List of Fennel AI Customers
Menlo Park, 94025, CA,
United States
Since 2010, our global team of researchers has been studying Fennel AI customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Fennel AI for AI Model Deployment and Monitoring from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Fennel AI for AI Model Deployment and Monitoring include: Cricut, a United States based Manufacturing organisation with 830 employees and revenues of $1.31 billion, Upwork, a United States based Professional Services organisation with 618 employees and revenues of $769.0 million, Rippling, a United States based Professional Services organisation with 3057 employees and revenues of $385.0 million and many others.
Contact us if you need a completed and verified list of companies using Fennel AI, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Fennel AI customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
Cricut | Manufacturing | 830 | $1.3B | United States | Fennel | Fennel AI | AI Model Deployment and Monitoring | 2024 | n/a |
In 2024, Cricut implemented Fennel AI for AI Model Deployment and Monitoring. The deployment targeted personalized ranking and recommendation capabilities to improve product and marketplace relevance and to reduce compute overhead.
The Fennel AI implementation leveraged feature engineering and incremental compute pipeline modules to maintain up-to-date ranking features while minimizing batch compute costs. The architecture positioned Fennel AI as a model serving and monitoring layer providing automated model orchestration, lightweight scoring at inference, and production observability for ranking models.
Operational coverage focused on product discovery, merchandising, and marketplace recommendation workflows, integrating model outputs into Cricut's e-commerce and marketplace business functions. Governance centered on model lifecycle controls, automated incremental retraining pipelines, and monitoring rules to manage compute efficiency, with stated outcomes of improved product and marketplace relevance and reduced compute overhead.
|
 |
Rippling | Professional Services | 3057 | $385M | United States | Fennel | Fennel AI | AI Model Deployment and Monitoring | 2024 | n/a |
In 2024 Rippling deployed Fennel AI within its people and HR product area in the United States. The deployment uses Fennel AI as an AI Model Deployment and Monitoring platform to support trust and safety, fraud detection and automated decisioning features.
Implementation centered on feature engineering and real time feature pipelines inferred from press coverage naming Rippling as a Fennel customer, with Fennel AI providing model serving and monitoring capabilities typical for the AI Model Deployment and Monitoring category. The configuration included pipelines to transform and serve features into production decisioning workflows, and instrumentation for model observability and drift detection.
Operational scope was scoped to Rippling's people and HR product domain, impacting product engineering, risk and compliance, and trust and safety teams across its US operations. Governance aligned model lifecycle orchestration with decisioning workflows and incident runbooks to support continuous monitoring and controlled rollout of machine learning features.
|
 |
Upwork | Professional Services | 618 | $769M | United States | Fennel | Fennel AI | AI Model Deployment and Monitoring | 2024 | n/a |
In 2024, Upwork implemented Fennel AI in its AI Model Deployment and Monitoring environment. Upwork used Fennel AI to build and serve machine learning features for marketplace recommendations, trust and safety, and fraud-detection workflows in the United States.
The implementation centered on feature engineering and incremental real-time feature pipelines, inferred from public announcements naming Upwork as a Fennel customer. Fennel AI was configured to materialize and serve features with low latency, enabling more frequent model refresh cycles and online feature access for production inference.
Operational coverage focused on Upwork’s marketplace and risk functions, aligning feature outputs directly into recommendation engines and automated trust and safety pipelines. Deployment architecture paired feature pipelines with production model serving endpoints, with configuration controls for feature versioning and freshness to support fraud-detection signals.
Governance emphasized feature lineage, version control, and incremental rollout for high-risk workflows, supporting controlled adoption across recommendation and risk teams. The deployment measurably improved model freshness and accuracy as reported, while concentrating operational effort on feature operationalization for marketplace recommendations and fraud detection.
|
Buyer Intent: Companies Evaluating Fennel AI
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||