AI Buyer Insights:

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Michelin, an e2open customer evaluated Oracle Transportation Management

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Michelin, an e2open customer evaluated Oracle Transportation Management

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Lawrence Livermore National Laboratory Data, Technology Stack, and Enterprise Applications
ERP Financial Management
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
SAP Legacy SAP Concur Expense Expense Management ERP Financial Management n/a 2017 2017
AI Development
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
IBM Legacy IBM Power AI Infrastructure AI infrastructure AI Development n/a 2017 2018
In 2017 Lawrence Livermore National Laboratory deployed IBM Power AI Infrastructure as the AI infrastructure foundation for its Sierra system. The Sierra deployment provided high performance compute capacity to support large scale simulations and emerging AI and deep learning workflows used for national security and scientific research in the United States. Sierra combined IBM POWER9 processors with NVIDIA GPUs at the node level, with IBM supplying the POWER9 based infrastructure and collaborating on system software and workload tuning. The IBM Power AI Infrastructure implementation centered on GPU accelerated compute, multi node POWER9 architecture, and software stacks optimized for deep learning workloads and large scale simulation pipelines. IBM worked directly with LLNL on AI and code optimization to tune the software stack for deep learning and simulation performance, this collaboration encompassed system software tuning and application level optimization. Use of the PowerAI distribution is reasonably inferred from the POWER9 and GPU based AI deployment and is noted as an inference rather than an explicit vendor disclosure. Operational scope focused on laboratory research groups running simulation driven science and AI experimentation, supporting national security and scientific research missions across LLNL facilities. Governance emphasized joint engineering between IBM and laboratory HPC teams to align system configuration, application tuning, and workload orchestration for sustained AI infrastructure operations.
AI infrastructure, MLOps Platforms AI Development 2025 2025
Analytics and BI
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
MicroStrategy Legacy MicroStrategy ONE Analytics Analytics and BI Analytics and BI n/a 2012 2018
Collaboration
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Audio Video and Web Conferencing Collaboration 2020 2020
Content Management
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Digital Signing Content Management 2021 2021
ITSM
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Application Performance Management ITSM 2021 2021
PLM and Engineering
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
3D Modeling PLM and Engineering 2004 2009
PPM
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Project Portfolio Management PPM 2019 2019
Project Portfolio Management PPM 2017 2017
Project Portfolio Management PPM 2017 2017
PaaS
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Test Automation Platform PaaS 2008 2009
IaaS
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Cloud Storage IaaS 2019 2020
Content Delivery Network IaaS 2019 2019
Database Management, Open-Source Database IaaS 2024 2024
IT Decision Makers and Key Stakeholders at Lawrence Livermore National Laboratory
First Name Last Name Title Function Department Email Phone
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Apps Being Evaluated by Lawrence Livermore National Laboratory Executives
Date Company Status Vendor Product Category Market
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FAQ - APPS RUN THE WORLD Lawrence Livermore National Laboratory Technographics

Lawrence Livermore National Laboratory is a Government organization based in United States, with around 9563 employees and annual revenues of $3.25 billion.

Lawrence Livermore National Laboratory operates a diverse technology stack with applications such as SAP Concur Expense, IBM Power AI Infrastructure and MicroStrategy ONE Analytics, covering areas like Expense Management, AI infrastructure and Analytics and BI.

Lawrence Livermore National Laboratory has invested in cloud applications and AI-driven platforms to optimize efficiency and growth, collaborating with vendors such as SAP, IBM and MicroStrategy.

Lawrence Livermore National Laboratory recently adopted applications including Antrophic Claude in 2025, Elasticsearch in 2024 and DocuSign eSignature in 2021, highlighting its ongoing modernization strategy.

APPS RUN THE WORLD maintains an up-to-date database of Lawrence Livermore National Laboratory’s key decision makers and IT executives, available to Premium subscribers.

Our research team continuously updates Lawrence Livermore National Laboratory’s profile with verified software purchases, vendor relationships, and digital initiatives identified from public and proprietary sources.

Subscribe to APPS RUN THE WORLD to access the complete Lawrence Livermore National Laboratory technographics profile, including detailed breakdowns by category, vendor, and IT decision makers.