Uber
1515 3rd Street,
San Francisco, 94158, CA,
United States
San Francisco, 94158, CA,
United States
1 415-612-8582
Transportation
Uber Technographics
Uber Software Purchases and Digital Transformation Initiatives
Discover the latest software purchases and digital transformation initiatives being undertaken by Uber and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 31100 Uber employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Uber has purchased the following applications: LatentView PRISM for AML, Fraud and Compliance in 2020, Golang for Apps Development in 2015, Baidu Apollo Go for Computer Vision in 2025 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Uber is running and its propensity to invest more and deepen its relationship with LatentView Analytics , Google , Baidu 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 Uber revenues, which have grown to $43.98 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 Uber 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.
Uber Data, Technology Stack, and Enterprise Applications
TRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| LatentView Analytics | Legacy | LatentView PRISM | AML, Fraud and Compliance | TRM | n/a | 2020 | 2021 | In 2020, Uber engaged LatentView Analytics in the United States and public disclosures support an inferred deployment of LatentView PRISM for AML, Fraud and Compliance to address payments and fraud risk associated with ride hailing transactions. The source lists LatentView as a service provider for technology and payments related use cases, and attribution to the LatentView PRISM product is inferred from LatentView's PRISM positioning and the payments focus of the engagement. The implementation scope is described around payments and technology functions, with LatentView PRISM for AML, Fraud and Compliance positioned to support transaction monitoring, anomaly detection, risk scoring, rule orchestration, and alert generation as category aligned capabilities. Configuration would plausibly include a mix of model scoring and rule based detection, pipelines for real time event ingestion and batch reconciliation, and investigator facing case records to enable triage by fraud analysts. Operational coverage is centered on the US region and payments workflows, integrating enriched transaction feeds, settlement records, and rider metadata to improve signal quality and support downstream case management. Governance and operating cadence would be expected to include rule tuning, analyst feedback loops for model refinement, and formal handoffs between engineering, payments operations, and fraud investigation teams, consistent with deployments in the AML, Fraud and Compliance category. |
PaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| Legacy | Golang | Apps Development | PaaS | n/a | 2015 | 2016 | In 2015, Uber adopted Golang across its backend estate, positioning Golang within its Apps Development efforts for high-performance services. The adoption targeted thousands of backend microservices, with emphasis on latency-sensitive service paths and internal platform tooling deployed across Uber's global production fleet. Golang usage at Uber centers on microservice architectures and internal developer tooling, specifically profiling infrastructure and API gateway components. Uber Engineering implemented Go-specific performance workstreams, applying profiling practices and profile-guided optimizations referenced in published posts such as pprof++ and PGO to tune garbage collection and CPU hotspots. Operational coverage includes latency-critical request paths, service mesh ingress points where API gateway components run, and internal profiling utilities used by platform and engineering teams across regions. The implementation model reflects a service-oriented deployment pattern, with Golang services running alongside other runtime types in Uber's production environment and instrumented for CPU and memory profiling. Governance was codified through engineering publications and shared performance tooling, creating repeatable workflows for profiling, optimization, and code-level tuning of Go services. Uber Engineering reported outcomes from these Go-specific optimizations that include reduced CPU usage and improved service latency and resource efficiency in production, reinforcing Golang as a strategic choice for Apps Development of backend services and internal tooling. |
AI-Powered Application
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| Baidu | Legacy | Baidu Apollo Go | Computer Vision | AI-Powered Application | n/a | 2025 | 2025 | In 2025, Uber partnered with Baidu to deploy Baidu Apollo Go as a Computer Vision powered autonomous taxi offering across international markets outside the United States and mainland China. The deployment connects Uber with Baidu's commercially operated Apollo Go fleet, which has been running robotaxi services since 2022 and completed more than 11 million rides by May 2025. The Baidu Apollo Go application brings core Computer Vision capabilities to the joint deployment, including perception driven object detection, sensor fusion for environment modelling, high definition mapping and motion planning modules that support fully driverless operation. These functional modules are central to vehicle autonomy, and are used to enable continuous environment sensing, localization and trajectory generation typical of autonomous mobility systems. Operational integration centers on embedding Baidu Apollo Go vehicles into Uber's ride-hailing platform, aligning vehicle dispatch and booking flows so autonomous vehicles can accept trips via Uber, and provisioning fleet orchestration across targeted cities. The rollout targets markets in Asia and the Middle East with Apollo Go already present in 15 cities including Dubai and Abu Dhabi, and leverages Baidu's fleet of more than 1,000 fully driverless vehicles worldwide. Governance for the program emphasizes cross-organizational coordination between Uber's ride operations and city teams, and Baidu's engineering and safety teams, with implementation contingent on local regulatory approvals and engineering integration across markets. The partnership represents a strategic operational expansion for Uber, positioning Baidu Apollo Go Computer Vision capabilities directly into Uber's ride-hailing business functions while requiring localized safety and regulatory governance for commercial rollouts. |
SCM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
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|
|
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Fleet Management | SCM |
|
2018 | 2018 |
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HCM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
|
|
|
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Learning and Development | HCM |
|
2021 | 2021 |
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CRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
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|
|
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Sales Automation, CRM, Sales Engagement | CRM |
|
2022 | 2022 |
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IT Decision Makers and Key Stakeholders at Uber
| First Name | Last Name | Title | Function | Department | Phone | |
|---|---|---|---|---|---|---|
| No data found | ||||||
Apps Being Evaluated by Uber Executives
| Date | Company | Status | Vendor | Product | Category | Market |
|---|---|---|---|---|---|---|
| No data found | ||||||
FAQ - APPS RUN THE WORLD Uber Technographics
Uber is a Transportation organization based in United States,
with around 31100 employees and annual revenues of $43.98 billion.
Uber operates a diverse technology stack with applications such as
LatentView PRISM, Golang and Baidu Apollo Go,
covering areas like AML, Fraud and Compliance, Apps Development and Computer Vision.
Uber has invested in cloud applications and AI-driven platforms to optimize efficiency and growth,
collaborating with vendors such as LatentView Analytics, Google and Baidu.
Uber recently adopted applications including
Baidu Apollo Go in 2025, Salesforce Media Cloud in 2022 and Rosetta Stone in 2021,
highlighting its ongoing modernization strategy.
APPS RUN THE WORLD maintains an up-to-date database of Uber’s key decision makers and IT executives,
available to Premium subscribers.
Our research team continuously updates Uber’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 Uber technographics profile,
including detailed breakdowns by category, vendor, and IT decision makers.