Business Need
A 50,000-Document Knowledge Base Difficult to Navigate
A Global Regulatory Body overseeing international labour standards holding one of the world’s most authoritative policy knowledge bases, over 50,000 documents spanning conventions, research reports, country profiles and legal guidelines across different languages including English, French and Spanish.
But accessing it was a nightmare. Researchers spent 3-4 weeks per query manually scanning PDFs, switching between databases, and cross-referencing sources, just to locate a single clause or statistic. The expertise was locked inside documents that no one had time to read.
With policy decisions affecting millions of people globally, the cost of slow knowledge access wasn’t just inconvenience, it was impact.
The Shift
An AI Assistant That Knows Every Document by Heart
We built the Intelligent Research Assistant, a purpose-engineered, agentic based conversational platform that turns any natural language question into a synthesized and cited response drawn from multiple relevant documents in just a few seconds.
Ask about child labour statistics in West Africa and then follow-up about Argentina; Ask it to cross-reference a convention article with a country profile. It handles all of it, maintaining full conversation context, auto-translating source documents and linking every fact back to the exact page it came from.
This is not a search engine dressed up as a chatbot. It is a multi-agent intelligence system built specifically for high-stakes, multi-document policy research.
DATA ENGINEERING
Before It Can Answer, It Has to Understand
Reliable answers start with reliable data. Before any agent processes a query, 50,000+ documents in multiple languages are extracted, enriched, translated, chunked and semantically indexed. At this scale, the pipeline runs in parallel batches using Azure Durable Functions — concurrently processing multiple documents with retry logic and a Dead Letter Queue ensuring nothing is silently dropped. Each document is assigned a unique ID with a change-hash so only genuinely new or modified files trigger reprocessing, keeping the pipeline fast and cost-efficient at full corpus scale. This is the invisible infrastructure that makes everything possible.
01
Collect & Store
– Source types: PDFs, HTML, Database
– Incremental: Only new/changed docs downloaded
– Auditable: Unique doc ID + full metadata per file
02
Extract & Translate
– PDF → JSON: Structure, headings & tables preserved
– HTML parsing: Processed with same fidelity
– Auto-translate: Non-English documents
03
Chunk & Embed
– Documents Split into overlapping chunks
– Each chunk Enriched with metadata
– Semantic meaning,not just keywords
04
Index & Keep Current
Azure AI Search: Sub-second hybrid retrieval
Auto-refresh: New docs live within minutes — incremental re-index only
Resilient:Dead Letter Queue + full audit log
KEY FEATURES
What the Platform Does for Your Researchers
Plain-Language Queries
Ask anything in natural English — no commands, no syntax. The system understands intent, not just keywords.
Conversation Memory
Follow-up questions build naturally on earlier turns. No context lost, no repetition required across a session.
Smart Query Rephrasing
Vague follow-ups are rewritten using conversation history before retrieval begins — every search is fully contextualised automatically.
Entity-Based Filtering
Topic codes, countries, years, and source types extracted and applied as filters — narrowing the corpus before any vector search begins.
Page-Level Citations
Every claim carries an inline marker [1][2][3] linking to the exact document and page number. Verify any source in one click.
Multi-Language Support
Documents in English, French, Spanish, and Arabic all processed and retrievable. Language is never a barrier to the right answer.
Multi-Agent Routing
Conversational, informational, and data-driven queries are classified and handled by separate specialised agents — not a single generic model.
Continuous Auto-Ingestion
Azure Functions CRON jobs scan source repositories on a scheduled cadence, detect new or updated documents, and trigger the full ingestion pipeline automatically — extraction, translation, chunking, embedding, and re-indexing. New policy documents go live in the knowledge base within minutes of publication. No manual uploads. No stale answers.
Always Grounded
Responses are drawn only from the controlled document corpus — no hallucinations, no unverified web content. When information is unavailable, the system says so transparently.
TECHNOLOGY
The Infrastructure Behind the Intelligence
Every component was chosen for production reliability, Azure-native security, and seamless scalability – from a pilot to a global deployment serving hundreds of concurrent researchers.
Azure OpenAI
Language understanding & response generation
Azure AI Search
Hybrid semantic + keyword retrieval
Azure Blob Storage
Centralised document storage & provenance
Azure Functions
Serverless automated ingestion pipeline
Azure App Service
Chatbot frontend & backend hosting
PostgreSQL
Structured metadata & session management
RESULTS
The Numbers That Followed
The International Regulatory Body saw immediate, measurable improvements in research velocity, policy engagement, and organisational decision-making – across every regional team.
75%
Less Time Searching
Queries answered in under 10 seconds – down from 3-4 hours of manual PDF scanning.
3×
More Content Explored
Researchers engage with policy resources daily, not ad-hoc. Depth of use tripled.
90%
Faster Decision Velocity
Critical data surfaces in one conversation. No analyst queues. No bottlenecks.
Zero
Compliance Incidents
Role-based access across all regions. Zero unauthorised accesses since go-live.
3-4 weeks of searching. Replaced by a few seconds conversation.
The AI Assistant didn’t just accelerate research – it changed what research looks like for an International Regulatory Body. Expertise that lived inside documents is now accessible to everyone, instantly, in any language, with every claim backed by a source they can verify.
Do you have a knowledge problem this complex? Let’s help build your solution.