[ KNOWLEDGE & COMPLIANCE ]
Askive
Sovereign Multi-Agent Document Platform
A private RAG chatbot for compliance and policy archives. Citations on every answer. No data leaves the corporate firewall.
Domain
KNOWLEDGE & COMPLIANCE
Status
Delivered as a sovereign-deployment RAG platform inside a public-sector engagement
Use when
Legal, compliance, or regulated-industry clients need conversational query over their archive without using public LLM endpoints.
Reference
A national tourism authority in the GCC
The problem
Public-sector and regulated organisations cannot ship document content to public LLM endpoints. The default chatbot architecture violates that constraint on day one. Internal staff still need answers in minutes, not days.
The approach
Retrieval-augmented generation with a private vector store and an LLM that respects data residency. Every response surfaces the source PDFs and page numbers it drew from. Operations staff get a familiar chat interface.
The architecture
ChromaDB and HuggingFace embeddings inside the customer environment. Generation against Gemini Pro with retrieval-augmented prompts. A Next.js 16 frontend with streaming responses, document upload and management, and chat history. FastAPI service ties it together. Source citations stitched into every response.
The outcome
A working internal Q&A surface for the corporate archive, with source citations on every answer. A pattern that ports directly to other regulated archives: legal, compliance, internal policy, regulator filings.
[ ATI SHAPE ]
Predictive intelligence
Retrieval scoring as the predictive layer over the archive
Agentic execution
LLM generation grounded in retrieved citations, not free invention
Secure data
Vector store and embeddings stay on-prem; no data leaves the perimeter
Actionable outcomes
Cited answers staff can hand to a regulator without rework
[ TECH STACK ]
[ IMPACT ]
Local
Vector store and embeddings stay on-prem
Cited
Every answer points to its source PDF and page
Streaming
Real-time response generation
[ NEXT STEP ]
See Askive in your data.
[ READY FOR YOUR STORY? ]