Case Studies

A US outdoor equipment reseller needed reliable competitor pricing across 700 SKUs, but manual monitoring was too slow and inconsistent product matching led to incorrect repricing decisions. The team needed hourly visibility into competitor prices, sellers, Buy Box status, and availability.

An AI-powered marketplace price monitoring pipeline with verified product matching, hourly data collection, delta detection, and repricing-ready API delivery across Amazon, Walmart, and eBay. Match-confidence and pricing guardrails ensured unreliable competitor offers were excluded from automated decisions.

Price-change detection improved from 2–4 days to under one hour, audited product-match accuracy reached 98.4%, and Buy Box win rate increased by 31%. The system also recorded zero false-match price cuts and maintained 99.9% uptime.

A US sports analytics startup needed near-real-time moneyline, spread, and totals odds across seven sportsbooks and four major leagues. Inconsistent formats, event matching issues, rapid line movements, and changing sportsbook structures made reliable cross-book comparison difficult.

A managed real-time odds pipeline with dedicated sportsbook collectors, canonical event and market matching, normalized odds data, and sub-minute delta detection. The feed also incorporated timestamped injury, lineup, and weather signals and delivered live updates directly into the client's AI fair-price model.

The client achieved a median 22-second line-movement detection latency, 99.93% cross-book event matching accuracy, and 99.95% pipeline uptime. The platform now processes more than 2.1 million odds updates on peak game days.

A US real-estate media platform needed fresh, structured listing data across multiple metros to power hyperlocal content and lead generation. Manual research was time-consuming, while fragmented, duplicate, and stale listings made daily price-change tracking difficult.

A managed property listings pipeline collecting daily data from Zillow, Redfin, Realtor.com, and Apartments.com, with entity resolution, deduplication, price-change detection, and event-based feeds for new listings, price reductions, and status changes.

The platform expanded from 3 to 27 metro markets, automated research, reduced content production costs by 70%, and brought published duplicate rates below 0.5%. Daily price-change detection also became the foundation for its highest-converting lead product.

A US sales intelligence company needed 50,000 verified business records with live websites and current CEO, President, or Owner names, but generic list vendors struggled with outdated leadership data, dead domains, duplicates, and inconsistent verification.

A custom B2B data extraction pipeline combining public-source scraping, cross-source leadership verification, AI-powered entity matching, deduplication, and human quality control to produce an auditable company database.

The client received 50,000 verified records with 100% live websites, 0% duplicate rate, 100% records verified within 90 days, and 97.2% audited leadership-name accuracy—delivered in 22 days.

A US research and advisory firm needed to convert 10,000+ public regulatory PDF filings into a structured benchmarking database within a strict one-week deadline, while maintaining high field-level accuracy and handling multiple document template revisions.

A batch PDF data extraction pipeline that classified documents by template, reconstructed structured tables, extracted 42 fields per filing, validated financial and categorical data, and delivered an auditable CSV and JSON dataset with source-page references.

The full corpus of 10,214 PDFs was processed and delivered in 72 hours with 99.6% audited field-level accuracy, while only 1.9% of documents required human review. The resulting pipeline was also reused for quarterly database refreshes.

A US used-car marketplace needed a reliable view of vehicle pricing across CarGurus, Cars.com, and AutoTrader to benchmark listings, help sellers price competitively, and identify genuine deals.

A matched, timestamped used-car listing intelligence feed capturing vehicle attributes, mileage, pricing, location, seller type, days-on-market, and price-drop history, with duplicate vehicles reconciled across marketplaces.

The marketplace gained accurate cross-site price benchmarks, identified underpriced acquisition opportunities, helped sellers reprice aging inventory, surfaced buyer deals, and generated cleaner market statistics through precise vehicle matching and de-duplication.