A multi-agent RAG platform replaced shadow-AI in a global pharma.
Standardised prompts, project-level ACLs, and end-to-end observability — replacing teams pasting confidential documents into external AI tools with a sovereign, audit-ready Azure alternative.
Confidential content was leaving the building — and nobody could prove it wasn’t.
Shadow AI in confidential workflows
Teams pasted privileged scientific content and clinical summaries into external chat tools to summarise and draft, creating an active data-exposure risk the compliance office could not close.
Inconsistent messaging at scale
Different employees used different tools, different prompts, and different reference material — leaving therapy-area communications uneven across markets and audiences.
No leadership visibility
Leaders had no way to see what information employees were accessing, which AI tools were in use, or whether outputs aligned with scientific and regulatory guidelines.
Manual SharePoint search
Large repositories of research, clinical, and marketing material meant analysts spent significant time hunting for source documents before any writing actually began.
Audit posture
Compliance teams could not assure regulators that AI-generated outputs respected internal scientific and brand guidelines — no logs, no reproducibility, no chain of evidence.
A sovereign RAG ecosystem, audit-ready by design.
Multi-agent orchestration
Specialised agents handle retrieval from SharePoint, web access when explicitly allowed, and content updates. A coordinator agent routes each request and enforces guardrails before any output is returned.
Document understanding
GPU-powered container apps process source documents, extract tables and structured content, and transform them into searchable, retrieval-ready insights aligned with the organisation's taxonomy.
Project-level access control
Retrieval respects the organisation's SharePoint folder structure end-to-end — users only see and retrieve content they were already authorised to view, with ACLs honoured at query time.
Consistent compliant responses
Standardised system prompts enforce scientific accuracy, brand-aligned tone, and regulatory messaging across teams and therapy areas, so every output reads like the same organisation.
End-to-end observability
Every retrieval, agent action, external reference, and final generation is logged with user attribution and timestamps — ready for compliance review and full reconstruction.
Sovereign Azure deployment
All data ingestion, indexing, embedding, and LLM execution run entirely inside the organisation's Azure environment — no data leaves the tenant, no third-party model sees a document.
Shadow AI shut down — governance back in the room.
Confidential documents leaving the tenant
AI actions captured for audit and review
ACLs honoured at retrieval time, not after
Other engagements worth a look.
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Shadow AI, scattered prompts, no audit trail — we’ve seen this pattern across regulated industries. A pod can be in your release train within weeks.