I built an open-source financial research terminal (SEC data and SQL)
Details
- External ID
- 48543537
- Source
- HN
- Company
- —
- Product
- I built an open-source financial research terminal (SEC data and SQL)
- Website domain
- tesseractanalytics.ai
- Launched
- June 15, 2026
- Cohort
- —
- Upvotes
- 5
- Upvotes percentile
- 0.12568306010928962
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
I posted this a few weeks ago and the server died under the traffic. Fixed that by adding an in-mem caching layer with Redis/valkey and added CloudFront caching for static content. Also upgraded the server.Also fixed the Firefox bugs, trying again.It's a research tool for US stocks. Financials for ~10k companies pulled from SEC filings. You can chart any metric across companies, filter news by ticker, ask questions in plain English and get a chart back. There's also SQL console against the whole database, which is the part I like to use together with the AI chat (generates an SQL query).Doesn't do international stocks or intraday data yet.Its a python flask app + gunicorn, with duckDB for datasets.GitHub: https://github.com/alexanderdolotov/open-terminal Self-hosted: https://terminal.tesseractanalytics.ai Docs and landing page: https://tesseractanalytics.ai
Enrichment
- Theme
- financial intelligence and trading tools
- Vertical
- Fintech
- Function
- Analytics & BI
- Audience
- Developer
- AI stance
- Not AI
- Project type
- Hobby / open-source project
- Normalized one-liner
- sec financial data terminal with sql
- Manually corrected
- False
Could you build this?
Partial The frontend dashboard and SQL/financial queries are vibe-codeable, but building and maintaining a reliable SEC EDGAR parser and financial normalization pipeline across 4,000+ public companies is notoriously tricky.
What it would actually take: The system requires an automated ingestion pipeline connecting to SEC EDGAR (XBRL, 10-K, 10-Q) and market APIs (Polygon.io), normalizing messy and inconsistent XBRL taxonomies into a structured SQL database (PostgreSQL/DuckDB). It needs a caching tier (Redis/Valkey) and an in-browser or backend query engine that safely executes user SQL against multi-gigabyte datasets. The hard part is handling the non-standardized reporting, amendments, and quirks inherent to historical SEC filings across thousands of corporate filers.
Discussion
No comments on this launch.
Competitors
Other products that read as similar to this one — 184 launches clear the similarity bar, closest 8 shown.
Attention rank: #170 of 185 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 219 days after the earliest competitor.
- FactIQ · hn · 2026-07-08 · 7 upvotes · similarity 0.51
- I built a website to visualize company financial data · hn · 2025-11-08 · 7 upvotes · similarity 0.49
- Trader News · hn · 2026-09-24 · 25 upvotes · similarity 0.49
- I licensed $50k of stock market data to do analysis Claude can't · hn · 2026-09-10 · 7 upvotes · similarity 0.49
- Finterm.ai Bloomberg terminal for Claude Code · hn · 2026-07-13 · 6 upvotes · similarity 0.48
- Stock Broker Analyzer · ph · 2026-09-12 · 2 upvotes · similarity 0.48
- OpenAlgo Charts · ph · 2026-09-18 · 62 upvotes · similarity 0.47
- 13Radar · hn · 2025-11-17 · 7 upvotes · similarity 0.46
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a analytics & bi tool for Legal yet.