Reported impact
Business outcome
Freed 741.7 hours by automation in one quarter
- Productivity Improvement
- Speed to Market
Google CloudSoftware / SaaSIT Operations AutomationCloud NativeDevOpsGenerative AI / LLMProductivity ImprovementSpeed to MarketUndated Google CloudGC#4285f4Software / SaaSUnited StatesLiveRamp leveraged Google Cloud and AI to automate operational center tasks, significantly boosting developer productivity and improving SLA attainment for its global engineering teams.Achieved a 435% year-over-year increase in operational center hours savedArchived · Aug 5, 20264IT Operations AutomationAgent Platform · BigQuery · Cloud Run0 2026-08-05 4
LiveRamp
IT Operations Automation
LiveRamp leveraged Google Cloud and AI to automate operational center tasks, significantly boosting developer productivity and improving SLA attainment for its global engineering teams.
Achieved a 435% year-over-year increase in operational center hours saved
Freed 741.7 hours by automation in one quarter
Solution
LiveRamp's key technology goals for the OC automation project were modernization, cloud-enabled scalability, and AI-driven operational efficiency. They aimed to eliminate manual ticket routing, speed resolution, and minimize repetitive support work. Prior IT environments relied heavily on manual ticket handling, and high context-switching overhead, creating engineering bottlenecks. The objectives were to automate ticket assignment using a fine-tuned AI model on historic JIRA data, introduce a Slack bot for automated real-time responses by leveraging team-specific data, and trigger infrastructure workflows directly from JIRA for fast resolution. True operational value lies in delivering a seamless, unified user experience across channels like Slack, web UI, and Jira, enabling users to get support wherever they work.
Solution architecture
- Compute
- Cloud Run Runs serverless application services and APIs with automatic scaling for bursty workloads.
- Storage
- BigQuery Serves as the governed analytics and storage layer for high-volume operational data, features, and reporting.
- Orchestration
- Gemini Enterprise Agent Platform Coordinates multi-agent workflows, tool calling, and governed automation across the application.
- Gemini Enterprise Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
- Agent Platform Coordinates multi-agent workflows, tool calling, and governed automation across the application.
- Gemini Pro Provides the reasoning or generation layer used for classification, orchestration, content generation, or analysis.
Evidence from the source
By facilitating seamless identity translation, LiveRamp enables marketers to break down data silos and safely expand their understanding with trusted partner data without moving it. This dynamic, interconnected ecosystem
Freed 741.7 hours by automation in one quarter
LiveRamp boosts developer productivity and SLA efficiency with AI automation on Google Cloud
LiveRamp's on-call (OC) automation solution streamlines operational tasks for engineers through three core innovations: AIOps Jira assist, an AI Slack bot, and OC automation. The solution started with Gemini Enterprise A
Products: Cloud Run Gemini Pro Gemini Enterprise Agent Platform BigQuery BigQuery ML
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value77/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth10/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity12/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact25/252 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence75%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance0/10The publication date has no documented provenance.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity6/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://cloud.google.com/customers/liveramp-aiGoogle CloudFirst-party
LiveRamp customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
Date evidence
- First archived Aug 5, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.Open date source
- Sitemap last modified Aug 4, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
Related
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