COYOTE
25 Quai Gallieni,
Suresnes, 92150,
France
Suresnes, 92150,
France
33 1 76 49 48 47
Professional Services
COYOTE Technographics
COYOTE Technographics, Software Purchases, AI and Digital Transformation Initiatives
Discover the latest software purchases and digital transformation initiatives being undertaken by COYOTE and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 240 COYOTE employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that COYOTE has purchased the following applications: SAP Travel and Expense Management for Expense Management in 2010, Dataiku Data Science Studio (DSS) for ML and Data Science Platforms in 2017, SAP Conversational AI for Chatbots and Conversational AI in 2016 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems COYOTE is running and its propensity to invest more and deepen its relationship with SAP , Dataiku , Google 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 COYOTE revenues, which have grown to $119.0 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 COYOTE 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.
COYOTE Tech Stack and Enterprise Applications
COYOTE ERP
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| SAP | Legacy | SAP Travel and Expense Management | Expense Management | ERP | n/a | 2010 | 2010 |
In 2010, COYOTE implemented SAP Travel and Expense Management. COYOTE uses SAP Travel and Expense Management within Expense Management to support finance-led annual plant budgeting and period expense control, specifically to prepare and develop the annual plant budget including developing standards and updating the standards and period expense budgets in SAP. The deployment consolidated travel and expense capture, policy enforcement, and budget provisioning for finance and travel operations across company sites.
Functional configuration emphasized expense reporting workflows, per diem and allowance standards, approval routing, and automated updates to period expense budgets inside SAP financial modules, aligning Expense Management processes with corporate budgeting cadence. Governance was structured around the finance team and plant budget owners, with processes defined for standards development, periodic budget updates, and approval controls. The implementation focused on integrating expense lifecycle controls with budget management to maintain consistent period expense budgeting within SAP.
|
COYOTE AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Dataiku | Legacy | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | AI Development | n/a | 2017 | 2017 |
In 2017, Coyote implemented Dataiku Data Science Studio (DSS) in the ML and Data Science Platforms category to automate detection and correction of speed limit data used in its embedded maps. Coyote’s IoT fleet and mobile apps generate billions of anonymized rows of speed and position telemetry, creating a high volume data input that quality teams needed to analyze for map accuracy. The two companies already enjoyed a long-term relationship, in 2015 Coyote deployed a churn project developed using Dataiku Data Science Studio which validated broader application of predictive analytics to Coyote’s core product development.
Using Dataiku Data Science Studio, Coyote implemented machine learning workflows to segment roads into sections and analyze driving patterns within each segment. The implementation included anomaly detection and predictive modeling capabilities that estimate the likely speed limit for a given road section. Data mining and visualization capabilities in the platform were adopted to surface anomalies and support iterative model refinement through collaborative project workspaces.
Operational coverage focused on product quality and map accuracy workflows within Coyote’s quality teams and product development organization, leveraging the high volume IoT-derived dataset as the primary data source. Workflows were engineered to process billions of rows of anonymized telemetry and produce section-level predictions that feed downstream correction pipelines and quality assessment processes.
The deployment reinforced a data driven decision model across the company, shifting decisions from standard analytics reports to model based evidence and automated correction outputs. Collaborative features in Dataiku Data Science Studio enabled employees with differing skill sets to participate in model development, review, and deployment, expanding data mining and visualization practices beyond central analytics teams. The implementation automated parts of the speed limit correction process and embedded governance checkpoints for quality validation before updates were applied to map feeds.
Explicit outcomes reported by Coyote include a 9% increase in speed limit reliability on analyzed datasets and automation of the speed limit correction process. The project also contributed to a global data driven spirit within the company and increased customer loyalty. Dataiku Data Science Studio served as the platform enabling machine learning driven quality assurance for embedded map speed limits.
|
COYOTE AI-Powered Application
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| SAP | Legacy | SAP Conversational AI | Chatbots and Conversational AI | AI-Powered Application | n/a | 2016 | 2017 |
In 2016, COYOTE implemented SAP Conversational AI. The deployment targeted customer-facing conversational interfaces under the Chatbots and Conversational AI category to automate routine service interactions and improve first contact handling.
The implementation emphasized core conversational modules, including natural language understanding, intent classification, entity extraction, dialog flow orchestration, and webhook-driven actions to create or update service tickets. Configuration work included training intents, authoring conversation trees, integrating automated routing logic, and establishing fallback and escalation paths to surface complex issues to human agents.
Operational coverage focused on COYOTE's professional services support teams in France, embedding the chatbot into existing service desk workflows and agent escalation processes. SAP Conversational AI can be paired with SAP Service Ticket Intelligence to route and enrich tickets, a pattern illustrated by an SAP Innovation Services engagement for NHK Spring that linked conversational front ends to ticket intelligence for case triage. Governance centered on bot training lifecycle management, conversational content versioning, and formal handoff rules between automated agents and human operators.
|
COYOTE Collaboration
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Collaboration | Collaboration |
|
2018 | 2018 |
|
COYOTE TRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Treasury Management | TRM |
|
2011 | 2011 |
|
COYOTE IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
|
|
|
|
Application Hosting and Computing Services | IaaS |
|
2020 | 2020 |
|
IT Decision Makers and Key Stakeholders at COYOTE
| First Name | Last Name | Title | Function | Department | Phone | |
|---|---|---|---|---|---|---|
| No data found | ||||||
Apps Being Evaluated by COYOTE Executives
APPS RUN THE WORLD tracks software evaluation trends across 2 million companies worldwide, including buyer insights from COYOTE IT executives and key decision makers. As part of ARTW Buyer Intent and technographics insights, these findings provide useful visibility into the COYOTE digital transformation priorities and AI adoption trends.
| Date | Company | Status | Vendor | Product | Category | Market |
|---|---|---|---|---|---|---|
| No data found | ||||||
FAQ - APPS RUN THE WORLD COYOTE Technographics
COYOTE is a Professional Services organization based in France,
with around 240 employees and annual revenues of $119.0 million.
COYOTE operates a diverse technology stack with applications such as
SAP Travel and Expense Management, Dataiku Data Science Studio (DSS) and SAP Conversational AI,
covering areas like Expense Management, ML and Data Science Platforms and Chatbots and Conversational AI.
COYOTE has invested in cloud applications and AI-driven platforms to optimize efficiency and growth,
collaborating with vendors such as SAP and Dataiku.
COYOTE recently adopted applications including
Microsoft Azure Cloud Services in 2020, Google Workspace (Formerly Google G-Suite) in 2018 and Dataiku Data Science Studio (DSS) in 2017,
highlighting its ongoing modernization strategy.
APPS RUN THE WORLD maintains an up-to-date database of COYOTE’s key decision makers and IT executives,
available to Premium subscribers.
Our research team continuously updates COYOTE’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 COYOTE technographics profile,
including detailed breakdowns by category, vendor, and IT decision makers.