ENGINEERING DOCUMENT INTELLIGENCE · PRIVATE DEPLOYMENT · CUSTOM AI WORKFLOWS
DOCUMENT CONTEXT · LINEAGE · CHANGE IMPACT

Documents contain facts. Connections create intelligence.

Engineering answers rarely live in one file. What matters is which part, feature, requirement, supplier, inspection, decision and revision every piece of information belongs to.

Illustrative cross-document intelligence — available through a scoped custom project

IrisX concept visualization: drawings, bills of materials, first article inspection, emails, comments, specifications, and revision history connect to the engineering domains of parts, suppliers, requirements, processes, and quality, enabling lineage, traceability, impact analysis, and AI-ready data.

Illustrative data and relationships. Change-impact and multi-system traceability require workflow-specific extraction, source verification, and integration.

FROM FRAGMENTED TO TRACEABLE

Not simply a database of files. A map of engineering meaning.

An engineering record combines entities, evidence, revisions and relationships rather than collapsing everything into text chunks.

01

Source content

Drawings, BOM rows, FAI characteristics, supplier emails, requirements, comments, inspection records.

02

Domain context

Parts, suppliers, requirements, processes and quality — with source-linked entities and relations.

03

Changes over time

Revisions, versions, superseded values, approvals, and why an engineering decision changed.

04

Actionable outputs

Lineage views, impact questions, traceability evidence and structured data for AI applications.

EXPLORE THE POSSIBILITIES

Questions that need more than document search.

Choose an example to see the kinds of relationships a custom IrisX workflow could bring together.

ENGINEERING QUESTION

Can we accept a supplier's request to change material specifications?

A proposed material change can affect a part's BOM, specification, drawing callouts, FAI results and previous engineering decisions.

CONNECTED EVIDENCE · CONCEPT

Proposed output: an evidence-linked review package, not an automatic engineering approval.

THE AI READINESS CONNECTION

Give an AI agent the missing context.

Raw text tells an AI system what a page says. Structured relationships can help it understand which requirements, parts, revisions and source documents matter to a question.

Explore AI-ready technical data →
Document → extracted field → part / requirement → revision → source evidence → answer
Readable records
Source references
Human review

Custom architecture example; not a claim of an installed knowledge graph.

START WITH A HIGH-VALUE QUESTION

What important answer takes your engineers days to assemble?

Bring a representative set of documents and a question. We'll help scope what could be connected and how to validate it.