Data Engineering & Business Intelligence
Turn public and internal data into a live decision feed.
The problem
Pricing, competitor and market data is collected by hand, weeks late, and it never reaches the people deciding.
How we solve it
Resilient extraction pipelines with browser automation, scheduling, validation and delivery into your warehouse and dashboards.
Business impact
Daily market visibility instead of quarterly guesswork. Typical return: Margin gains of 2–9%.
What is included
Data Engineering & Business Intelligence solutions
What actually breaks
Someone in pricing opens competitor pages every Monday and types the numbers into a sheet. By the time it circulates, half the prices have moved. Market data arrives as a PDF once a quarter. Where a scraper does exist, it was written once, it broke months ago, and the sheet it feeds has been quietly returning last-known values ever since, which is worse than no data because people still act on it.
How we build it
Extraction runs in Python, with Playwright or Puppeteer driving a real browser only where a source genuinely needs rendered JavaScript or an authenticated session. Every source gets a schema, and every record gets a fetch timestamp and a source URL, so a number in a dashboard can always be traced back to the page it came from. Raw payloads land before parsing, so a selector change can be replayed against stored responses instead of re-crawling. Parsed rows go into PostgreSQL with deduplication and change detection, so you see what moved rather than a full snapshot daily.
What goes wrong on these projects
Sources change without warning, and they usually change silently rather than by returning an error. A layout tweak produces a page that parses cleanly to the wrong value, which is why validation rules matter more than parser cleverness: price within a plausible band, required fields non-empty, row count within tolerance of yesterday. Rate limits and blocking escalate over time, so a pipeline proven at low volume is not proven at scale.
What changes after
Pricing and market data arrive on a schedule, with a timestamp and a source you can check. When a source breaks, an alert fires instead of a stale number propagating. Decisions get made on this week's data rather than last quarter's, which is where margin gains of 2–9% come from.
Questions we get asked first
Is the data collection compliant?
Foxquart collects publicly available data only, respects rate limits and legal boundaries, and documents the sources behind every pipeline. That documentation matters later: when someone asks where a number in a pricing decision came from, the pipeline can be traced back to a named, permitted source rather than an unattributed scrape.
What happens when a source changes?
Foxquart pipelines are monitored, so a broken selector raises an alert and is patched under the maintenance agreement. The common failure elsewhere is a scraper that breaks and nobody notices for a month, quietly feeding stale data into decisions. Change detection and validation catch that before it reaches a dashboard.
How often is the data refreshed?
On whatever schedule the decision needs, run by scheduled extraction pipelines rather than by hand. The point of Foxquart data intelligence is daily market visibility instead of quarterly guesswork, so pricing and competitor feeds usually run far more often than the weekly manual research they replace.
Can the data feed our existing warehouse and dashboards?
Yes. Foxquart delivers extracted data into the warehouse and dashboards you already use, or through custom data APIs where a system needs to pull it directly. Validation and deduplication happen before delivery, so what lands in your BI layer is clean rather than raw.
What is the commercial case for a data pipeline?
Foxquart data intelligence work targets margin gains of 2–9%, earned by pricing and market decisions made on daily data instead of information collected by hand and already weeks old. There is no list price: discovery is fixed price and delivery is scoped per phase or on retainer.
Who maintains the pipelines after they are built?
Foxquart does, under a maintenance agreement that covers monitoring, alerting and patching when a source structure changes. The pipelines and their sources are documented, so your own engineers can take them over instead. Either way the extraction estate is not left as undocumented scripts nobody maintains.
Tell us the process that is costing you the most hours.
A 30-minute call: what to automate first, what to leave alone.