01
Scope the market view
Define the sources, fields, markets, refresh cadence, and edge cases that matter, so the dataset matches the decision, not just the website structure.
Public-web data systems
Public-web data your team can rely on.
WebNano builds managed data systems for pricing, competitor tracking, lead enrichment, sentiment, product intelligence, and market analysis. Coverage, freshness, delivery, and source changes stay managed after launch.
Defined coverage
Reliable refresh
Ready outputs
Managed data layer
Public sources become dependable inputs for real decisions.
Marketplaces
Competitors
Directories
Public filings
Normalized set
entity
price
availability
timestamp
source
BI workspace
Data feed
Ops review
Decision-ready
Teams can see what is covered, what changed, and what is ready to use.
Managed data layer
Public sources become dependable inputs for real decisions.
Marketplaces
Competitors
Directories
Clean dataset
entity
price
source
date
BI workspace
Data feed
Ops review
Teams can see what is covered, what changed, and what is ready to use.
Delivery destinations
Delivered where analysis and review already happen.
Clean public-web data lands in the warehouses, BI tools, files, and review workflows your teams already depend on.
Snowflake
BigQuery
Databricks
PostgreSQL
Looker
ClickHouse
Google Sheets
Airtable
Capabilities
Public web data, maintained like business infrastructure.
Most vendors sell access: proxies, scraping APIs, actors, or generic datasets. WebNano owns the result: scoped, validated, refreshed data that stays usable after the first delivery.
02
Keep it current
Monitor source changes, validation failures, and freshness gaps so the dataset does not quietly drift out of date.
03
Put it to work
Deliver clean data into the workflows your teams already use: feeds, exports, dashboards, APIs, or review queues.
Built for recurring datasets with source monitoring, validation checks, and human review where automation breaks.
Use cases
For decisions that depend on public data staying clean, current, and comparable.
Track competitor prices, stock status, and promotions across changing product pages.
Monitor market coverage, launches, positioning, and footprint changes across public sources.
Enrich account lists with public company, location, contact, and category signals.
Turn reviews and reputation signals into comparable location, product, or competitor benchmarks.
Maintain recurring public indicators for investment, pricing, planning, or risk models.
Normalize product, catalog, store, dealer, or location data across fragmented public sources.
Reliability model
Maintained so the data does not quietly decay.
Public sources change constantly. WebNano keeps the operational layer around the dataset active: monitoring, validation, review, and change handling.
Source change handling
When layouts, access patterns, fields, or coverage shift, the system is monitored and adjusted before bad data becomes normal.
Validation before delivery
Freshness, completeness, duplicates, outliers, and missing fields are checked so teams can trust the feed, not inspect it manually.
Review where it matters
Human review can be added for ambiguous records, source exceptions, entity matching, and outputs that need judgment.
Change history stays visible
Coverage notes, anomalies, format changes, and delivery exceptions are tracked so teams know what moved and why.
Outcome
A managed data system that keeps market signals current, structured, and ready to use.
Use it when pricing, sales, market intelligence, finance, or operations depends on public-web data, and the team needs dependable output without owning the collection stack.