Trellis (YC W24) Turns your Documents into a Database

Hacker News

Hi HN! We're Jacky and Mac, and we're building Trellis ( https://runtrellis.com ). Trellis is the fastest and most accurate way to automate your document workflows. You upload your documents, define the information you're looking for in natural language, and get your results back in an Airtable-like interface. Today, Fortune 1000 real estate and pharmaceutical companies are using Trellis to automate underwriting of Master Lease Agreements, identify missed revenue payments from contracts, and extract patient information from clinical trial lab reports. In many industries like real estate, life sciences, and even the FP&A teams at your favorite companies, critical workflows involve emailing documents back and forth while analysts extract information into Excel spreadsheets or their CRMs. Trellis provides references for the extracted results, allows you to run validation on your results (e.g., does the patient name in the document exist in your DB), and with a single API call, you can sync your data in Trellis to your system of record (e.g., Salesforce, Snowflake, etc.)

Visit product View on Hacker NewsNov 21, 2024

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best fitHighest predicted score across all platforms for this description.

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

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, ide, 000 · Missing: https docs, excited, just released

69%69% 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: way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

16%16% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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