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Data Product · Live Tool

BurgReport: Fine Wine Pricing Intelligence

A live pricing-intelligence tool that aggregates scattered market data into fast, usable benchmarks for fine-wine buyers, sommeliers, and retailers.

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Role
AI Product Builder
Product
Live pricing intelligence and market benchmarking tool
Stack
Python, FastAPI, OpenAI web search (Tavily fallback), Supabase, Airtable, Railway
Focus
Low-friction user experience (UX), data normalization, and fast time-to-value
01

Challenge

Fine-wine pricing is scattered across sources and slow to evaluate. Buyers often have to cross-reference multiple merchant listings, inconsistent critic scores, and scattered vintage guidance just to get to a usable pricing view. That slows decision-making for collectors, sommeliers, and retailers, and increases the odds of weak pricing decisions. BurgReport was built to compress that scattered research into a single benchmark view that can be used in seconds.

02

Build Decisions

BurgReport acts as a specialized aggregation and pricing-reference layer for fine wine. It provides:

  • Live price snapshots with average, minimum, and maximum retail pricing.
  • Merchant-count visibility.
  • A seen-price checker to compare an observed price against market benchmarks.
  • Normalized critic consensus across major sources.
  • Vintage and drinking-window context to make the pricing signal more useful.
03

The product

A no-login pricing terminal that compresses scattered merchant listings into one confidence-gated read. Click any frame to enlarge.

Landing: paste a quote and search any of 34 Grand Cru climats, the named vineyard plots, no account required.
Pricing terminal: a live search returns range, median, and a confidence-gated defensibility verdict with source counts.
Grand Cru guide: all 34 climats filterable by Cote, color, and monopole status (a vineyard held by a single owner), each one tap from a live price check.
Methodology: trust labels come before price claims. Estimated, reference, and unavailable data stay visibly separated.
Captured walkthrough · 26sReal screen capture
Screen capture of burgreport.com: the live pricing terminal running a La Tache 2019 search with confidence labels and real web-sourced listing data, plus the methodology page. Real product, live data, no fabricated prices.
04

Outcome Evidence

This project was less about model development and more about live data acquisition, normalization, and fast search-to-insight UX. Key technical decisions:

  • Python FastAPI backend on Railway with three routers (search, wines, vintages).
  • Uses the OpenAI Responses API web-search tool (with a Tavily fallback) to fetch live pricing from public merchant listings: unvalidated estimates parsed from public web pages, not a licensed feed or Wine-Searcher integration.
  • Supabase Postgres for a 24-hour cache expiry (TTL) price cache to keep response times sub-3 seconds.
  • Airtable REST API for curated Grand Cru content (descriptions, producers, pairings) with a 1-hour in-memory cache.
  • Nightly Railway scheduled job refreshes 34 Grand Crus across 5 vintages so the cache stays warm.
  • Designed for near-instant utility with no login wall or onboarding friction.
Reliability and Trust Notes
  • 24-hour Supabase cache and nightly cron keep price lookups fast and repeatable.
  • Multiple source normalization reduces outlier noise before benchmark display.
  • No onboarding wall: interface is optimized for immediate utility in high-intent sessions.