tables into structured column formats.
Standardise varied government date formats, funding units, and office hierarchies into clean data types.
Handle infinite scroll, legacy ASP.NET paginators, and hidden form states across federal archives.
Brief in. Clean data out.
Specify target offices, grant categories, or dataset types. We design the extraction schema together.
We configure Scrapy crawlers, PDF extraction rules, and multi-subdomain routing for energy.gov.
Schema validation, null-rate checks, and PDF parsing accuracy verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Federal websites present unique extraction challenges. We build pipelines that normalise legacy architectures and complex document formats.
The Department of Energy operates dozens of sub-agencies, each with custom CMS implementations. We map these varied HTML structures into a single normalised schema for your warehouse.
Critical funding details are often locked inside 100-page PDF files. We deploy OCR and structural parsing to extract budget tables, deadlines, and eligibility criteria into queryable fields.
Many federal archives rely on legacy viewstates and complex session cookies. Our Playwright integration navigates these stateful forms to extract historical records.
Government sites utilise strict Akamai rules to prevent DDoS attacks. We configure polite crawl delays, residential proxy rotation, and concurrent request limits to ensure stable extraction.
Federal data often mixes date formats and measurement units across departments. Our pipeline includes post-processing scripts to cast these values into strict database types.
Research institutions and clean-tech startups monitor FOAs to secure federal funding for new projects.
Energy producers track directive updates and efficiency standards to ensure regulatory compliance.
Commodity traders ingest grid reliability metrics and generation statistics to forecast pricing.
Universities mine OSTI technical reports to track technological advancements in battery chemistry and solar efficiency.
Venture capital firms analyse EERE project data to map federal investment trends in climate technology.
Contractors monitor historical award data and project summaries to optimise future government proposals.
"The Department of Energy publishes the most critical energy transition data globally, but it is buried in PDFs and legacy subdomains."
Extracting data from federal websites requires more than simple HTTP requests. You need optical character recognition for legacy PDFs, JavaScript rendering for modern data portals, and adaptive schemas to handle 40 different agency subdomains. We manage the pipeline so you can analyse the policy.
Everything supported by our energy.gov scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles broad crawls across massive government archives, managing deduplication and polite request delays to respect federal server limits.
Dedicated worker nodes run OCR and structural layout analysis to convert complex government documents into queryable JSON records.
Airflow schedules extraction jobs across Kubernetes clusters, ensuring reliable data delivery regardless of target site latency.
Data delivered to where your team already works — no new tooling required.
About energy.gov scraping, legality, and pipeline operations.
Ask us directly →Yes. Data published on energy.gov and its subdomains is generally public domain information funded by taxpayers. We extract only publicly accessible documents, grants, and metrics without bypassing authentication or accessing classified systems.
Yes. Our pipeline includes a dedicated PDF processing layer that uses layout analysis and OCR to reconstruct budget tables and eligibility matrices from federal documents.
We cover all public subdomains including eere.energy.gov, osti.gov, arpa-e.energy.gov, eia.gov, and specific national laboratory publication portals.
Pipeline cadence is configurable. Grant trackers typically run daily, while deep historical archives may be extracted on a weekly or monthly schedule depending on the source update frequency.
Yes. We can configure initial runs to crawl backwards through federal archives, extracting policy directives and technical reports dating back to the limits of the online repository.
Yes. Government data schemas vary wildly between departments. We handle the normalisation layer, ensuring dates, funding amounts, and office names match your target warehouse structure.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually downloading PDFs and checking for FOA amendments. We build and maintain the extraction infrastructure. Tell us your data requirements.
