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AI Services All ai services → Claude Agents Claude Copilots Claude on Adobe Claude on Salesforce Agentforce + Claude GEO & Brand Visibility AI Governance & Safety FrontRow Methodology
Adobe Services All adobe practice → Adobe Experience Manager Marketo Engage Journey Optimizer Customer Journey Analytics Workfront GenStudio Content Supply Chain Marketo MCP + Claude Marketo ↔ Salesforce Ops Salesforce Practice
Products All products → KoruIQ MarTech Observability QuipTag for AEM QuipMLR AEM Cloud Launchpad
Industries All industries → Pharma & Life Sciences Financial Services Retail & Commerce Higher Education Manufacturing
Company All company → About NextRow Global Delivery Partners Results Security & Trust Insights
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Numbers, not adjectives.

Three documented engagements and one governed pilot offering, anonymized by policy, each with situation, approach, and measured outcome.

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THE HEADLINE NUMBERS

What shipped, measured.

up to 80%

faster metadata tagging with QuipTag for AEM at a Fortune 100 pharma

$4M

recoverable media spend identified per year by KoruIQ at a Fortune 100 pharma

70%

MLR review cost and time saved with QuipMLR compliance automation

100+

Marketo operations available to the governed Campaign QA Copilot via Adobe's hosted MCP

CASE STUDIES

Situation. Approach. Outcome.

up to 80% faster tagging

Metadata at Fortune 100 scale with QuipTag

Situation. A Fortune 100 pharmaceutical company managed thousands of AEM assets by hand: a bottleneck for search, reuse, and analytics.

Approach. QuipTag inside AEM Assets, wired to Adobe Analytics and CJA, with human review on edge cases.

Outcome. up to 80% faster tagging across thousands of assets, with taxonomy the downstream analytics could trust.

$4M/yr identified

Media-spend recovery with KoruIQ

Situation. At a Fortune 100 pharmaceutical company, broken tags meant paid media was buying traffic the systems could not see.

Approach. KoruIQ monitoring tag health, data integrity, and media delivery continuously across the stack.

Outcome. $4M per year in recoverable media spend identified, visible and attributable.

70% saved

MLR review automation with QuipMLR

Situation. Medical-Legal-Regulatory review is the throughput ceiling for pharma content: every promotional asset waits on committee review.

Approach. QuipMLR's agentic AI pre-screens content against claims libraries, reference packages, and prior rulings. Human reviewers keep final sign-off.

Outcome. 70% reduction in MLR review cost and time, without lowering the compliance bar.

100+ operations, governed

Campaign QA Copilot: Claude on Marketo (pilot offering)

Situation. Pre-launch Marketo QA covers links, tokens, audience filters, and program settings, manually, against the launch clock.

Approach. A governed Claude copilot running checks through Adobe's hosted Marketo MCP server (marketo-mcp.adobe.io, released 2026): 100+ operations, write-capable but non-destructive, restricted by a Munchkin-ID allowlist, human approval on every change.

Outcome. Offered as a FrontRow pilot, the proof-point for governed agents inside production marketing systems.

CDW

NAMED CLIENT · ADOBE CUSTOMER STORY

CDW: four terabytes, one system of record

NextRow implemented Adobe Experience Manager Assets on Microsoft Azure as CDW's enterprise DAM. CDW reported about 20 hours per week returned to the creative team and more than 4TB of assets centralized.

CDW, a Fortune 500 technology distributor, is a public Adobe success story from NextRow's Adobe Gold Solution Partner practice. When a client permits a name we publish it; otherwise we publish the number.

READ THE FULL CDW CASE STUDY →

HOW TO READ THIS PAGE

Our claims policy, in plain terms.

Results are measured against client baselines during the engagement and anonymized by policy: "a Fortune 100 pharmaceutical company" is a real client, not a composite. NextRow never invents client names, awards, or certifications. See AI Governance & Safety, Global Delivery, and the FrontRow methodology.

ANSWERS · FAQ

What buyers ask about these results

Because enterprise clients, particularly the Fortune 100 pharmaceutical company behind several results here, rarely permit named AI case studies. NextRow publishes the numbers and the mechanism, anonymizes the client by policy, and never invents a logo to decorate a claim. One public exception exists: CDW's Adobe success story.

Against the client's own baseline during the engagement. The 80% tagging figure compares QuipTag-assisted throughput to the client's prior manual tagging rate; the $4M per year figure is recoverable media spend identified by KoruIQ monitoring; the 70% figure compares QuipMLR-assisted MLR review cost and time to the pre-automation process.

A governed Claude copilot that runs pre-launch quality checks on Marketo campaigns (links, tokens, audience filters, program settings) through Adobe's hosted Marketo MCP server (marketo-mcp.adobe.io, released 2026, with Claude Desktop and Claude Code among Adobe’s supported clients). It is offered as a pilot: write-capable but non-destructive, restricted by a Munchkin-ID allowlist, with 100+ operations available.

The mechanisms do. Metadata automation, media-spend observability, and gated review are industry-agnostic patterns; pharma simply proves them under the strictest constraints. Industry pages for financial services, retail, higher education, and manufacturing show how each pattern maps.

CDW's Adobe engagement is a public success story, a named and verifiable reference from a Fortune 500 technology distributor. For anonymized results, NextRow can walk through the engagement mechanics, measurement approach, and governance model in detail during an assessment conversation.

With the FrontRow assessment stage: a fixed-scope engagement, typically from $15,000 over 4–6 weeks, ending in a scorecard, prioritized use cases with ROI, and a 90-day plan. Pilot, production, and run stages follow only when the number justifies them.

Put a number on it in your stack.

A fixed-scope assessment ends in a scorecard, prioritized use cases with ROI, and a 90-day plan.

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