Turn Any Web Page Into Structured Data
We extract, parse, normalize, and deliver structured datasets from any website: tables, directories, listings, search results, and product pages transformed into clean, schema-ready data.
What happens between the markup and your warehouse.
- 20
- Fields resolved per record on a delivered listings table
- 6
- Validation gates a record clears before it ships
- 0
- Cleanup steps left on your side
Website data is messy, inconsistent, and hard to use directly
The information you need is publicly visible on websites, but it's buried in HTML, scattered across inconsistent layouts, duplicated, and impossible to use without significant engineering effort to parse and normalize it.
- Raw HTML scraped from websites requires complex parsing logic to extract meaningful fields
- Data formats vary wildly across sources, dates, currencies, addresses, and units are inconsistent
- Duplicate records from multiple pages and sources inflate dataset size and reduce quality
- Missing values, typos, and encoding issues degrade downstream analytics and model performance
- Custom schemas and validation rules require ongoing engineering investment when sites change
From raw HTML to validated, structured data in your format
Pyronets handles the full extraction and transformation pipeline: parsing HTML, identifying fields, normalizing values, deduplicating records, validating against your schema, and delivering clean data ready for immediate use.
What you get instead
What you get
HTML Parsing & Field Extraction
We identify and extract every relevant field from any HTML structure: nested elements, dynamic attributes, microdata, JSON-LD, and custom class-based layouts.
Table & Directory Parsing
HTML tables, sortable grids, paginated directories, and multi-column layouts are parsed and flattened into clean relational rows with proper column headers.
Data Normalization
Dates, currencies, addresses, units of measurement, and phone numbers are standardized to consistent formats. Inconsistent source formatting becomes uniform output.
Deduplication & Record Merging
Identical or near-identical records sourced from multiple pages or sites are detected, merged, or flagged using configurable deduplication keys and similarity thresholds.
Schema Validation & Error Handling
Every record is validated against your defined schema. Missing required fields, out-of-range values, and format violations are flagged, quarantined, or corrected before delivery.
Custom Output Schemas
Data is mapped to your exact schema (field names, data types, required fields, and relationships) so output slots directly into your database or application without transformation.
Fields we collect.
A starting point, not a fixed list, the final schema is whatever you sign off on during scoping.
How your pipeline gets built
From first conversation to recurring delivery, with a sample you sign off on before anything runs on a schedule.
Source & Schema Analysis
We analyze your target websites and work with you to define the exact output schema: fields, data types, validation rules, and required versus optional columns.
Extraction Pipeline Build
Custom extraction logic is built for each source, including HTML parsers, field selectors, normalization transforms, and deduplication logic tailored to your data.
QA, Validation & Schema Test
The full extraction output is validated against your schema and reviewed for quality. Edge cases, missing data patterns, and format anomalies are resolved before delivery.
Scheduled Delivery & Maintenance
Extraction runs on your schedule. When source websites change, we update the parsing logic and maintain schema compliance without any effort on your side.
Common use cases.
Business Directory Extraction
Parse company name, address, phone, website, categories, and descriptions from directories like Yelp, Yellow Pages, or industry-specific databases.
Product Catalog Digitization
Extract product names, SKUs, specifications, categories, and images from supplier or competitor websites to build or enrich your internal product catalog.
Search Results Harvesting
Systematically extract structured data from search result pages (titles, URLs, descriptions, ratings, and metadata) across any search platform.
Public Records & Filings
Parse corporate filings, court records, property registers, and other public data portals into clean structured datasets for research or compliance use.
Academic & Research Data
Extract publication titles, authors, abstracts, citations, and keywords from academic databases, journals, and research portals for systematic review.
Classified & Listing Sites
Extract listings from classifieds, job boards, real estate portals, and marketplace sites with all relevant fields normalized and deduplicated across the full site.
Delivery formats
Pick whatever drops straight into your stack.
Industries served
Where this dataset tends to be used.
Validated before it reaches you.
Every batch runs the full validation suite before delivery. If a batch fails, it does not ship. We investigate and repair the extraction first, and you get told what happened.
Frequently asked questions
We build adaptive extraction logic that handles layout variations within the same site. For highly inconsistent sources, we use rule sets and fallback selectors to maximize field coverage across all page types.
Yes. We can extract content from PDFs, Word documents, and spreadsheet files linked or embedded in web pages as part of the same extraction pipeline.
Validation failures are quarantined into a separate report file with the reason for failure noted per record. You can review, accept, or route these records for manual review depending on your workflow.
Yes. We map all output fields to the exact names, types, and ordering of your target schema. The output is ready to insert into your database or application without any column renaming.
Yes. We can extract and deliver data in the original language or route it through translation where needed. Character encoding, right-to-left text, and multi-byte characters are handled correctly.
Tell us the sources. We'll send back a sample.
Describe the sites and the fields you need. You'll get a proposed schema, a real sample extracted from those sources, and a fixed price, before any commitment.
No retainer required to find out whether your sources are feasible.
Sectors this data serves
Sectors this dataset commonly serves. Schema and cadence are set per project.
Sample output
An illustrative preview of delivered records. The real schema is whatever you sign off on.
| url | title | description | category | extracted_at |
|---|---|---|---|---|
| techcrunch.com/2025/05/... | AI Model Raises $200M Series C | A leading AI startup... | Technology | 2025-05-19 07:00:00 |
| bloomberg.com/news/... | Fed Signals Rate Cut Path | Federal Reserve officials... | Finance | 2025-05-19 07:00:01 |
| reuters.com/world/... | Trade Talks Resume in Geneva | Representatives from 12... | Politics | 2025-05-19 07:00:02 |
Raw Web Content Becomes Structured Data
Any public web page can be transformed into a clean, schema-mapped dataset ready for analysis.
<div class="product-wrapper x821"><span class="prc" data-v="9">$&19.99</span><p class="nm hidden">Widget <!-- --></p><script>trackView('p',{id:4421})</script><div style="display:none" class="meta">category: electronics | sku: WDG-4421</div>
| name | price | sku | category |
|---|---|---|---|
| Widget Pro | $19.99 | WDG-4421 | Electronics |
| Widget Mini | $9.99 | WDG-4422 | Electronics |
| Widget Max | $29.99 | WDG-4423 | Electronics |