# Eytan Sheerit Eytan Sheerit writes about building logistics software that uses AI to automate operational work, from reading shipping documents and coordinating warehouse tasks to generating workflows and handling voice interactions. - Profile: https://b2binfluencer.marketing/creators/eytan-sheerit/ - LinkedIn: https://www.linkedin.com/in/eytansheet - LinkedIn followers: 974 - Topics: artificial-intelligence, supply-chain, workflow-automation - Based on 12 dated posts, latest 2026-09-29 ## Summary Eytan Sheerit is most useful for explaining how AI can automate logistics operations inside established systems. - Best for: Logistics software or supply-chain automation vendors wanting thought-leadership or advisory content on AI operations. - Not for: Consumer fintech or mass-market lifestyle campaigns seeking broad reach or app installs. - Check first: Confirm whether they are a CargoMatrix insider, independent commentator, or paid contributor, and any competitor conflict. ### Takeaways - Add AI to a working logistics platform instead of replacing the platform. - Document intelligence is the base layer the rest of the operation depends on. - A voice agent should connect to systems of record, not just answer questions. ## Main ideas - **Add AI to a working logistics platform; don't swap the platform out**: Sheerit rejects the idea that the company became an AI company overnight. Their position is that integrations, workflows, customers and accumulated operational knowledge form the foundation, with AI adding new capabilities on top. Replacing the platform would throw away what already works, so early generative-AI failures argue for grafting on capability rather than starting over. - **Automation is a decades-long project; AI continues it rather than starting it**: Sheerit describes a continuous mission to remove manual work, connect fragmented systems and help logistics staff make faster decisions. Current AI capabilities build on integration work that predates the generative AI boom; earlier tools such as screen scraping and floor-side mobile devices addressed the same problem of systems that do not talk to each other. - **Document intelligence is the base layer the rest of the operation depends on**: The earliest AI question Sheerit describes is whether a machine could read an airway bill, commercial invoice, packing list or shipping label and turn unstructured logistics documents into structured operational data. The post presents that experiment as the platform's foundation, not a side project. The current order fulfillment flow reads documents before matching, compliance checks or document generation run. - **The enterprise question is shifting from operational efficiency to entering new verticals fast**: Sheerit argues that workflow generation matters most for entering a new market quickly, not for incremental savings in an existing one. The post quotes a CIO describing the standard route for a large enterprise entering a new industry, using coal mining as an example of a business the company already runs end to end. Sheerit's point: describing the operation and generating workflows shifts the conversation from efficiency to how quickly a company can enter a vertical. - **A voice agent should connect to systems of record, not just answer questions**: Sheerit distinguishes a website voice agent that answers questions from an operational agent that helps get work done. The agent starts with a company's approved website content, products and business knowledge. Connections through MCP to CargoMessenger and CargoWise let it retrieve operational context, validate information, create or update tasks, trigger workflows and keep the right team informed. The listed uses are operational, not informational. - **Cargo should move only when the order, documents, physical cargo and required controls agree**: Sheerit builds compliance and exception handling into the order workflow rather than treating them as after-the-fact checks. The company traces this approach to its aerospace origin, where purchase-order matching, traceability and compliance requirements are described as unforgiving. The same flow is presented as configurable for automotive, electronics, pharmaceutical, perishables and medical devices. ## Work to read - [Automation before AI: mainframes, screen scraping and the 1999 warehouse app](https://www.linkedin.com/posts/eytansheet_artificialintelligence-logisticsautomation-activity-7485768371309867008-KV5O) - [Voice AI that does work, not just answer questions](https://www.linkedin.com/posts/eytansheet_voiceai-logisticstechnology-cargowise-activity-7495871094118178816-hx8H) - [Ten years of AI at a logistics software company, including what went wrong](https://www.linkedin.com/posts/eytansheet_ai-logistics-cargomatrix-activity-7500175936064016384-iWx-) - [Order Fulfillment relaunch: from purchase order to delivered shipment](https://www.linkedin.com/posts/eytansheet_cargomatrix-orderfulfillment-warehouseautomation-activity-7505283758225428480-zOC4) - [The CIO conversation: generating operational workflows in minutes](https://www.linkedin.com/posts/eytansheet_cargomatrix-ai-workflowautomation-activity-7510333626212093952-d2lz) ## Brand relationships - **CargoMatrix** (disclosed_partnership) - **CargoWise One** (mention) - **eAdaptor Next** (mention) - **CargoMessenger** (mention) ## Partnerships Eytan Sheerit's five posts cover CargoMatrix product and company communications—document intelligence, order fulfillment, an AI workflow generator, voice agents, and a history of logistics automation—rather than third-party brand work. The posts publish no rate card, media kit, editorial-guidelines page, or partnership inquiry route; the LinkedIn account carrying them is the only public contact route stated. A brand pursuing a collaboration should ask directly about terms, deliverables, disclosure expectations, and the approval process. ## Alternatives - Alain Borri: Choose Alain Borri for a campaign about the business consequences of AI in logistics. In a post on who captures AI-driven productivity gains and an argument about the future of standalone TMS software, Borri frames AI as a question of value capture and market structure, not just automation. - Marcelo Fujimoto: Choose Marcelo Fujimoto for a campaign about international-trade infrastructure and reusable data tools. A post on a free import-duty calculator and API-first trade tools connects a practical tool to a broader product direction. In a separate post on AI and freight brokerage, Fujimoto argues that exception handling—not simply matching freight to capacity—is where logistics value can persist. - Deloris Fisher: Choose Deloris Fisher for a campaign about dependable integration across e-commerce, warehouse, carrier, and billing systems. Fisher's integration post highlights the less-visible engineering work: syncing inventory, handling webhooks and rate limits, and preventing duplicate processing. A second post emphasizes the infrastructure behind high-load logistics platforms. --- AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/