Use Cases

The intelligence layer behind decision-ready companies.

Corporations and mid-sized companies in the DACH region run their intelligence functions with AI employees: watching the outside, linked to their own figures, available across the whole company. From product management in mechanical and plant engineering, through the nightly run at Morningstar, to sales at gastromatic, plus projects we show in anonymised form.

All use cases Book a call

KERNRead the case study

hearthuntingRead the case study

gastromaticRead the case study

LeuphanaRead the case study

MorningstarRead the case study

Leaders of AIRead the case study

Meet our clients.

Corporations and mid-sized companies show which tasks their AI employees handle today. Partly anonymised, every detail carries a source and a date.

Finance Morningstar: portfolio accounts checked against the target allocation, proposals with reasoning. Based on Morningstar data, two AI employees check portfolio accounts against the target allocation, prepare reallocation proposals with reasoning and draft the mandatory documents. From concept to a working prototype in one week for the AI bootcamp in Frankfurt. Read the case study

Machinery and plant engineering Competitors and customers every morning, with source and date. Two AI employees monitor the companies in the customer and competitor portfolio for the business and market intelligence team: prices, product launches, acquisitions, locations. Product management works from a single basis, and every detail can be expanded down to the source. Anonymised.

Software and services gastromatic: every enquiry reaches sales fully prepared. The AI employee for lead intelligence researches target customers such as golf and hotel resorts, enriches contacts in HubSpot and prepares every first conversation. The sales development representatives call prepared rather than searching. Read the case study

M&A advisory KERN Unternehmensnachfolge: invoices, proposals and NDAs from a Teams message. At the Essen location, three AI employees record time entries, create invoices from them, build proposals and draw up non-disclosure agreements. They are operated through Microsoft Teams and by email, and the team keeps working in its familiar tools. Read the case study

Animal nutrition Commodities, regulation and trade flows, put into context instead of merely reported. An AI employee for market intelligence monitors commodity prices, new requirements in the target markets, trade flows and demand signals and puts them into context against your own planning. The result reaches the specialist departments as a weekly newsletter. Anonymised.

Personnel marketing hearthunting: research and first contact for a one-person sales team. Two AI employees research contacts in the target group of haulage and logistics, check for open positions on the career pages and carry out the personalised first contact by email and LinkedIn. Positive replies become agreed first conversations. Read the case study

Networking and professional development · Project Leaders of AI: 60 specialists build five specialised AI teams in one day. Together with Leaders of AI, EY, ThynkAI and Virtual Identity, scoreprise.AI developed a working multi-agent system. At the one-day Leaders Lab in the EY Wave Space on 21 February 2025, 60 specialists built five specialised AI teams from it. Read the case study

Pharma Target practices for the medical field sales team researched and validated. An AI employee for lead intelligence researches and validates medical practices according to the field sales team's criteria, for each sales region in Germany and Austria. Every record carries its signal chain, and the field sales team receives it before the visit. Anonymised.

Higher education and research · Project Leuphana: How human may a chatbot appear? A study with 500 students. Four chatbot variants in a 2x2 design, fast or slow, personal or impersonal. scoreprise.AI provided the technical support for the study by Prof. Dr. Monika Imschloss and Dr. Lennart Seitz; more than 500 students took part. Read the case study

Media and education · Project campus a: Journalistic feedback for Austria's first nationwide school newspaper. A tailor-made chatbot gives 12 to 18 year olds feedback on their texts, for example on a missing opposing view, passive sentences or mixed facts and opinions. Built through joint learning with founder Bernhard Salomon. Read the case study

Finance Fund cockpit with peer positioning on a weekly cycle. An AI employee for institutional asset management sets the key figures of your own funds against the comparison group each week, with a source for every number. The assessment and every decision remain with portfolio management. Example scenario.

Mittelstand Quarterly report from the systems, not from enquiries. An AI employee for OKR management pulls the progress on objectives and metrics from CRM, ERP and project tools, checks with those responsible where details are missing, and compiles the quarterly reporting with the source next to every figure. Management and teams see the same status. Example scenario.

What Intelligence AI employees make possible.

“Any software can do a pure limit and compliance check today. Real AI has to do more: an independent, reasoned assessment where you can tell that there really is intelligence behind it.”

Kathryn Kexun Hengst-Li

Director Business Development, Morningstar

“The more precisely I can tell Carl what to look for, the better the results. For us this was an important step towards working more efficiently with the resources we have. Carl is more than just a tool: he is a genuine colleague who noticeably takes the pressure off the team.”

Christian Fuchs

Head of Sales, gastromatic

“Time recording, invoices, quotes and NDAs run through AI employees in Teams and by email. What used to take whole afternoons is now a single message.”

Dr Peter Slawek

Partner, KERN Unternehmensnachfolge

“We bring the experience from transformation projects in finance, scoreprise.AI brings the AI employees. As partner companies we develop solutions together that hold up in regulated operations and do not end at the pilot stage.”

Ralf Temporale

Country Lead and Managing Director, Projective Group

“They did not approach it in a preaching way, to show off everything they know, but rather approached it in a learning way.”

Bernhard Salomon

Founder, campus a

The approach

From the first conversation to regular operation, in five stages.

The start deliberately stays small · cancellable monthly

Book a call Conducted as a conversation and without a presentation. The aim is to clarify where intelligence work is done by hand today and which case carries the highest priority.

Scoping workshop The first chargeable threshold, together with the technical lead. The result is a completed role profile made up of the target profile, signals, volume estimate and delivery format. The commitment fee is offset against the offer.

Proposal Two to three days later. Built from numbered modules with fixed prices and consecutively numbered features that are referred to throughout the entire term.

Build In two to three groups, each with a verifiable result: first build for one case, validate with the responsible specialist, then scale. Weekly coordination, shared board.

Regular operation Source maintenance, support and model changes, monthly review, quarterly optimisation. Cancellable monthly, the first month is a shared calibration phase.

Next step

Your use case, shown on a comparable case.

Book a call Cancellable monthly · operated in the EU