AI Buyer Insights:

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Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Michelin, an e2open customer evaluated Oracle Transportation Management

List of Evidently AI Observability Platform Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
Deepl Communications 1000 $150M Germany Evidently AI Evidently AI Observability Platform Database Performance Monitoring 2023 n/a
In 2023 Deepl deployed Evidently AI Observability Platform to instrument production translation and machine learning pipelines in Germany. The Evidently AI Observability Platform is classified under Database Performance Monitoring while operationally serving ML and data observability use cases, and it is used daily to test data quality and monitor production data drift for translation and ML pipelines. The implementation emphasizes ML and model observability and data quality monitoring capabilities drawn from vendor-aligned functionality, including automated drift detection, statistical evaluation of input distributions, scheduled model validation jobs, and dashboards for anomaly detection and alerting. Configuration focused on pipeline instrumentation and operationalizing evaluation routines to generate repeatable quality signals for engineering teams. Operational coverage centers on Deepl engineering and data science teams supporting translation services in Germany, with the Evidently AI Observability Platform running against live inference streams and upstream data ingestion layers. Signals from the platform feed day to day engineering workflows for triage and remediation of model or data issues, integrating into existing pipeline orchestration and incident processes. Governance shifted to incorporate regular drift review and incident triage, assigning monitoring ownership to engineering owners and embedding observability checks into routine delivery. Deepl reports reduced monitoring overhead and earlier detection of anomalies as direct outcomes of daily use of the Evidently AI Observability Platform, establishing it as a central tool for model and data quality within its translation pipelines.
Realtor.com Professional Services 1634 $262M United States Evidently AI Evidently AI Observability Platform Database Performance Monitoring 2023 n/a
In 2023, Realtor.com implemented the Evidently AI Observability Platform to operate a production-level feature-drift pipeline. The Evidently AI Observability Platform was integrated into Realtor.com’s Database Performance Monitoring posture to surface input data issues for property and search machine learning models. The implementation centers on feature-drift and model observability capabilities, specifically detecting anomalies, missing values, and new categorical values in upstream data sources. Realtor.com deployed these detection capabilities as a continuous pipeline that profiles input features, compares distributional baselines, and flags deviations that could indicate data quality regressions. Integrations are focused on upstream data sources feeding property and search models in the United States, with the pipeline instrumented alongside model scoring flows to provide real-time input validation. Operational ownership aligns with model operations and data engineering teams, using the Evidently AI Observability Platform to monitor data integrity for production ML workloads. Governance emphasizes automated detection of bad inputs to prevent degradation of model performance, with the platform providing observable signals that feed existing remediation workflows. The primary stated outcome is prevention of bad inputs from degrading model performance, achieved through continuous feature-drift detection and upstream data monitoring.
Wise Banking and Financial Services 4301 $710M United Kingdom Evidently AI Evidently AI Observability Platform Database Performance Monitoring 2023 n/a
In 2023, Wise implemented Evidently AI Observability Platform as part of its Database Performance Monitoring footprint to monitor production data distribution and to link model performance metrics back to training data for financial and transactional machine learning systems in the United Kingdom. The Evidently AI Observability Platform is used to instrument production ML pipelines that support transaction processing, providing continuous monitoring of input distributions and model outputs for operational risk detection. Module usage has been characterized from vendor commentary as ML and data observability functionality rather than a traditional database performance product, and implementations emphasize data distribution monitoring, concept drift detection, and metric alignment between production signals and training datasets. Configuration appears focused on dataset versioning references and performance metric tracking to establish lineage between deployed models and their training sources. Integrations are implemented at the pipeline and model telemetry level to propagate model performance metrics into Wise operational dashboards, enabling teams that own transactional ML systems to correlate runtime behavior with historical training data. The deployment covers production model endpoints and the surrounding feature ingestion processes, aligning observability with the operational scope of Wise's financial and transactional ML workloads in the United Kingdom. Governance and workflow adjustments include establishing traceability between training data and production performance to improve detectability of regressions and to support model robustness procedures. Explicit outcomes reported include improved model robustness and enhanced detectability of regressions, reflecting the platform role of Evidently AI Observability Platform within Wise Database Performance Monitoring efforts.
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FAQ - APPS RUN THE WORLD Evidently AI Observability Platform Coverage

Evidently AI Observability Platform is a Database Performance Monitoring solution from Evidently AI.

Companies worldwide use Evidently AI Observability Platform, from small firms to large enterprises across 21+ industries.

Organizations such as Wise, Realtor.com and Deepl are recorded users of Evidently AI Observability Platform for Database Performance Monitoring.

Companies using Evidently AI Observability Platform are most concentrated in Banking and Financial Services, Professional Services and Communications, with adoption spanning over 21 industries.

Companies using Evidently AI Observability Platform are most concentrated in United Kingdom, United States and Germany, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Evidently AI Observability Platform across Americas, EMEA, and APAC.

Companies using Evidently AI Observability Platform range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 33.33%, large organizations with 1,001-10,000 employees - 66.67%, and global enterprises with 10,000+ employees - 0%.

Customers of Evidently AI Observability Platform include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified Evidently AI Observability Platform customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Database Performance Monitoring.