# Randy Altschuler

Randy Altschuler co-founded Xometry, a manufacturing technology company that connects buyers with manufacturers. After 13 years building the company, Altschuler announced a move to executive chairman as Sanjeev Singh Sahni took over as CEO.

- Profile: https://b2binfluencer.marketing/creators/randy-altschuler/
- LinkedIn: https://www.linkedin.com/in/randyaltschuler
- Topics: artificial-intelligence, leadership, supply-chain
- Based on 13 dated posts, latest 2026-09-23

## Summary

Randy Altschuler is most useful for strategic insight on manufacturing technology, AI supply chain, and advisory fit.

- Best for: Manufacturing technology company seeking board or strategic advisory on AI-enabled supply chain growth.
- Not for: Campaigns buying creator reach, sponsorship, or independent vendor-neutral commentary.
- Check first: Confirm recent LinkedIn audience analytics and documented follower roles for board or advisory brief.

### Takeaways

- Xometry tools are embedded in Siemens industrial software so engineers avoid switching platforms.
- Board appointment connects AI experience to quoting, supplier matching, and procurement.
- Q1 2026 results pair growth figures with manufacturers and engineers behind them.

## Main ideas

- **The supply-chain shift is about buyer expectations, not just technology**: Altschuler argues that manufacturing is changing because customers now refuse a clunky, offline supply chain. They expect a digital, intuitive experience that works on demand across geographies, processes, and disruption—the same standard they already hold elsewhere in their business. The technology matters because it meets that expectation, not as an end in itself.
- **AI claims should be measured by operating data, not announcements**: Rather than framing AI as a product category, Altschuler ties it to specific functions—AI-powered manufacturability, pricing and sourcing intelligence, quoting, supplier matching, agentic procurement—and a platform trained on real-world manufacturing outcomes over 13 years. The test is whether AI shows up in production work, not just in a launch.
- **Distribution works best embedded in tools engineers already use**: Altschuler explains partnerships by the friction they remove and the reach they add. They present the Siemens partnership not as a co-marketing arrangement but as placing Xometry's manufacturability, pricing, and sourcing intelligence directly inside software engineers already run, so nobody has to switch platforms.
- **A marketplace is judged by both sides and by when engineers arrive**: Altschuler presents Xometry as a two-sided community rather than a catalogue. They credit buyers who trust it with critical parts and manufacturers who grow revenue on it for the results, and frame reaching engineers at the earliest stage of design as the compounding effect that keeps the loop turning.
- **Public results are told as a mission story, numbers first**: Altschuler's earnings posts lead with the figures, then turn them into a claim about why the company exists: to provide better access, technology, and tools for buyers and suppliers, the backbone of the economy. They close with renewed day-one energy rather than a forecast.
- **Leadership criteria favor operators, and the founder's own role changed**: Altschuler's governance writing consistently favors hands-on, behavioral qualifications: hardworking, disciplined, relentlessly customer-focused, kind, fair, with a founder mentality and a demonstrated ability to operationalize AI. The posts also record their move from CEO to executive chairman, the choice of a successor from inside the company, and the appointment of a new board member described as a two-time founder.
- **Broadcast appearances are part of the communication method**: Altschuler uses national television to restate the manufacturing and AI argument, adding a post alongside the clip so the reasoning stands on its own. They credit guests and interviewers by name rather than presenting their views as the company's.

## Work to read

- [Handing over the CEO role and explaining what Xometry was built to do](https://www.linkedin.com/posts/randyaltschuler_xometry-activity-7477724825319563264-Kiky)
- [Discussing manufacturing capacity and AI on CNBC’s Mad Money](https://www.linkedin.com/posts/randyaltschuler_xometry-cnbc-madmoney-activity-7473335652290473984-DVjp)
- [Adding an AI founder to the Xometry board](https://www.linkedin.com/posts/randyaltschuler_xometry-appoints-lukas-biewald-to-its-board-activity-7463219439019401217-S2L0)
- [Framing record Q1 2026 results around the manufacturing community](https://www.linkedin.com/posts/randyaltschuler_xometry-thomasforindustry-q1earnings-activity-7458179993207058432-MoEo)
- [Explaining the Siemens partnership and the shift to an on-demand supply chain](https://www.linkedin.com/posts/randyaltschuler_xometry-manufacturing-ai-activity-7463337032724107265-BKdX)

