Engineering, accelerated by the data you already have.
40
Proprietary patents
96
Co-owned patents
50⁺
R&D labs, CoEs & innovation studios
EnGeneer
An AI Center of Excellence
Engineering lifecycle
Every engineering program runs on data - requirements, designs, simulations, test results, decades of it locked in PLM, MES, and ERP.
Yet teams still work in manual, disconnected workflows. The investment is made; the payoff is stranded.
We connect that data across the whole development arc - from concept to a proven, producible design - and put AI to work inside it, so engineering moves faster and every program starts smarter than the last.
Baseline your asset data,
systems, and
aftermarket P&L.
Identify the highest-value pillar
to start with.
Engineering lifecycle
Every engineering program runs on data - requirements, designs, simulations, test results, decades of it locked in PLM, MES, and ERP.
Yet teams still work in manual, disconnected workflows. The investment is made; the payoff is stranded.
We connect that data across the whole development arc - from concept to a proven, producible design - and put AI to work inside it, so engineering moves faster and every program starts smarter than the last.
Architect the target state
on the Engineering Intelligence
Platform and Product-to-Service
Digital Thread.
Engineering lifecycle
Every engineering program runs on data - requirements, designs, simulations, test results, decades of it locked in PLM, MES, and ERP.
Yet teams still work in manual, disconnected workflows. The investment is made; the payoff is stranded.
We connect that data across the whole development arc - from concept to a proven, producible design - and put AI to work inside it, so engineering moves faster and every program starts smarter than the last.
Stand up the first connected
use case — usually data intelligence
or predictive maintenance — and
prove the value.
Engineering lifecycle
Every engineering program runs on data - requirements, designs, simulations, test results, decades of it locked in PLM, MES, and ERP.
Yet teams still work in manual, disconnected workflows. The investment is made; the payoff is stranded.
We connect that data across the whole development arc - from concept to a proven, producible design - and put AI to work inside it, so engineering moves faster and every program starts smarter than the last.
Extend the digital thread
across the remaining pillars, sites
and business units.
Why this is changing now?
The systems are in place. The workflows aren’t.
Heavy investment in PLM, MES, and ERP - but the data sits in silos and the work stays manual and disconnected.
Mistakes get more expensive the later you find them.
A flaw caught on the whiteboard costs a conversation; the same flaw at deployment costs a teardown. Connected data moves the catch earlier.
AI changes what “faster” means.
Design reuse, simulation, and validation can now run on your own engineering data - but only once it’s joined up. Connected data is the precondition, not the reward.
What the Engineering Lifecycle covers - The three pillars
The create-and-develop arc - from a blank sheet to a design that’s proven, producible, and ready to enter service. Concept, requirements, architecture and design, build, and verification and validation.
One connected thread, powered by our Engineering Intelligence Platform - the base operating layer beneath every lifecycle - linking requirement to design to test, so nothing already solved gets rebuilt.
PDLC Acceleration
Productivity through MBSE and Digital Twin
Operational Excellence
One discipline, three domains
The engineering lifecycle holds its shape across everything we engineer. One platform, one thread, across the industries we serve.
Products
Full product development, concept to production, chip to cloud.
Plants
Front-end engineering design through detailed engineering.
Networks
Network design through plan, build, and rollout.