Engineering Consulting
Engineering reports required hours of copying project details, extracting test data, formatting tables, placing figures, and assembling standard language before the real interpretation could begin. We designed an agentic AI product that brings those inputs together, validates the extracted data, and generates a traceable first draft for the engineer to complete.
Users
Engineers & discipline leads
Before
~15 hrs finding & copying data
Target
a traceable first draft
The firm produces thousands of consulting reports across specialized engineering practices. Each one draws from a different combination of data sources such as project proposals, quality-assurance sheets, figures, etc.
Junior and intermediate engineers spent much of the reporting process locating these files, copying project metadata, transcribing technical values, numbering figures, and recreating standard sections. Senior engineers then reviewed those reports for technical correctness, clarity, formatting, and liability-sensitive language.
The bottleneck wasn't the engineering analysis. It was assembling everything required to communicate it.
The product locates the source files for a project, extracts the relevant information, and presents every value for engineer validation before generating the report. Once approved, the system uses the validated data, discipline-specific templates, and report rules to draft the factual, repeatable sections. Sections that need engineering judgment, like results, interpretation, and conclusions, stay with the engineer.
01
The engineer selects a report type, and the system locates expected files from the network or accepts a manual upload.
02
The product extracts project metadata, testing information, and other report-specific values.
03
Every extracted value appears with its source document and passage. The engineer confirms, corrects, or fills gaps.
04
The system combines validated data with the right template and drafts the factual, repeatable sections.
05
The engineer adds technical interpretation, conclusions, tables, photos, and project-specific context.
06
Coaching and quality checks flag potential issues before senior review. The report exports to Word.
01
Engineers review factual values in one place before generation. This stops one incorrect value from getting repeated across a polished-looking report.
02
The system drafts factual and templated content. Results, interpretation, and conclusions stay explicitly owned by the engineer.
03
When a source document changes, the system re-extracts the affected values, shows the old and new versions, and requires engineer approval before updating anything.
Extracted values appear inside the draft as traceable data chips, so an engineer can see exactly where a value came from without leaving the section they're writing. If a validated value changes, the system finds everywhere it appears and shows which sections will be affected.
A correction made once could be reviewed and propagated everywhere that value appeared.