When AI Meets Sales, Support & Supply Chain: Omnae & Bardin AI

AI is not just changing CAD, BIM, and engineering. It is moving into the messy, high-stakes parts of the industrial back office: pre-sales, support, procurement, supply chain collaboration, quoting, order changes, invoices, and customer communication. In this episode of AI Across the Product Lifecycle, I’m joined by Fay Goldstein, Co-Founder and CEO of Bardin AI, and Scott Lionello, Co-Founder and CPO of Omnae Technologies, for a practical discussion on where industrial AI actually creates value and where it can still break trust. Bardin AI is building an application engineer for industrial automation sales and support teams, helping non-experts answer complex engineering and application questions without escalating everything to senior engineers. Omnae builds supply chain collaboration software designed to work across many companies, including smaller suppliers, while giving AI agents a safe and deterministic environment to operate in. We discuss why industrial AI cannot just be “ChatGPT bolted onto a workflow,” why auditability and trust matter when AI touches contracts, engineering claims, supply chain commitments, or financial systems, and why the best AI use cases may start in the unglamorous parts of the business. Topics include: Why Fay was “nauseatingly bullish” on AI from the beginning Why Scott remains more skeptical when AI touches the general ledger Why industrial AI needs determinism, traceability, and audit paths How AI is changing software development inside startups Why founders can now prototype product ideas much faster How AI changes agile, product management, and engineering team structure Where AI sits inside Bardin and Omnae Why not all AI in industrial software is generative AI Why human-in-the-loop workflows still matter The economics of LLM usage, API keys, and token burn Whether supply chain will ever have its own “OpenAI moment” Why entry-level talent needs AI fluency, not AI fear Why mid-market manufacturers may adopt AI faster than large enterprises Why startups may outperform incumbents in delivering practical industrial AI This conversation is less about AI hype and more about execution: trust, workflows, liability, integration, adoption, and the hard operational details that decide whether AI actually works in industrial companies. Timestamps 00:00 — Intro: switching from CAD/BIM to sales, supply chain, and pre-sales 00:32 — Fay Goldstein introduces Bardin AI 01:16 — Scott Lionello introduces Omnae Technologies 02:26 — First reactions to the OpenAI moment 03:36 — Why AI touching the general ledger requires skepticism 04:01 — Trust, determinism, and industrial AI 05:00 — Auditability, knowledge graphs, and regulated AI decisions 06:25 — The missing “black box” for AI and robotics 07:41 — How AI coding tools changed software development 08:37 — Scott on smaller, faster engineering teams with AI tools 09:34 — Fay on AI enabling non-engineer founders and product prototyping 11:50 — Bardin Flow: internal AI systems for startup operations 13:17 — Is AI changing agile and software craftsmanship? 14:37 — Freedom versus discipline in AI-assisted development 15:37 — Why AI agents need skepticism 16:26 — Where AI sits inside Bardin and Omnae 16:43 — Bardin as an AI-first industrial application 18:12 — Omnae as a “jungle gym” for supply chain AI agents 19:36 — Human-in-the-loop workflows and trust 20:50 — Why accounting personas resist uncontrolled automation 21:22 — From AI distrust to “prove to me it works” 22:18 — The economics of LLM-powered industrial software 23:11 — Usage-based pricing, user-based pricing, and uncertainty 24:17 — Omnae’s approach to API keys, rate limits, and token control 25:17 — Bardin’s long-term infrastructure vision 26:09 — Token-burn culture and AI leaderboards 26:45 — Will supply chain have its own OpenAI moment? 28:21 — Fay on segmented AI moments across industrial workflows 30:31 — Dark-stack AI in procurement and supply chain 32:01 — Lessons from legal, medical, and regulated AI adoption 33:06 — Advice for young professionals entering the AI era 33:40 — Fay: show your AI stack, not just your résumé 34:47 — Scott: people skills, product sense, and initiative matter more 35:35 — Digital maturity in industrial companies 36:19 — Enterprise stacks versus how work actually gets done 37:03 — Why manufacturers may use agents more deeply than expected 39:10 — Can startups move companies faster than incumbents? 39:57 — Fay: the goal is relief, not demo theater 41:04 — Scott: startups can prove value in smaller deployments 41:38 — Why top-down enterprise AI rollouts often fail 43:41 — Where to meet Fay and Scott 44:57 — Sponsor mention and wrap-up Please don't forget to click on this link from our sponsor AWS for access to an exclusive webinar! https://pages.awscloud.com/awsmp-gim-...