## Brand relationships

- **Xometry** (owned_business)
- **Thomas** (mention)
- **Siemens** (disclosed_partnership)
- **Weights & Biases** (mention)

## Partnerships

Randy Altschuler's posts do not show a creator partnership or sponsorship offer. Across five posts, the only partnership content is Xometry's corporate relationship with Siemens: Xometry's AI-powered manufacturability, pricing, and sourcing tools are embedded in Siemens' industrial software so engineers can work without switching platforms. This company-to-company product integration appears in an earnings-interview context; it is not a format a brand can buy from Altschuler. No terms, deliverables, pricing, exclusivity, or review process are given. The remaining posts cover Xometry's Q1 2026 results, Mad Money and Cheddar appearances, and the appointment of Lukas Biewald to the board; none mentions sponsored content, paid speaking, affiliate arrangements, or an advisory offer. A buyer exploring an advisory or board relationship should treat it as an unadvertised, individually negotiated conversation and raise it directly through Altschuler's LinkedIn profile.

## Alternatives

- Keith Dunnell: A better choice when a company wants an advisor who has built the commercial machinery for a platform vendor’s manufacturing vertical from inside one, rather than someone who has run a two-sided marketplace. Dunnell joined ServiceNow as VP, Global Head of Manufacturing Industry GTM, and describes the job in terms relevant to a company focused on AI, IT/OT convergence, supply chain resilience, and the pressure to connect plant floor performance to enterprise outcomes, with ServiceNow positioned as the AI control tower that orchestrates across the manufacturing value chain. The second post shows the same buyer’s problem from the operator’s side: a controller fails on a CNC machine, gets swapped for a replacement two firmware versions behind with a known exploited flaw, and is caught only six weeks later because the work order and vulnerability list live in different systems. That is a supply chain and asset-management argument, not a product pitch, and a useful starting point for an advisory session. Choose Dunnell over Altschuler when the question is how to join a manufacturer’s operational and security records or build a manufacturing go-to-market motion, and when a large incumbent platform—not a marketplace—is the reference point.
- Peter Koerte: A better choice when the AI-enabled supply chain question is really about hardware and power: where AI capacity gets built, what it runs on, and how a manufacturer keeps production, engineers, and supply chains inside the regions it serves while maintaining a global technology base. Koerte makes that argument publicly, treating digital and energy sovereignty as one conversation and pairing a national-strategy discussion with two new US plants costing more than 200 million dollars in Georgia and Texas that make the electrical equipment AI data centers run on. The second post offers a rarer angle: apprentices in the Amberg factory built an industrial miniature world in the middle of the factory floor, powered and controlled entirely by the relays, safety devices, contactors, and power supplies they manufacture every day. Colleagues who turned out to be model builders joined in. For a company weighing advice on industrial capability, workforce, or where plant investment meets grid demand, that firsthand account of how a factory floor absorbs a project is useful. Choose Koerte over Altschuler when the decision turns on industrial operations, power infrastructure, or regional manufacturing footprint.
- Delphine Clement: A better choice when the AI-enabled supply chain question is narrower than manufacturing and sits inside building operations and asset value. Clement argues that commercial real estate investors who historically assessed assets on location, occupancy, and rental income increasingly have to weigh energy performance: most of a building’s lifecycle cost falls during operations, while rising regulatory expectations, occupier demands, and investor attention are changing the economics. The argument is framed as a decision for buyers, not a sustainability pitch: the conversation is no longer sustainability versus profitability, but how intelligent, efficient buildings deliver both, with digitalization and AI reducing operating costs, improving resilience, and protecting asset value. The second post is a working schedule for MIPIM 2026, including a panel on the economics of energy resilience and making the business case for net-zero assets. It names the co-panelists and organisations involved. Choose Clement over Altschuler when the company’s product affects how buildings perform, or when the advisory question is how operational data changes an asset’s financial case and who inside a large organisation to bring into that conversation.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/