About nexwise

Why nexwise exists

Whoever sells industrial components rarely sells just a product. What they sell is the certainty that it will work in the application: that the pressure sensor withstands the process temperature, that the tap changer fits the existing transformer, and that the spare part actually replaces the discontinued type. In most companies, that certainty comes from a handful of people in application engineering, inside sales and product management. Their time grows neither with the portfolio nor with the markets or the number of inquiries.

So coverage gets prioritized, usually without anyone explicitly deciding it:

• Strategic customers and large projects get the experts, while the volume business waits.
• Escalations from existing customers come first, while new inquiries without obvious potential are left waiting.
• Core products receive active consultation, while the rest of the portfolio rarely gets sold, even where it would fit.

Each of these decisions is sound on its own. Taken together, they cost revenue that never shows up as a loss in any report: quotes that fail on response time rather than on the product, prospects who don't come back after their first technical question, and a portfolio whose breadth is never reflected in revenue. For the experts themselves, it means an inbox full of questions they have answered many times before, while the requests that truly need their judgment are left waiting.

At the same time, the way customers search is changing. Engineers and buyers increasingly put their questions to AI assistants, with every parameter of their application. Answering them takes product knowledge that is machine-readable down to the individual configuration.

Hiring more experts only goes so far, because their knowledge takes years to build. That is why nexwise exists: we make this knowledge available in every channel where a question arises, with customers, within your own team or with partners, and feed it directly into processes such as quoting and order processing. This lets a company serve its entire market, while its experts keep their time for the cases that genuinely need them.

What nexwise does

nexus: the AI-native semantic product data layer

nexus brings together product data from ERP, PIM, PLM, CMS and document repositories into a Harmonized Product Graph (HPG). The graph captures not only which attributes a product has, but also what it is suited for, what it is compatible with and which product replaces another. This is the knowledge that today lives in the heads of experts. Existing systems remain unchanged.

Guided Selling Agent

In the online shop, product finder or configurator, the Guided Selling Agent asks the questions application engineering would otherwise ask. It captures the application, checks compatibility and approvals, leads to the right variant or configuration and cites the source for every statement. This way, even inquiries that today end with “please call us” on the website can be completed digitally.

Product Expert Agent

The Product Expert Agent answers technical questions for sales, inside sales and service. Typical requests include sizing questions on datasheet values, compliance declarations such as REACH and RoHS, or finding the equivalent to a competitor's product. Because these questions no longer pass through several stations before reaching application engineering or product management, customers receive a reliable answer faster, and more quotes turn into orders.

Commissioning Agent

The Commissioning Agent supports technicians during installation, connection and parameterization. It answers questions about terminal assignments, settings and error codes from operating manuals that often run to several hundred pages, and points to the relevant passage in the document.

Spare Parts Agent

The Spare Parts Agent identifies the right spare part or successor type for an installed component, even when only a type code or a description is available. It takes into account compatibility with the existing installation and discontinued variants.

What makes nexwise different

No migration project

Most manufacturers have invested in ERP, PIM and PLM for years, and these systems remain the systems of record. nexus builds on top of them and starts with the data as it exists today. There is no master data project that has to be completed before value is created.

Suitability, not just attributes

PIM and ERP systems record what a product is: attributes, variants, prices. For a purchase decision, what matters is what it is suited for, such as a specific Ex zone, a temperature range or a standard. nexus models these relationships explicitly.

Precise answers across tens of thousands of variants

In broad portfolios, many variants differ by a single character in the type code, and that very character determines whether a product will work in the application. General-purpose AI assistants and conventional RAG approaches that rely solely on semantic similarity treat such variants as nearly identical. In these portfolios, nexus achieves significantly better results in context precision, context recall, answer relevancy and answer accuracy. For your customers, this means the recommended variant is the one that actually fits. And because every answer cites its source document and version, sales and service can pass it on without further checks.

Data quality improves in operation

When an agent encounters conflicting or missing information, it flags the passage and a responsible expert reviews it. The correction flows back into the source system. Experts resolve a question once instead of answering it again and again, and the master data becomes more complete with every use.

Industry standards from day one

nexus processes ECLASS, ETIM, BMEcat and the Asset Administration Shell, as well as documents in PDF, DOCX, PPTX, XML and JSON. nexwise's infrastructure partners are ISO 27001 certified and host in Europe; development and operations are based in Munich.

Ten weeks to the first agent in production

A Proof of Value is designed for ten weeks and ends with an agent in production on a defined part of the portfolio. The decision on further rollout is therefore based on real inquiries rather than on a presentation.

