Trellis recently launched!

Launch YC: 🌊 Trellis : Make your unstructured data SQL ready. Try it live w/ your data⚡️

"LLM-powered Snowflake for unstructured data."

Trellis extracts and transforms your unstructured data to SQL-compliant tables with schema you define with natural language. With Trellis, you can run SQL queries on your unstructured data sources like financial documents, contracts, customers, emails, etc.

Founded by
Mac Klinkachorn & Jacky Lin

✅ Try out the product live at

❌ Problem — Modern data warehouses are not designed for unstructured data

• For complex business and aggregation queries (i.e. what are the most common customer complaints or how do transaction categories change over time? ), RAG and traditional search techniques fall short.

• 80% of enterprise data is unstructured and arrives in many different formats. This makes it hard for applications and business decisions to be built reliably on top of that data.

• Building dedicated ML pipelines to extract features from unstructured data and performing inferences are time-consuming and hard to maintain. Teams are bogged down by handling edge cases.

🎉 Solution

Trellis' AI engine combines LLMs, multimodal models, and database query engines to guarantee correct schema and accurate results across unstructured data sources.

• Define your transformation and tasks with natural language. Trellis takes care of the rest.

• First-class support for PDF, HTML, and images with table transformation, context-aware chunking, and data normalization. Trellis robustly finds and aggregates all the data in situations where the smallest details matter.

• Real-time compute and feature store for all your analytics needs

Trellis in-action: Processing hundreds of pages for all common health insurance plans) ⤵️

🏃🏽‍♂️ Leading Enterprises Use Trellis to:
  1. Supercharge RAG Applications: Enrich RAG pipelines and data warehouse by including business-critical information from unstructured data.
  2. Unlock Hidden Insights from Customer Calls and Emails: Process and query Terabytes of calls and emails to identify revenue opportunities, compliance risks, and user behavior over time
  3. Automate Contract Reviews and Underwriting: Extract key provisions from thousands of contracts, experiment with new features from financial data sources, and build better ML models from the newly transformed structured

Learn More

🌐 Visit to learn more

⭐️ Try out the live
demo and join the waitlist for API access here.

❓ Know someone working with a high volume of unstructured data (PDFs, calls, Log files)? Make the intro!

🗓️ Have a use case in mind? Do a deep dive with the team

👥 Follow
Trellis on LinkedIn and X
March 28, 2024
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