List of New Relic AI Monitoring Customers
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Since 2010, our global team of researchers has been studying New Relic AI Monitoring 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 New Relic AI Monitoring 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 New Relic AI Monitoring for AI Model Deployment and Monitoring include: MercadoLibre Argentina, a Argentina based Retail organisation with 12043 employees and revenues of $3.82 billion, Banco Inter, a Brazil based Banking and Financial Services organisation with 3800 employees and revenues of $3.56 billion, Thredd, a United Kingdom based Banking and Financial Services organisation with 331 employees and revenues of $50.0 million and many others.
Contact us if you need a completed and verified list of companies using New Relic AI Monitoring, 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 New Relic AI Monitoring 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!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Banco Inter | Banking and Financial Services | 3800 | $3.6B | Brazil | New Relic | New Relic AI Monitoring | AI Model Deployment and Monitoring | 2016 | n/a |
In 2016, Banco Inter implemented New Relic to monitor its digital banking platforms, explicitly instrumenting customer-facing services and the Babi conversational bot. Banco Inter extended that observability footprint to include New Relic AI Monitoring to support AI model visibility and runtime behavior in the AI Model Deployment and Monitoring category.
The deployment centralized application performance monitoring, distributed tracing, synthetic checks, real-time dashboards, and alerting to cover transaction flows across web, mobile, and conversational interfaces. Configuration work included service-level telemetry, anomaly detection tuned for model-driven interactions, and role-based dashboards for operations and engineering to surface degradations tied to AI-driven channels.
Integrations and instrumentation emphasized the Babi conversational bot and digital channels, with telemetry correlated to core banking transaction services and customer journeys. Operational coverage was reported to include roughly 95% of Banco Inter’s critical processes, reflecting end-to-end observability across digital banking and channel operations.
Operational governance centralized incident routing and triage into platform and SRE teams, aligning alerts and runbooks with the monitoring configuration. Reported outcomes linked to the New Relic deployment include an approximately 57% reduction in mean time to repair and broad coverage of critical processes, supporting ongoing use of New Relic AI Monitoring for model and digital channel observability.
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MercadoLibre Argentina | Retail | 12043 | $3.8B | Argentina | New Relic | New Relic AI Monitoring | AI Model Deployment and Monitoring | 2023 | n/a |
In 2023 MercadoLibre Argentina standardized on New Relic and implemented New Relic AI Monitoring to extend end-to-end observability across its e-commerce and payments platforms. The implementation aligns with a company-wide observability strategy intended to ensure uptime and consistent operational metrics for millions of users across Latin America.
New Relic AI Monitoring was deployed to capture telemetry across application, infrastructure, and machine learning model layers consistent with the AI Model Deployment and Monitoring category. Configuration emphasized model performance monitoring, anomaly detection, latency profiling, instrumentation of traces and logs, and real-time alerting workflows to surface model drift and production inference issues.
Operational scope covered market-facing commerce and payments services and was integrated into engineering and product team workflows, providing centralized dashboards and contextual traces for incident response. The New Relic AI Monitoring application unified metric, trace, and log streams to create correlated observability across microservices and ML inference paths.
Governance and rollout focused on standardized instrumentation patterns, alert runbooks, and role-based access controls to align SRE and product team responsibilities with monitoring workflows. The deployment supports AI Model Deployment and Monitoring use cases for model health, inference latency, and anomalous behavior detection while aligning with MercadoLibre Argentina’s stated aim to maintain uptime and consistent operational metrics.
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Thredd | Banking and Financial Services | 331 | $50M | United Kingdom | New Relic | New Relic AI Monitoring | AI Model Deployment and Monitoring | 2023 | n/a |
In 2023, Global Processing implemented New Relic AI Monitoring as an AI Model Deployment and Monitoring initiative. The deployment targeted a payments and financial services observability use case in Argentina, with an explicit focus on incident reduction and operational efficiency for the platform a Latin American digital payments provider.
The implementation configured New Relic AI Monitoring to simplify engineer onboarding and to surface prioritized incidents, using AI-driven alert correlation and contextualized triage to reduce alert noise. Configuration emphasized automated enrichment of telemetry and incident context, enabling engineers to consume fewer, higher signal alerts and accelerate time to remediate issues.
Operational coverage centered on site reliability engineering and platform operations teams supporting payments processing in Latin America, with the monitoring solution ingesting platform telemetry including logs, traces, and metrics. The rollout integrated the AI monitoring into existing observability streams and on-call workflows to align detection, routing, and escalation with operational practices.
Governance and process changes included new alerting thresholds, incident classification workflows, and onboarding artifacts to ramp engineers on AI-assisted triage. Outcomes reported by the customer included a reduction in alert noise by 50% and an improvement in mean time to resolution of about 30%, outcomes that reinforced the deployment focus on incident reduction and operational efficiency.
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