Who uses nexwise

Industrial product worlds follow their own rules. A manufacturer of measurement, drive or energy technology often carries tens of thousands of variants that differ in material, connection, approval or a single character in the type code. Standards, certificates and regional requirements come on top, and the tolerance for error is low, because a wrongly specified component can bring a customer's plant to a halt. That is why, in the component business, the purchase decision is made as soon as suitability for the application is confirmed, and that confirmation comes from a few experts whose time does not grow with demand. This weighs all the more as manufacturers move into new markets and industries to offset weaker core markets: every new market brings new inquiries, but no additional experts. We built nexwise for these companies:

• Manufacturers of industrial components in measurement, sensing, automation, drive and energy technology with broad, variant-rich portfolios.
• Companies headquartered in Germany, Austria and Switzerland, typically with annual revenue of €250 million to €5 billion.
• Manufacturers that already run an online shop, product finder, configurator or customer portal and want to complete more inquiries digitally.
• Machine and plant builders, for example in machine tools, packaging technology and intralogistics.

nexwise is used by the people who make or carry these trade-offs every day: sales and service leaders who decide where the experts' scarce time goes, and the teams in technical sales, customer service, application engineering and product management where the inquiries land. They are joined by the teams for digital marketing, e-commerce and digital sales, often with sales excellence or sales operations as the initiator.

The team behind nexwise

nexwise was founded in 2024 as a spin-off of the Technical University of Munich. It started with research into data representations that AI agents can actually work with, and the question of where they make the biggest difference. We found the answer in the product data of industrial manufacturers. Mathis knew the problem from his time at Tacto: technical product expertise does not scale and causes high transaction costs, while more and more of the economy depends on industrial hardware.

We spend a large part of our time with customers: in conversations with inside sales and application engineering, in project meetings and at trade fairs. What you read on this page, we learned there, and the product is built the same way.

David Klüners, Co-founder and Managing Director

As CEO, David is responsible for technology and product. Bachelor's in Business Administration (FH Aachen) and Computational Engineering (RWTH Aachen); Master's in Management & Technology (TU Munich). LinkedIn

Mathis Stolz, Co-founder and Managing Director

As CCO, Mathis is responsible for sales and customer relationships. Bachelor's in Economics (Zeppelin University, Friedrichshafen), Master's in Management & Technology (TU Munich), Center for Digital Technology & Management (CDTM), and a research stay at the Center for Collective Intelligence (CCI) at the Massachusetts Institute of Technology (MIT). LinkedIn

The team consists of 8 people in Munich, focused on the core disciplines of software development (data engineering, AI engineering, design engineering).

How nexwise works

We often say: our customers' inbound inquiries write the case study we implement first, and with it determine the first agent. The tickets and emails piling up in inside sales and application engineering today show where an agent will provide the most relief and how success can be measured. A collaboration therefore starts with a conversation about these inquiries and about where the product data lives. We then run a Proof of Value for one agent on a defined part of the portfolio, initially in one region, with success criteria agreed in advance. Once these are met, a license follows, along with a step-by-step rollout to further product areas, regions and use cases.

Customers work directly with the two founders and a dedicated project team. Coordination takes place in regular meetings and via Microsoft Teams. A Proof of Value takes 10 weeks, and we respond to inquiries within 24 hours.

Contact: hello@nexwise.ai or book a meeting.

Key facts

Company name

nexwise GmbH

Type

B2B software company, spin-off of the Technical University of Munich

Founded

2024

Founders

David Klüners, Mathis Stolz

Headquarters

Georgenschwaigstraße 24, 80807 Munich, Germany

Website

www.nexwise.ai

Core offering

nexus, an AI-native semantic product data layer that makes technical product knowledge machine-readable for AI agents, and the agents built on top of it

Pricing

Flexible, transparent, usage-based pricing via nexwise tokens. Entry via a Proof of Concept or Proof of Value with fixed scope, followed by a production license

Contract terms

Minimum term of one year, with either a committed-use budget or pay-per-use, billed quarterly

Services

Agents (Guided Selling Agent, Product Expert Agent, Commissioning Agent, Spare Parts Agent), build and operation of the nexus product graph, integration of ERP, PIM, PLM, CMS and document repositories as well as horizontal systems such as CRM and ERP for workflow orchestration. Proof of Concept (PoC), Proof of Value (PoV), production license

Communication

Direct contact with the founders, Microsoft Teams, email

Notable clients

Reinhausen, WIKA

Customers served

Industrial manufacturers in Germany, Austria and Switzerland

Projects delivered

10+

Competitors

Contentserv, antiloop, Prodlane, encoway, Zoovu, Frontnow, Tendos, Mavenoid, Empolis, Spread, 4PACE

Social

LinkedIn, X

Frequently asked questions