Cognyx

Deon and I are thrilled to announce that Cognyx just closed a 1.7m€ Pre-Seed to help manufacturers design hardware at software speed! The round is led by Bpifrance's VC team Digital Ventures, and features some of the most prominent business angels of the French & German startup scenes. “Hardware is hard”? Let's make it easier and faster to engineer. Our journey started only 8 months ago, when we decided to join forces with OSS Ventures. Using the studio’s robust co-design methodology, we uncovered a massive opportunity in the manufacturing space: engineering R&D cycles are often very slow, mostly because technical and product data lies disseminated across siloed IT systems. Engineers and stakeholders spend weeks identifying dependencies and solving conflicts between design, manufacturing or supply constraints. In particular, the industry’s most central R&D deliverable, the BOM (Bill of Materials) and its many variants, takes forever to align over several departments and scattered data sets. What first sounds like a technical problem actually has a direct impact to a manufacturing company’s core competitiveness: it slows down innovation cycles, extends Time to Market, makes it really hard to optimize products for a set of conflicting constraints, and eventually leads to serious quality issues on the production line. The problem sizes in dozens of millions for most large manufacturers. Cognyx intends to fix this, leveraging the latest available technologies. Using knowledge graphs, the data layer we built already bridges the gap between historical manufacturing softwares (ERP, PLM, MES…). All engineers and stakeholders can now contribute in real time on a unique "super-BOM", solving technical conflicts in real-time. The resulting acceleration of engineering workflows is already massive and… we’re only getting started with #AI! (stay tuned :) We’re incredibly excited by what lies ahead of us, and very grateful to a whole crowd of people for believing in our vision from the very early days! First and foremost our OSS team : Renan, Léopold, Quentin, Jean-Philippe, Guillaume, Elise, Ashok, Pierre, Aurore, Alexandre, Maroussia... many of whom are also angels. My friends, your support was been nothing short of outstanding to get this company off the ground. Then, a very special thanks to our early Design Partners and early-adopter clients (more on this soon ;). And last but not least, to our investors Quentin Mayolle & Ugo Varrasso and to our incredible team of Tech B.A.'s, just to name a few: Roxanne Varza, Christophe Raynaud, Thibault Renouf, Simon Dawlat, Ning Li... Manufacturing experts such as Arno Zinke, Laurent Fiard... not forgetting Laurent, Tom, Jaume and many other members of the Bonial France mafia. Now let’s get to work and build the future of hardware engineering! 📝 Merci à Adrien Lelièvre, Les Echos https://lnkd.in/epxPfmv7

Here's a hard truth: Hardware innovation is in a bit of a chaos. Our co-founder Renan explains why: From our discussions with 100+ companies, a staggering 80% expressed difficulty in their engineering processes. Even more eye-opening? 99% felt that refining their product data architecture could lead to monumental gains in efficiency. Can you believe that a leading car manufacturer sometimes prefers public databases to access their own product data? Or that a top 5 automotive supplier confessed that their current Bill of Materials (BOM) system feels more artisanal than industrial? And forget implementing AI with their current data structure – it's nearly impossible! But, here’s the silver lining 🌟: Companies that manage their technical data well have seen incredible boosts in their engineering processes. Case in point: Tesla managed to slash their time-to-market by ⅔! The US army reduced a 60-hour data-loading task to just 7-8 hours. And Schleich innovated with automated product compliance, connecting product data seamlessly. Our experiences from stints at Google, Tesla, and spearheading 15 industrial startups made one thing crystal clear: The secret lies in optimizing data with tools like the knowledge graph. With all this in mind, we’re thrilled to introduce Cognyx! Our mission? Empowering European businesses to experience Tesla-level results without the need to onboard hundreds of data scientists or overhauling their tech platforms. Get in touch by DM or through our website to get a free audit of your technical data landscape!

Hey you, COMEX member of an automotive manufacturing company 👋🏼 How are you going to achieve electrification without good product data? Automotive electrification isn’t just another buzzword. It’s the imminent future, it’s the industry's key to survival in an environmentally-conscious world. Yet, as massive as this shift seems, the cold reality is not all players will thrive. Many might even stumble and lose their market position. Why? The challenge isn’t only about replacing combustion engines with electric motors. It’s about redesigning entire ecosystems, adapting to new regulations, managing evolving supply chains, and more. It’s a colossal undertaking, touching every facet of operations. But here’s the thing: the companies that can synchronize their product design with manufacturing, that can seamlessly integrate R&D with production, are the ones who'll come out on top. Some, like Tesla, manage design and industrialise products much faster. But what’s their secret? It’s not just about having a visionary at the helm, nor is it just about financial muscle. They built an efficient product data platform. This seemingly unassuming technology has given them unparalleled insights and unprecedented speed. It’s bridging the traditional silos of engineering and manufacturing. Here’s what such a platform achieves: 🔍 Clarity in Complexity: Automotive product development isn’t linear. From initial designs to the assembly line, multiple changes occur. A unified platform tracks these, ensuring everyone is on the same page. 🛻 Rapid Prototyping: In the electric transition, time is of the essence. Efficient data management means quicker prototyping, testing, and iterating. 🔗 Optimized Supply Chains: Electrification demands new components, new suppliers. A solid product data platform ensures supply chains are agile, responsive, and resilient. If this feels daunting, here’s the good news. Companies no longer have to build such platforms from scratch, reinventing the wheel. Cognyx offers a solution. It’s not just a tool, it’s a game-changer, especially crafted for the challenges of electrification. In just 8 to 12 weeks, Cognyx can empower manufacturers with the same capabilities that industry leaders boast. The transition to electrification is a mountainous task. But with the right tech partner, the climb becomes surmountable. The future of automotive is electric, and how swiftly and efficiently companies transition will define their market position in the decades to come. Tools like Cognyx can be the difference between leading the race and playing catch-up. Let's implement together better, faster engineering. 🚀

What a pleasure to be the brand new startup of OSS Ventures! During 100+ conversations, manufacturers have told us that AI projects are really hard to implement... And indeed it is very hard to perform AI/ML projects when the data structure is not the right one. This is all the more salient for projects that encompass several parts of the value chain. For example Engineering, Manufacturing, and Supply where legacy systems (PLMs, CADs or ERPs) usually don’t talk to each other. And at the centre of this issue is the way product data is built and understood in organisations. The so called Bill of Material (BOM) does not share the same properties across different departments and hence systems, which lead to fundamental business issues, mainly 3: ⌛ Time-to-market: the engineering process is slowed down and hence hinders companies’ ability to have the right timing when launching a new product. Follows a loss in market share and an increase in development cost 🚗 Portfolio management and product synergies: companies don’t have enough information to manage base-components and relationships and hence miss profit opportunities for modularisation and re-design. We see huge potential for reduced parts cost and re-sequencing of the product portfolio to better serve client needs 👩⚖️ Compliance: data on products and parts simply are lacking because of the current data structure, which makes it almost impossible to prove compliance across the value chain Verbatims are as such: “We can not grow our industrial activities with the current BOM. We do artisanal work, not industrial. ” (Top 5 world automotive supplier) “ We don’t know the BOM prices, the variation and how to react appropriately.” (Electronics manufacturer) “BOM are everywhere, nothing is up-to-date, lots of mistakes are made.” (Aeronautics Tier 1 supplier) So we built a team of Graph and AI expoerts to eventually come up with THE solution to provide better and faster engineering to manufacturers. We did Cognyx. I'll stop here for now but contact us in DM if you want to find out more! Follow us at Cognyx to follow our adventures 🚀