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The Engineering Intelligence AI Platform for Regulated Industries

Medical Devices Defence Aerospace

Zero Data
Leakage
Zero Token
Bills
Total AI
Sovereignty

Trust

AI must earn trust before it earns adoption.

Regulated industries are being told to adopt AI and told never to let their data leave. The only honest resolution is to bring the intelligence to the data. Everything else is a compromise somebody eventually has to explain to an auditor.

The problem

Engineering work is spread across records, systems, and revisions.

Generic AI can search and draft. In regulated engineering, it also needs an intelligence layer that connects authoritative records, relationships, revisions, and review context.

01

Higher costs

Skilled engineers spend hours on low-value document work instead of design.

02

Errors & reinvention

Knowledge is lost and rebuilt across teams, programs, and revisions.

03

Increased delivery time

Manual reviews and approvals stretch out critical program timelines.

The platform

One engine, every engineering system, every way of working.

One governed architecture connecting authoritative engineering sources to Enginius applications and the enterprise AI tools your teams already use.

01

Authoritative engineering sources

Internal systems, engineering records, standards, and regulations.

02 · INTELLIGENCE ENGINE

Connexa EIE

Organizes and connects engineering knowledge.

03

Applications and AI tools

Enginius native applications and the enterprise AI tools teams already use.

Who it is for

Built for engineering, quality, regulatory, and IT teams.

01

Engineering & R&D

Search connected engineering knowledge, find the approved revision, and keep the source with the answer.

See the use case
02

Quality & Compliance

Review technical evidence against requirements and standards with a traceable audit trail.

See the use case
03

Regulatory

Ground every answer in regulatory and engineering knowledge, so requirements and standards stay current and traceable.

See the use case
04

IT & Digital

Deploy engineering AI with enterprise permissions, governance, and deployment control.

See the use case
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Engineering workflows

Put the right record behind the work.

From search to generation and review, Connexa keeps engineering knowledge connected to the task in front of your team.

01

Find the governing revision

Search connected engineering records and keep the source beside the answer.

02

Draft from approved information

Use controlled templates and authoritative project knowledge to build documents.

03

Review against requirements

Compare engineering artifacts with criteria, policies, standards, and regulations.

04

Carry context across work

Keep relationships and revisions connected through the engineering digital thread.

05

Put agents on defined workflows

Give native applications and configured agents engineering context to work from.

What we hold ourselves to

The STARS framework.

Security

Deployment and data flows are reviewed against your environment and security requirements.

Trust

Keep source links with outputs and make human review part of the workflow.

Accuracy

Domain-adapted models grounded in your controlled corpus rather than the open web.

Reliability

Design workflows around reviewable steps and an inspectable record.

Scalability

Scope the commercial model around your deployment and use requirements.

Sovereign deployment

Engineering AI. Behind your firewall.

Deployment is designed around your operating boundary. On-premise, private-cloud, and air-gapped configurations are evaluated against your infrastructure and security requirements; data flows and controls are confirmed for each environment.

Explore sovereign deployment
YOUR
ENVIRONMENT
  • Data boundary
  • Access policy
  • Retention
  • Review

Zero Data Leakage  ·  Zero Token Bills  ·  Total AI Sovereignty

Bring engineering context into view.

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