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Siemens and Salesforce Deepen AI Partnership to Redefine Industrial Sales and Service

Salesforce and Siemens are extending their AI collaboration to embed engineering data and autonomous agents into industrial sales, service, and partner onboarding.

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Siemens’ Teamcenter will work with Agentforce to bring engineering-grade answers directly into sales, service, and customer workflows.

Agentforce qualifies every inbound lead for Siemens’ 18,000 sellers, converting inbound interest into productive sales conversations and revenue growth.

SAN FRANCISCO--(BUSINESS WIRE)-- Today at Dreamforce, Salesforce (NYSE: CRM), the #1 AI CRM, and Siemens (SIEGY), a leading technology company focused on industry, infrastructure, mobility, and healthcare, announced a new chapter in their partnership: by combining Agentforce with Siemens’ Teamcenter Service Lifecycle Management (SLM), Siemens and Salesforce are helping industrial companies become agentic enterprises at scale — putting engineering-grade answers directly into sales, service, and customer workflows.

Agent-to-agent AI is transforming industrial service

The result is a new level of industrial intelligence in the front office. Questions that once had to go back to engineering can now be answered in seconds, directly in the customer workflow. A service technician can identify the right spare parts for a specific serial number before the first site visit. A sales representative can quote only those upgrades that are technically valid and manufacturable. And a customer can find and order the right part without waiting for an engineer or calling a hotline.

"Siemens and Salesforce are showing what it means to become an agentic enterprise at industrial scale,” said Marc Benioff, Chair and CEO of Salesforce. "We’re bringing the best of our technology, expertise, and industry knowledge together to reinvent how work gets done and how customers are served. This is a blueprint for the AI era: deep collaboration that goes beyond connecting technology to accelerate transformation, unlock new growth, and create entirely new value for customers."

“For decades, the expert knowledge of the engineer has been separate from the person servicing the machine in the field. We are closing an important gap," said Roland Busch, President and CEO of Siemens AG. "By embedding our digital twin into the commercial workflow, we are putting a virtual engineer in the hands of service technicians and salespersons. Siemens brings industrial AI, Salesforce enterprise AI. Together, they create a critical building block for an industrial AI operating system that connects engineering, operations and business.”

For manufacturers, the impact of this agent-to-agent connection is immediate and transformative.

The ability to compress processes from weeks to hours unlocks faster service, more reliable quoting, and new opportunities to grow aftermarket revenue – a business that grows around six times faster and carries roughly four times the margin of new equipment sales, according to industry analysis. By connecting product truth with customer context, Siemens and Salesforce help manufacturers move beyond one-time equipment sales toward deeper customer relationships, and lay the foundation for predictive, performance-based service models.

From thousands of unqualified leads to total engagement

Siemens has also deployed Agentforce, modernizing its inbound sales development with AI agents. This gives customers greater flexibility in how they buy through AIforce, a trusted enterprise AI harness that brings the whole of Salesforce — the data, workflows, business logic, actions, and governance — into every agentic interface.

Siemens received over 2,500 unqualified leads a month and had no way of knowing which ones were worth sellers’ time; it turned to Agentforce to convert more inbound interest into productive sales conversations at scale for 18,000 sellers. The leads flow into Sales Cloud, where they are engaged, assessed, and routed by two AI agents working in tandem: an engagement agent and a qualification agent. The engagement agent reaches out to incoming leads and moves interested prospects to the qualification agent, which vets each one before handing off the strongest opportunities to the appropriate seller.

The engagement agent uses CRM data to personalize email outreach, and each email contains a secure public key that identifies the lead without exposing their internal record ID. When the prospect follows the qualification link, that key lets the qualification agent retrieve their sales record, confirm or add information, and save details like budget and timeline needs as the conversation progresses. Today, Siemens engages 100% of these inbound leads across 132 countries.

Streamlining partner onboarding

Siemens’ global partner ecosystem faces a common bottleneck: Prospective distributors search the company’s site, fill out an intake form, and wait for further outreach. Looking ahead, Piper, an AI SDR agent, will eliminate that wait, building a personalized pitch on the spot and booking qualified partners directly with a partner account manager.

Once a partner signs on, an employee will hand off a new supplier to Slackbot, which will orchestrate onboarding behind the scenes — running certification, financial, and risk checks and surfacing decisions in Slack — while Agentforce Operations, powered by Regrello, will handle the final onboarding steps in SAP, no human clicks required. The result: supplier onboarding will be orchestrated end-to-end, simplifying the process from weeks to days.

About Salesforce

Salesforce helps organizations of any size become agentic enterprises — integrating humans, agents, apps, and data on a trusted, unified platform to unlock unprecedented growth and innovation. Visit www.salesforce.com for more information.

PR Contact:
pr@salesforce.com

Source: Salesforce

Key Terms

service lifecycle management technical
Service lifecycle management is the set of processes and systems a company uses to design, deliver, support, update and eventually retire a service offering. It covers everything from initial concept and pricing to customer onboarding, ongoing maintenance, performance measurement and decommissioning, and helps coordinate people, technology and costs across stages. For investors, it matters because how well a firm manages a service’s lifecycle affects revenue consistency, customer retention and the cost of operations—much like how regular maintenance and upgrades affect a car’s long-term value.
digital twin technical
A digital twin is a live virtual replica of a physical asset, process, or system that mirrors real-world behavior using data and models so users can test changes, predict problems, and measure performance without touching the real thing. For investors, digital twins matter because they can lower maintenance costs, speed product development, improve uptime and reliability, and make future cash flows and risks easier to forecast — like using a flight simulator to safely train and tune a real airplane.
public key technical
A public key is one half of a cryptographic key pair used to encrypt data and verify digital signatures; it is shared openly while a matching private key is kept secret. For investors, public keys enable secure, tamper-evident transactions and identity checks—like a lock on a mailbox that anyone can drop mail into but only the key holder can open—so they help confirm authenticity and protect assets in digital finance systems.

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