An r/buildinpublic post launched Olivepress (a Perplexity-like tool for stocks using FRED/FMP). This walks the recipe — pin to authoritative sources for your vertical, fill SERP/social gaps with Scavio, output as charts + cited paragraphs.
Prerequisites
- A vertical with 3-7 authoritative data sources
- Scavio API key
- LLM API key
- A chart library
Walkthrough
Step 1: Pin the source list per vertical
Discipline = trust.
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// Finance: FRED, FMP, SEC EDGAR
// Real estate: HUD, FRED housing, county assessors
// Healthcare: NIH PubMed, CMS, FDAStep 2: Build a structured query layer per source
API per source.
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// FRED API: macro series
// FMP API: equity fundamentals
// SEC EDGAR: filings
// Each call = typed JSON.Step 3: Use Scavio for the social/SERP layer
What are people saying?
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// 'site:reddit.com r/stocks TICKER 2026'
// 'TICKER earnings 2026 site:wsj.com OR site:reuters.com'
// AI Overview lookup for 'is TICKER a buy 2026'Step 4: LLM compose: pin citations to source-tagged JSON
No 'I think'; only cited claims.
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// LLM: 'Answer using ONLY the sources below. Every claim ends with [N].'
// Sources: [{ idx: 1, source: 'FRED', data }, { idx: 2, source: 'Reddit', data }]Step 5: Render charts as native tool calls
Polished output > raw JSON.
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// Define chart-render tools: { type: 'line', data, x_label, y_label, title }
// Render with Recharts/Plotly server- or client-side.Step 6: Validate against a source-skeptical reviewer
Sanity check before launch.
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// 20 random output queries. Verify each claim against the source it cites.Python Example
Python
# Per-product-month MVP: Scavio $30 + LLM ~$50 + ~$5-15 source feeds = under $100/mo.JavaScript Example
JavaScript
// Same in TS / Next.js.Expected Output
JSON
A vertical mini-Perplexity that pins to authoritative sources, fills the social/SERP gap via Scavio, and outputs charts + cited paragraphs.