Eggenstein-Leopoldshafen, 76344,
Germany
Karlsruher Institut für Technologie (KIT) Technographics
Karlsruher Institut für Technologie (KIT) Technographics, Software Purchases, AI and Digital Transformation Initiatives
Discover the latest software purchases and digital transformation initiatives being undertaken by Karlsruher Institut für Technologie (KIT) and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 9783 Karlsruher Institut für Technologie (KIT) employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Karlsruher Institut für Technologie (KIT) has purchased the following applications: d.vinci Applicant Management for Applicant Tracking System in 2018, AutoGPT for Generative AI Platforms in 2024, AIMMS Prescriptive Analytics Platform for Analytics and BI in 2012 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Karlsruher Institut für Technologie (KIT) is running and its propensity to invest more and deepen its relationship with d.vinci HR-Systems , AutoGPT , AIMMS or identify new suppliers as part of their overall Digital and IT transformation projects to stay competitive, fend off threats from disruptive forces, or comply with internal mandates to improve overall enterprise efficiency.
We have been analyzing Karlsruher Institut für Technologie (KIT) revenues, which have grown to $1.17 billion in 2024, plus its IT budget and roadmap, cloud software purchases, aggregating massive amounts of data points that form the basis of our forecast assumptions for Karlsruher Institut für Technologie (KIT) intention to invest in emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database or in cloud-based ERP, HCM, CRM, EPM, Procurement or Treasury applications.
Karlsruher Institut für Technologie (KIT) Tech Stack and Enterprise Applications
HCM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| d.vinci HR-Systems | Legacy | d.vinci Applicant Management | Applicant Tracking System | HCM | n/a | 2018 | 2018 |
In 2018, Karlsruher Institut für Technologie implemented d.vinci Applicant Management as its Applicant Tracking System. The d.vinci Applicant Management instance is surfaced on KIT's public careers site using the dvinci subdomain to host job postings and the online application form.
The implementation centralizes job posting management, online application intake, candidate profile storage, and workflow orchestration for HR and hiring managers, with role based access controls and configurable approval routing aligned to KIT recruitment processes. Operational coverage includes KIT human resources and the institute's hiring units, and the application captures candidate submissions directly through the d.vinci Applicant Management career portal.
|
AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| AutoGPT | Legacy | AutoGPT | Generative AI Platforms | AI Development | n/a | 2024 | 2024 |
In 2024, Karlsruher Institut für Technologie (KIT) implemented AutoGPT as the foundation for AutoGPT+P, an affordance-based task planning extension, in a robotics research deployment in Germany. The project positioned AutoGPT within the Generative AI Platforms category to target robotics planning tasks and to benchmark LLM-based planners under controlled experimental conditions.
AutoGPT+P extended AutoGPT with affordance modeling and a task planning loop tailored for robotic action sequencing, implementing affordance-driven action selection, multi-step task decomposition, and iterative replanning to increase robustness in execution. These functional capabilities reflect common Generative AI Platforms workflows that orchestrate LLM output for structured decision making and control-oriented plan generation.
The deployment and evaluation were research-focused and executed in robotics contexts in Germany, with experiments benchmarked against prior LLM-based planners. KIT researchers published experimental code and the dataset to enable reproducibility, and reported higher task success rates on the benchmark, for example 98% versus 81%.
Governance and rollout emphasized reproducible research practices rather than enterprise production operations, with dataset release and evaluation methodology intended to permit verification by other research groups. The work demonstrates AutoGPT and the AutoGPT+P extension applied within Generative AI Platforms for robotics research, showing improved planning success and robustness compared with prior LLM-based planners.
|
Analytics and BI
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| AIMMS | Legacy | AIMMS Prescriptive Analytics Platform | Analytics and BI | Analytics and BI | n/a | 2012 | 2012 |
In 2012, Karlsruher Institut für Technologie implemented AIMMS Prescriptive Analytics Platform as an Analytics and BI initiative to develop a production planning tool for its manufacturing sites. The implementation objective was to deliver optimal production schedules with explicit production smoothing aligned to principles described by the Toyota Production System, targeting operational planning and production control functions.
Development and configuration centered on linear programming model creation inside the AIMMS Prescriptive Analytics Platform, capturing capacity constraints, sequencing rules, inventory buffers, and smoothing objectives. The deployment included model formulation, solver orchestration, scenario generation, and automated schedule generation capabilities to translate optimization outputs into executable production plans.
The planning tool was operated by production planning and operations teams across production facilities, embedding AIMMS Prescriptive Analytics Platform outputs into routine planning workflows. Governance focused on model version control and constraint input management by planning engineers, and the system produced optimal production schedules including the specified production smoothing behavior.
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Collaboration
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Audio Video and Web Conferencing | Collaboration |
|
2020 | 2020 |
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Content Management
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Web Content Management | Content Management |
|
2009 | 2009 |
|
CRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
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|
|
Customer Experience | CRM |
|
2019 | 2019 |
|
ITSM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
IT Service Management | ITSM |
|
2022 | 2022 |
|
PLM and Engineering
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Geographic Information System | PLM and Engineering |
|
2010 | 2010 |
|
IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Servers, Storage and Networking | IaaS |
|
2016 | 2016 |
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IT Decision Makers and Key Stakeholders at Karlsruher Institut für Technologie (KIT)
| First Name | Last Name | Title | Function | Department | Phone | |
|---|---|---|---|---|---|---|
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Apps Being Evaluated by Karlsruher Institut für Technologie (KIT) Executives
| Date | Company | Status | Vendor | Product | Category | Market |
|---|---|---|---|---|---|---|
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