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Introduction

Engenerate is a knowledge-based engineering workspace that allows you to extract data from complex techinical documents, interact with the data, and build data-driven analyses and designs.

Accurate data is vital to every engineering workflow and Engenerate was built from the ground-up with that in mind, leading the industry in accuracy benchmarks for text, tables, and equations.

Engenerate also allows you full editing control of the data you store, completely removing the black-box problem you encounter with other providers.

What You Can Do​

  • Organize work into projects and workspaces
  • Upload PDFs (including scanned documents), Office documents, CSVs, text files, and images
  • Automatically extract text, tables, figures, plots, and equations from uploaded documents—even from scanned or image-based PDFs
  • Review and edit extracted content before using it downstream
  • Digitize and validate chart-based data with precision tools
  • Create, import, and manage structured datasets
  • Chat with LLM using your project documents as grounded context
  • Select specific documents to increase their priority in any conversation
  • Save useful chat responses directly to a notebook
  • Write, format, and export polished notes and reports
  • Collaborate with teammates through shared Team projects and a shared credit pool
  • Access a curated Library of reference standards and regulations as chat context
  • Search National Bridge and Dam databases directly from chat

A Simple Mental Model​

Engenerate helps you move from raw inputs to working knowledge across three stages:

Extract — Turn uploaded documents into structured, reviewable content.
Interact — Chat with your project knowledge, take notes, and save outputs.
Build — Bring knowledge and models together in an active engineering workspace.

Who Engenerate Is For​

Engenerate is designed for engineers and technical teams who work with document-heavy projects. It is a strong fit when you need to:

  • keep project knowledge organized and searchable
  • ground LLM responses in source documents rather than general knowledge
  • turn figures, tables, and embedded data into reusable datasets
  • move from document review into modeling and reporting without switching tools