New playbook: when your own AI model pays. Read

Siemens: 90% of inbound calls handled without a person

Siemens (industrial technology) reported this on 7 Jul 2026 in vendor case with a named customer (source). It belongs to the agents, traceability and evals layer.

What they built

An AI agent on Amazon Connect that replaced the phone menu: callers speak naturally, the agent resolves from the knowledge base or routes to internal teams and partners, reading and writing CRM records.

The result

90% of inbound calls handled autonomously (resolved or correctly routed) without human intervention.

The number covers inbound calls on the Siemens line covered by the deployment (unit; specified in source) is not reported.

“When the AI agent can’t resolve, it routes to the appropriate human agent with full context,” Siemens said.

Guardrails

Human escalation with full conversation context when the agent cannot confidently resolve or route; clear confidence thresholds decide when it resolves versus escalates; every interaction reads from and writes back to the CRM.

The layer: agents, traceability and evals

Each agent has one narrow task, a named owner and an action log.

  • Agents with one narrow job and an identity
  • A trace of every tool call and decision
  • Eval sets that gate every change

Read the guide to agents, traceability and evals.

Playbooks that use this case

More cases on agents, traceability and evals

  • 12,500

    banker hours saved in the first month of operation, July 2026

    Five specialist agents on Amazon Bedrock AgentCore that classify and read payslips and bank statements, run serviceability calculations and verify them against lending policy, then hand the banker a result to review for mortgage and credit-card applications (source).

  • $10M

    EBITDA uplift from two agent systems, Partners Group says

    Two agentic systems built on a cleaned proprietary policy-level dataset: one runs new-client policy processing, the other automates human-intensive policy checking; delivered by a seven-person team with Version 1 (source).

  • 2–3 minutes

    per ocean or air freight quote, down from one to three days

    Hundreds of in-house AI agents embedded across the shipment lifecycle (quoting, orders, appointments, missed-pickup checks) and now ocean and air quoting, ocean booking and customs brokerage, built and run under a lean waste-removal discipline by 450+ in-house engineers and data scientists (source).

We map how your company runs, pick the first processes with your leadership team, and put them on agents.