Case Studies / Policy-Insider.AI
GOVERNMENT & PUBLIC AFFAIRS · DOCUMENT PROCESSING
Replacing manual policy document review with GenAI-powered summarization
Public affairs professionals track hundreds of policy documents published daily across multiple EU institutions and languages. Reading and summarizing them manually was a full-time job that couldn’t scale. We extended the Policy-Insider.AI platform with generative AI that automatically summarizes policy documents and delivers targeted alerts – turning hours of manual reading into seconds of automated extraction.
Client: Policy-Insider.AI – a platform for monitoring and analyzing public policy across European institutions.
KEY RESULTS
Auto
Policy documents summarized automatically – no manual reading
Multi-lang
Documents processed across multiple EU languages
Alerts
Email notifications with keyword-targeted summaries
LLMOps
Production-grade evaluation and quality assurance pipeline
INDUSTRY
Government & Public Affairs
USE CASE
Policy document summarization & retrieval
AI APPROACH
LLM + advanced prompting + LLMOps
LANGUAGES
Multiple EU languages
INTEGRATION
Platform extension + email alerts
ENGAGEMENT
Ongoing development
The challenge
Policy-Insider.AI serves public affairs professionals, lobbyists, and corporate government relations teams who need to stay on top of EU legislation, regulations, and policy developments. The volume of relevant documents is enormous – published daily by the European Commission, European Parliament, national governments, and regulatory agencies, often in different languages.
Before this project, keeping up with this flow required manual reading and summarization. Analysts would scan documents, identify which ones were relevant to their clients’ interests, and write summaries. At the scale of EU policy output, this was a bottleneck that limited how many topics and institutions the platform could cover – and how quickly users could be informed about developments that affected them.
The core problem: policy professionals needed to track and understand hundreds of documents published across multiple institutions and languages every day. Manual reading and summarization couldn’t keep up with the volume – critical developments were being missed or delivered too late.
What we built
We extended the Policy-Insider.AI platform with a generative AI layer that automates the most time-intensive part of policy monitoring: reading documents and extracting what matters.
Automatic document summarization. Using large language models with carefully engineered prompts, the system generates concise, accurate summaries of policy documents as they’re published. The prompts incorporate relevant context – document type, issuing institution, policy area – to produce summaries that are immediately useful to the platform’s users, not generic abstractions.
Multi-language processing. EU policy documents are published in multiple languages. The system handles this natively, processing documents regardless of their original language and producing summaries that capture the substance accurately across linguistic boundaries.
Keyword-targeted email alerts. Users can set up interest profiles based on specific topics, institutions, or keywords. The system generates targeted summaries and delivers them via email – so a user tracking AI regulation sees only documents relevant to AI regulation, summarized and delivered without any manual filtering.
Production-grade LLMOps. Deploying generative AI in production for professional users requires more than a good prompt. We built an iterative evaluation pipeline to monitor and maintain output quality – addressing the real challenges of LLM integration: inconsistent outputs, hallucination risk, and the difficulty of evaluating generated text at scale. This was built by experienced NLP engineers who understand the difference between a demo that works and a system that professionals can rely on.
The results
BEFORE
Manual reading and summarization of policy documents. Limited coverage. Slow turnaround. Analysts as the bottleneck between published documents and user insights.
AFTER
Automated summarization at the speed of publication. Multi-language coverage. Keyword-targeted delivery. Analysts freed to focus on analysis rather than reading.
The manual reading bottleneck was eliminated. Policy documents are now summarized as they’re published – not hours or days later. The platform’s coverage expanded because summarization capacity is no longer limited by how many documents a human team can read in a day.
For enterprise public affairs teams, this means faster awareness of relevant policy developments, broader monitoring coverage, and the ability to focus human expertise on interpretation and strategy rather than information gathering.
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