Harward Medical School
25 Shattuck Street,
Boston, 02115, MA,
United States
Boston, 02115, MA,
United States
1 617-432-1000
Education
Harward Medical School Technographics
Harward Medical School Technographics, Software Purchases, AI and Digital Transformation Initiatives
Discover the latest software purchases and digital transformation initiatives being undertaken by Harward Medical School and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 12000 Harward Medical School employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Harward Medical School has purchased the following applications: Accruent EMS for Facility Management in 2020, LightlyTrain for AI Frameworks and Libraries in 2023, IBM Netezza Data Warehouse for Data Warehouse in 2011 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Harward Medical School is running and its propensity to invest more and deepen its relationship with Accruent , Lightly , IBM 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 Harward Medical School revenues, which have grown to $856.0 million 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 Harward Medical School 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.
Harward Medical School Tech Stack and Enterprise Applications
Harward Medical School ERP Services and Operations
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Accruent | Legacy | Accruent EMS | Facility Management | ERP Services and Operations | n/a | 2020 | 2020 |
In 2020 Harvard Medical School deployed Accruent EMS as a Facility Management application. Accruent EMS is provisioned through the EMS Cloud web portal at https://hms.emscloudservice.com/web/ and is surfaced on Harvard Medical School's website for facility operations access, supporting an organization of roughly 12,000 employees.
The implementation centers on core Facility Management capabilities including centralized work order management, preventive maintenance scheduling, asset and space inventory, and room reservation workflows. Configuration emphasizes role based access for maintenance technicians, service coordinators, and facilities managers, enabling ticketing, automated PM triggers, and scheduling workflows consistent with enterprise facilities operations.
Operational scope aligns Accruent EMS with facilities operations, space planning, event scheduling, and asset tracking functions within Harvard Medical School, providing a web based intake and scheduling interface for staff. Governance is organized to centralize request intake and workflow orchestration between IT and facilities process owners, using the cloud hosted EMS portal to provide operational visibility and coordination across campus facility teams.
|
Harward Medical School AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Lightly | Legacy | LightlyTrain | AI Frameworks and Libraries | AI Development | n/a | 2023 | 2023 |
In 2023 Harvard Medical School implemented LightlyTrain within its AI Frameworks and Libraries stack to support self-supervised pretraining and distillation workflows for medical imaging research. Researchers at the Boston lab used LightlySSL and DINOv2 workflows to build a 3D CT foundation model for segmentation, improving representation quality and creating a reproducible training pipeline that underpins multiple downstream research projects.
The implementation centered on self-supervised representation learning and pretraining, leveraging LightlyTrain capabilities for pretraining and distillation alongside LightlySSL and DINOv2 model workflows. Configurations emphasized reproducible pipeline construction, experiment tracking, and evaluation loops tailored for volumetric CT segmentation tasks, with standard functional components such as data augmentation, representation extraction, checkpointing, and validation routines to support iterative model development.
Operational scope remained within research groups at Harvard Medical School in Boston, where the training pipeline is reused across multiple projects to accelerate segmentation model development. Governance practices focused on pipeline reproducibility and model version control to support collaborative research and experiment reuse, and the work explicitly improved representation quality while establishing a repeatable foundation model workflow for downstream imaging studies.
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Harward Medical School Analytics and BI
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| IBM | Legacy | IBM Netezza Data Warehouse | Data Warehouse | Analytics and BI | n/a | 2011 | 2012 |
In 2011 Harward Medical School implemented IBM Netezza Data Warehouse as a centralized analytics platform in the Data Warehouse category to consolidate institutional research and administrative data. The deployment established a single persistent data store intended to support reporting use cases and analytic workloads across the institution.
IBM Netezza Data Warehouse was configured to host high performance analytic processing, bulk data ingestion pipelines, and query acceleration for complex cohort and aggregate queries. Typical Data Warehouse functions such as ETL orchestration, dimensional modeling for subject area marts, and BI reporting layers were part of the implementation scope.
The implementation is described as being used on their website and to feed backend reporting systems, indicating the appliance served both public facing analytics pages and internal dashboards. Operational coverage emphasized research informatics and institutional reporting, aligning analytics consumption with academic and administrative business functions.
Governance and process changes focused on data model standardization, centralized ETL scheduling, and role based access controls to separate research datasets from administrative views. Rollout practices centered on staged data mart publication and validation workflows to ensure analytic consistency across departments.
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Harward Medical School ITSM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Application Performance Management | ITSM |
|
2022 | 2022 |
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Harward Medical School IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Data Warehouse Appliance | IaaS |
|
2011 | 2012 |
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Harward Medical School CyberSecurity
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Identity and Access Management (IAM) | CyberSecurity |
|
2022 | 2022 |
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IT Decision Makers and Key Stakeholders at Harward Medical School
| First Name | Last Name | Title | Function | Department | Phone | |
|---|---|---|---|---|---|---|
| No data found | ||||||
Apps Being Evaluated by Harward Medical School Executives
APPS RUN THE WORLD tracks software evaluation trends across 2 million companies worldwide, including buyer insights from Harward Medical School IT executives and key decision makers. As part of ARTW Buyer Intent and technographics insights, these findings provide useful visibility into the Harward Medical School digital transformation priorities and AI adoption trends.
| Date | Company | Status | Vendor | Product | Category | Market |
|---|---|---|---|---|---|---|
| No data found | ||||||
FAQ - APPS RUN THE WORLD Harward Medical School Technographics
Harward Medical School is a Education organization based in United States,
with around 12000 employees and annual revenues of $856.0 million.
Harward Medical School operates a diverse technology stack with applications such as
Accruent EMS, LightlyTrain and IBM Netezza Data Warehouse,
covering areas like Facility Management, AI Frameworks and Libraries and Data Warehouse.
Harward Medical School has invested in cloud applications and AI-driven platforms to optimize efficiency and growth,
collaborating with vendors such as Accruent, Lightly and IBM.
Harward Medical School recently adopted applications including
LightlyTrain in 2023, New Relic APM in 2022 and Okta Identity Cloud in 2022,
highlighting its ongoing modernization strategy.
APPS RUN THE WORLD maintains an up-to-date database of Harward Medical School’s key decision makers and IT executives,
available to Premium subscribers.
Our research team continuously updates Harward Medical School’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 Harward Medical School technographics profile,
including detailed breakdowns by category, vendor, and IT decision makers.