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STREIT

Customer storyHybrid Organisation / Customer service

An AI agent in everyday customer service.

MING Labs and STREIT built Tabea to turn incoming order emails into order proposals. She works in STREIT’s customer service team, with people in control.

STREIT colleagues working together in their office
The STREIT team. Photograph: STREIT.

The company

A workplace business.
A working AI colleague.

STREIT is a German provider of office supplies, workplace technology and services. Customer orders arrive by email, carrying information that needs to be understood and matched to the right customer and products.

Working with STREIT, MING Labs built Tabea for this specific role: preparing order proposals and handing unclear cases to the customer service team.

About STREIT ↗

TabeaCustomer service · STREIT

The work

From email to order proposal.

  1. 01

    Incoming orders

    Customers send their orders by email.

  2. 02

    Tabea prepares a proposal

    Reads the email, matches customers and products, and creates an order proposal.

  3. 03

    People handle exceptions

    Unclear cases go to the customer service team. People stay in control.

The reported result

Up to

40–50%

of orders prepared automatically

Reported by STREIT · September 2026

Figures reported by STREIT, not independently verified. The 40–50% figure refers to orders prepared automatically; up to 120 hours is capacity gained per month. The 80% automation rate is a target, not a result already achieved. The source does not specify the measurement period, order volume or capacity calculation. Results depend on the use case.

The result describes order preparation. People retain control and handle cases that need their judgement.

Figures supplied in STREIT’s customer-story material, checked on . STREIT’s original write-up is not yet publicly available.

capacity gained per month
Up to 120 hrs
target automation rate · Future goal
80%Working towards this target

From one role to a Hybrid Organisation

How could this work
in your team?

Explore how tasks, roles and systems come together when an agent joins a team.

Explore the interactive story Talk to MING Labs ↗