Yacine Coco
Founder
Sessions (3)
Sessions featuring Yacine Coco at Bits & Pretzels 2026 | Founders Festival in Munich
Welcome: CIO meet Founders
The core message of this short welcome segment is that the upcoming program is designed to connect CIOs with startups, specifically by creating a setting where both groups can meet around AI-focused industrial innovation. The hosts reopen the collaboration stage after a break, welcome the audience back to the second part of the summit, and quickly frame what is about to happen: three startups will pitch first, followed by a look into startup programs run by three corporates. The value proposition stated in the session is narrow and direct: the format is “built to bring the CIOs together with the startups.” The session begins with brief check-ins and repeated welcomes, setting a positive but informal tone. The hosts refer to the “Bits and Bredsratieabbau AI summit” and the “collaboration stage,” then explain the structure of the immediate next block. The first substantive agenda item is that “the three hottest startups” will pitch. The transcript does not provide the names of those startups, their products, their industries beyond the later phrase “AI industrial startups,” or any detail on what they will present. It only establishes that startup pitches are next in the sequence. Before starting, the hosts pause for logistics. They ask for the QR code and remind attendees that, if they have not registered for “Oktoberfest, the CIO summit,” they can still do so because some spots remain available. This is the only concrete audience action requested during the welcome. After that reminder, the hosts confirm they are ready to begin and return to the purpose of the session: building a bridge between CIOs and startups. They also acknowledge that more people may still be arriving, but decide not to delay the program. The segment concludes by kicking off the next portion with “three great AI industrial startups.” No claims are made about the startups’ performance, technologies, funding, customers, or future impact. The welcome functions as a concise transition into a startup-focused program block, combining stage-setting, registration logistics, and a clear articulation of the intended audience connection: CIOs on one side, startups on the other, and the session positioned as a bridge between those two worlds.
This is how Europe´s top AI Scale-ups win Enterprise: Certivity, Blockbrain, Allsides.
The session’s core message was that European AI scale-ups are winning enterprise customers by solving highly specific operational problems with infrastructure-grade products: ALLSIDES focuses on physically grounded 3D data for physical AI and world models, while Blockbrain focuses on sovereign enterprise AI agents that turn company knowledge into scalable workflows. The available transcript opens with Franz Tschimben presenting ALLSIDES from Brixen, Italy, as a computer vision, machine learning, and computer graphics company building “three d infrastructure” for markets where AI must understand physical objects rather than merely generate plausible images or text. ALLSIDES’ value proposition is mass production of high-quality 3D data for real-world objects such as tools, toys, household items, fruits, industrial parts, sporting goods, and consumer products. Tschimben emphasized that its scanner can convert an object into a high-quality, physically grounded 3D model in about five minutes, capturing not only visual geometry but also properties such as measured materials, mass, friction coefficients, colliders, and eventually physics. He positioned this as critical for content creation, physical AI, world models, and generative 3D. In product imagery, AI may hallucinate environments or people, but enterprise customers such as Adidas and Nike need the product itself to remain high fidelity and measured. The company said it is already in full rollouts with customers, has around 50 people across Italy and New York, and works with research partners including NVIDIA, the Technical University of Munich, and Heidelberg University. The ALLSIDES pitch then moved from asset capture into simulation and robot training. Tschimben explained the “real to sim, sim to real” pipeline and the sim-to-real gap: robotics demos often work in simulation but crack in reality. ALLSIDES aims to reduce that gap by producing scarce physical 3D data that cannot simply be scraped from the internet in the way language, image, or video data often can. The company described a 3D data factory in Bressanone scanning sixteen hours a day, six days a week, and announced a San Francisco “real to sim to real factory” with NVIDIA, Industrial Next, and academic partners, using scanners and robots to demonstrate assembly use cases such as server racks and car parts. Blockbrain followed with Antonius “Tony” Gress positioning the company as a sovereign enterprise AI platform built from Baden-Württemberg for Europe. He argued that Europe’s remaining controllable competitive lever is expert knowledge, especially as Germany faces high energy costs, high labor costs, bureaucracy, taxes, and demographic pressure. Blockbrain’s “brain” turns knowledge hidden in data silos and experts’ heads into institutional memory, connecting to systems such as CRM, SAP, PLM, Google, and Microsoft suites. Its “block” side provides Lego-like building blocks for company GPTs, bots, agents, workflows, always-on agents, and apps. Gress stressed sovereign deployment options, including European servers, European infrastructure, open-source weight models, on-premise and air-gapped deployments, and a close partnership with Schwarz Group’s IT cloud. The provided transcript ends during Blockbrain’s platform architecture discussion and does not include substantive Certivity content.
Anthropic, Siemens and SAP: Don't miss THE 3 top curated start-up collaboration programs.
The core message of the provided transcript is that startups can get far more value from corporate collaboration programs when they approach them with a specific goal, a clear understanding of the corporate’s business units and customers, and a technology-focused explanation rather than a buzzword-heavy pitch. Danijel Grabovac opened the Siemens segment by acknowledging that startup events often do not want “corporate” talk, then framed his presentation as a practical, “no bullshit” guide to working with corporates. He distinguished between venture capital, venture clienting and venture partnering: corporates may invest, buy startup solutions as first or early customers, or help startups sell jointly to the corporate’s own customer base. His central point was that knowing which of these paths a startup wants changes the entire conversation and helps the corporate route the startup to the right “happy home.” Siemens illustrated this with concrete examples. Tendet had developed GPS-like location devices for offshore safety, but Siemens identified a rail-track safety use case where workers could avoid physical barriers while receiving warnings if they moved even a centimeter too far; if they remained in a dangerous zone, the train would not receive a green signal. Grabovac used this to argue that founders should describe their technological know-how rather than default to fashionable terms like “AI agents,” because a corporate may discover a different product-market-fit path than the startup originally imagined. He then described Siemens for Startups as a funnel for finding the “needle in the haystack,” whether startups approach at events or via siemens.com/startup, and warned against sending generic investor decks when the actual goal is commercial collaboration. The Siemens section also highlighted the value of discounted or free access to enterprise-grade tools for venture-backed startups. Grabovac cited JetZero, which Siemens supported early with software licenses and attention, as an example of how aerospace startups can access tools once reserved for incumbents. He connected this to digital twin design, explaining how factories, planes and processes can be modeled before construction. The final Siemens example was Rechu, which scanned an existing factory with a backpack, returned point-cloud segmentation within two days, and enabled import into a digital twin. The speaker concluded that the stronger business case often lies not in merely selling to Siemens, but in building on Siemens technology and selling together to Siemens customers. The transcript then transitions to SAP. The host introduces Jan Gutknecht as a bridge between a large corporate and the startup world, and Gutknecht begins by connecting SAP for Startups to the idea that enterprise solutions should be ready for startups. He outlines three collaboration pillars and starts with strategic investments and acquisitions, mentioning recent investments and acquisitions such as WalkMe and Signavio before the supplied transcript cuts off. Anthropic is named in the session introduction as one of the three programs, but no substantive Anthropic segment is included in the provided transcript.