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Stories, papers and videos on engineering intelligence — from our team and the engineers we work with.

Blog · May 07, 2026 · SPREAD Team

Former Stellantis Chief Software Officer Yves Bonnefont Joins SPREAD’s Advisory Board

BERLIN and SAN FRANCISCO, April 29, 2026 – SPREAD AI, the Engineering Intelligence Platform transforming how the world's most complex products are developed and operated, today announced it has raised $30 million in ...

Blog · May 06, 2026 · Paula Polli

Beyond accuracy: Designing AI features engineers can trust

Blog · Apr 29, 2026 · SPREAD Team

SPREAD AI Raises $30M Series B to Propel Software-Defined Defense, Vehicles and Machines from Concept to Mission

Blog · Apr 23, 2026 · SPREAD Team

SPREAD joins the AWS Partner Network and launches on AWS Marketplace to scale Engineering Intelligence

Berlin, Germany – SPREAD, the decision intelligence layer for engineering, today announced that it has joined the Amazon Web Services (AWS) Partner Network (APN) and is now available on AWS Marketplace. Together, these ...

Blog · Mar 31, 2026 · Ricardo Trindade

The case for friction in AI UX: why "Accept all" is the wrong pattern

Publications

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Mar 13, 2026SPREAD Team

Featured

Former Stellantis Chief Software Officer Yves Bonnefont Joins SPREAD’s Advisory Board

Beyond accuracy: Designing AI features engineers can trust

SPREAD AI Raises $30M Series B to Propel Software-Defined Defense, Vehicles and Machines from Concept to Mission

SPREAD joins the AWS Partner Network and launches on AWS Marketplace to scale Engineering Intelligence

The case for friction in AI UX: why "Accept all" is the wrong pattern

Publications

Scaling Industrial AI from Pilots to Value: Target Architecture

Requirements Management in the Age of AI: Turning Past Projects into Tender Intelligence

From AI Hype to Real Impact, How Enterprises Turn Artificial Intelligence into Measurable Business Value

Zero-Surprise Development in the Era of Software-Defined Products

Why Software-Defined Products Broke Engineering Intuition

Unifying icons at scale: lessons from a growing engineering tool

2025: The year SPREAD became a preferred software partner for Industrial AI in Engineering AND BEYOND.

From many shades to one family: the design story behind our colors update

Integrating AI into product workflows: Insights from Future Product Days 2025

Why Speed Will Define Europe's Defense Advantage

CUBE 2025: Engineering’s Next Era Begins with AI-Ready Teams

Inside the Industrial AI Summit 2025: What Europe’s Leaders Agreed Must Happen Next

What is Engineering Intelligence?

SPREAD completes SOC 2 Type II Examination

A product that works isn’t enough: why thoughtful UX defines customer happiness

Engineering Intelligence, Unlocked. The SPREAD AI Platform Explained

The Next Generation of Engineering Intelligence

The Engineering Intelligence Index

The Ontology Shortcut That Costs You Tomorrow: Why Custom Schemas Create New Data Silos

Life at SPREAD: Becoming a Product Manager – How I moved from UX Research to Product, almost over night

Read faster, decide faster: why sentence case delivers clarity in complex engineering software

What is Engineering Intelligence?

One Platform, one experience: Introducing SPREAD’s new sidebar

Closing the Feedback Loop: What Europe Can Learn from China’s Software-Driven Auto Strategy

Digitalization of Complex Systems: Knowledge Graphs and LLMs in Systems Engineering

SPREAD completes SOC 2 Type I Examination

AI in PLM: How Intelligent Product Lifecycle Management (iPLM) Is Transforming Systems Engineering

Industrial AI in Discrete Manufacturing: Unlocking Higher FPY with Engineering Context

Why Software-Defined Vehicle Projects Stall and How Functional Control Restores Confidence

Product Twin Across the Product Lifecycle: Turning Product Data into Operational Decisions

AI in Systems Engineering: Why Most Pilots Fail and What Top OEMs Do Instead

Purpose-built AI for Engineering Excellence

From Reactive Service to Strategic Uptime: Refining Commercial Vehicles Aftermarket for Complexity

The Cost of Complexity: Why Commercial Vehicle R&D Needs Architecture Transparency Now

Managing Requirement Chaos & Variant Complexity With Digital Product Twins

Software-Defined Defense: Engineering Intelligence for Europe’s New Era of Defense

Agentic Engineering Intelligence: Transparency & Efficiency through AI

Agentic Engineering Intelligence: Transparency & Efficiency through AI

SPREAD joins the EU AI Champions Initiative: Shaping the future of Engineering Intelligence in Europe

SPREAD's Technology: How We Build Trusted, Scalable Engineering AI on Product Data and Semantics

Closed-Loop Manufacturing: Can Digital Twins enhance innovation and efficiency in Production?

French National Railways meets SPREAD: How Digital Twins and unified product data redefine rail operations

Joining SPREAD to bring actionable Product Knowledge at engineers’ fingertips

Solve E/E and software errors during R&D up to 9x times faster

Agentic Engineering Intelligence explained

Knowledge Graphs explained: How you turn data into valuable insights

Mastering SDVs: Why innovative CTOs and R&D Teams turn to Agentic Engineering Intelligence

Back to the future: CUBE 2024 Report

Back to the future - Inside CUBE 2024 and Agentic Engineering Intelligence

Practical demonstration: How Agentic Engineering Intelligence (AEI) empowers engineers

CUBE Expert Panel: How we drive AI in Engineering

Agentic Engineering Intelligence (AEI) - The future of engineering

Back to the future: 5 years of Engineering Intelligence - A journey into the future of engineering

How Rheinmetall Air Defence improved change impact analysis - with a Defense Digital Twin

Tech Deep Dive: Federated queries in Dataspaces

How SPREAD Enables Automotive R&D Leaders to Eliminate SOP Delays Maturity Control

Speeding up chip-to-cloud-architecture: Have end-to-end product transparency and efficient change management to be rethought?

Enhancing Engineering Intelligence with AI Agents

How 3D diagnostics unveil efficiency in data-driven troubleshooting[DE]

AI-powered Systems Engineering: our solution explained

See SPREAD Studio in action: How to build an application in a few clicks

CUBE'23 recap: how to master product complexity on a whole new level

Mastering product complexity: how to meet industry standards and customer expectations

How we integrate AI and LLMs to make product data more accessible

John Deere, Rheinmetall, and TU Berlin share their experiences with Systems Engineering to manage product complexity

CARIAD and Renumics on the opportunities of AI applications and LLMs in Manufacturing

Introducing our platform: 4 steps to an end-to-end product journey

How can we demonstrate the added value of replacing blow fuses with semiconductors in a car?

How we use a GraphQL schema as a contract to efficiently build applications

How to break knowledge silos for innovation: Empower engineers through access to product data

How engineers can design more efficient products

Infineon, Stadler, Mercedes-Benz and FAPS in discussion on data transparency

What are the advantages of a data-centric architecture and knowledge graphs?