# HHLA Next: an AI product for logistics

> How we built an AI product for comparing heavy terminal machinery from the ground up for the logistics venture builder HHLA Next – MVP in under six months.

Canonical: https://www.waterglass.ai/en/portfolio/hhlanext/
Language: English (Deutsch: https://www.waterglass.ai/de/portfolio/hhlanext.md)
Company: Waterglass FlexCo, Börseplatz 1/3/6, 1010 Vienna, Austria · hi@waterglass.ai

HHLA Next

Kicker: Client

Location: Germany

Sector: Logistics

Website: https://hhla-next.de

Stat: €1.7B

Annual turnover (Group)

A logistics venture builder we partnered with to build one of their new ventures from scratch.

## Summary

- A complete venture built from zero as development partner, finished in under six months
- All of it centred on comparing terminal equipment for sound investment decisions
- Modern AI tooling in the build and AI agents in day-to-day operations
- The agents handle document processing, investment calculations and research

HHLA Next is a venture builder that builds and invests in cutting-edge logistics solutions for the companies that move the world. We came on as their development partner and built one of their new ventures from scratch: a product that compares terminal machinery so operators can make sound investment decisions. The MVP shipped in under six months. Support from AI agents was planned in from the outset, so that the venture can be run independently in its day-to-day operations.

## Overview

HHLA Next builds and invests in new logistics companies. We came in as development partner for one of those ventures and built it from zero. What was built is not only a product but a company whose day-to-day operations can be run with AI agents.

## Context

Terminals face an investment decision that the purchase price cannot answer. Electric terminal equipment costs more to buy than a diesel machine, but it pays off as soon as you compare the total cost of ownership (TCO). That is where the venture came from: it is meant to drive the green transformation in terminal operations and to show that investment decisions in that direction do earn a positive ROI.

## The venture

The product compares terminal equipment and makes investment decisions traceable. Its focus is the evidence that electric equipment pays for itself quickly across its service life and is a sound investment. That speaks to operators who are planning the switch but have to justify it to their own leadership.

## Developed with AI support and built for AI agents

We used modern AI tooling throughout the build. That is why a complete venture could take shape in under six months and still meet modern expectations. More important, though, was the decision to build the venture from the outset so that it can be run with AI agents. The agents handle document processing, investment calculations and research.

That is a structural difference: a company introducing AI after the fact has to change parts of its existing workflows fundamentally. Here the question from day one was which work an agent takes on and which a person does.

## Outcomes

**A venture in under six months.** From zero to a finished product, including an operating model on European infrastructure.

**Run with AI agents.** Document processing, investment calculations and research go through agents rather than people.

**AI in the build and in day-to-day operations.** The same tooling that set the pace during the build carries the company afterwards.

**A positive ROI for the green transformation.** Operators can see how electric terminal equipment performs across its service life instead of judging it on the purchase price.

## Engagement model

We were development partner for the full duration. Product, architecture and delivery sat with us, the entrepreneurial direction with HHLA Next.