DeepTable – an API that converts messy Excel files into structured data

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We tried to build an Excel error checker. To achieve that, we needed to actually understand the semantic structure of a spreadsheet first. So we built that, and it turned out to be the harder, more general problem. The core issue: most real-world spreadsheets aren't relational tables. Merged cells, multi-level headers, multiple tables per sheet, totals mixed in with data. You can't just dump them to CSV and call it done. LLMs handle the easy cases but fall apart on complex workbooks at scale. Our approach uses an agent-guided compilation pipeline that produces SQL-ready relational tables with full cell-level provenance. This demo visualizes what we do: https://storage.googleapis.com/deeptable-public/deeptable_an... We have a handful of early customers but honestly don't know yet whether this is a real market or a niche problem. We're posting this to hear from people who've dealt with arbitrary spreadsheet ingestion. Whether you solved it, gave up, or are still living with the pain. If you want to try it on your own files, email me (see my profile for my email) and I'll give you API access.

Visit product View on Hacker NewsMar 31, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, google, email · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, pipe, io · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: google, visualize · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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