AI. Innovation. Everything in between.

AI agents transform tickets, requirements, and architectural rules into testable specifications. The team prioritizes and approves the specs.

AI agents prepare code changes, tests, and diffs from clearly specified tickets and execute them in isolated environments. Humans approve merges and deployments.

AI reviews pull requests for style, architectural rules, security risks, and missing tests, and suggests fixes. The final decision to merge remains with the team.

AI analyzes code and specifications, creates unit, integration, and regression tests, and integrates them into existing CI pipelines. Developers review coverage and approve the results.

KI-Agenten wandeln Tickets, Anforderungen und Architekturregeln in prüfbare Spezifikationen um. Das Team priorisiert und gibt die Specs frei.

Automated creation, review and individualization of standard documents — lawyers or administrators give final approval.

Employees immediately receive precise answers from manuals, guidelines or databases.

AI agents search documents, combine templates and create initial drafts — the specialist department reviews and finalizes.

Machine learning models recognize recurring patterns in fault reports and initiate measures early on before a network failure occurs.

Data-driven trial design through AI evaluation of preclinical data, population histories or study registers.

AI-supported planned tours taking into account traffic, weather, vehicle data and customer windows.

Optimized feed-in control through AI-based modelling of wind, solar and storage capacities based on weather and real-time data.

Distinctive behavior of individuals can be automatically identified.

Live video surveillance footage can be analyzed in real time to identify predefined “suspicious” behavior. When something is discovered, shop owners are alerted via a connected app.

AI detects violent actions such as hitting, kicking, shooting and stabbing in crowds via drone or camera vision. In this way, clashes or sources of fire are found that emergency services on the ground overlook.

By analyzing public traffic cameras and traffic light data, traffic can be better controlled. Live traffic forecasts and recommendations can be created using data mining, video and image recognition, and other techniques.

A chatbot can answer many questions and help users keep an eye on their finances. From past user behavior, it is also possible to learn which offers specific user groups are particularly appealing to. Individual offers can be created for each customer using robo-advice.

Alexa is not the only one that is smart. With natural language processing, vacuum cleaners, hotlines or industrial devices can be made “smart” and respond to user commands. This is no longer a future scenario, but can be implemented today.

Use neural networks to detect copyright infringement of photos and documents on the Internet.

Data labeling is necessary but time-consuming. With intelligent human-in-the-loop systems such as Labelworld, the labeling of data can be accelerated many times over.

Use videos, images, or robots on the sales floor to check and analyze your shelf space usage. Identify and manage shortages or sub-optimal use of shelf space.