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Product & project · AI publishing governance

AI publishing governance ecosystem for editorial excellence at scale.

A human-in-the-loop, multi-agent editorial ecosystem: specialised AI agents support editing, translation, auditing, political-risk screening and analytics, while human editors keep final authority.

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Reference
eAI-PR / MAPE
Status
~45% in production · 4 modules in testing
Stack
LangGraph · AutoGen · AWS Bedrock · Azure AI Studio
Governance
EU AI Act · ISO/IEC 42001 · NIST AI RMF
eAI-PR / MAPE — concept illustration
Results

Measured outcomes.

−53%
content cycle time
−27%
content & governance errors
+32–45%
active users
27+
languages, zero terminology incidents
Architecture

Core design themes.

01

Editorial excellence

Multi-tier editing, summarisation of large reports and multilingual translation with terminology enforcement.

02

Logical auditing

Checks on figures and claims against trusted sources — no statistical hallucinations before publication.

03

Political-risk guardrails

Sensitivity screening, accessibility and IP checks that advise; editors decide.

04

Performance insight

Engagement analytics, A/B testing and UX recommendations tied to real outcomes.

Capabilities

What it delivers.

Lessons & roadmap

What production taught us, and what comes next.

Lessons learned

  • Human-in-the-loop: AI handles heavy processing, senior editors keep final veto
  • Institution-specific geopolitical filters outperform generic models
  • Engagement metrics tied to CSAT/NPS matter more than vanity data

Modules in development

  • Predictive audience analytics
  • Multimodal generation
  • Cross-channel automation
  • Advanced governance controls
Implementation note · Product · in production & support (~45%)

Builds on editorial-governance work in UN, NATO, EEAS and IBM contexts. Four further modules are in development under the same human-in-the-loop guarantees. It is a PiR2-IT product in production, and the team keeps refining it with every deployment.

References, case studies and demonstrations are available on request, under NDA.

Multi-agent AIHuman-in-the-loopMultilingualAI governance
Questions

About this project.

Who has the final say on content?

Human editors. AI agents draft, check and flag; senior editors keep final veto.

How many languages are supported?

27+ languages, with zero diplomatic terminology incidents in production.

Which AI governance frameworks apply?

EU AI Act, ISO/IEC 42001 and NIST AI RMF.

How far is it in production?

About 45% of the scope is in production, with four further modules in active testing.

Related

Explore further.

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