iM Global Partner
AI RFP - Automated requests for proposals
On-premise AI platform for automatic RFP processing for a global asset manager ($38B AUM). RAG architecture, Mistral-Nemo, structured extraction and contextualized generation.
AI integration + On-Premise MVP - June 2024 - March 2025
assets under management
RFPs processed
success rate
of development
100% sovereign
Automating RFPs
in asset management
For a global asset manager handling $38 billion, each request for proposal represents hours of manual compilation. RAG AI transforms this process by generating contextualized responses in minutes, with precision and consistency impossible to achieve manually.
Sovereign AI
Mistral-Nemo 12B deployed locally with 128K token context. Complete RAG architecture: vector embeddings, semantic retrieval, few-shot generation. No financial data leaves iMGP servers.
Measurable business impact
+50% volume of RFPs processed and +30% success rate on proposals. AI standardization ensures response consistency across 16 global offices.
End-to-end AI pipeline
Document RAG
RAG (Retrieval-Augmented Generation) architecture: vectorization of historical RFP documents, semantic matching with financial products and investment strategies.
Contextualized generation
Automatic generation of RFP responses contextualized by product, geography and strategy. Advanced prompt engineering (few-shot, chain-of-thought).
Structured extraction
Automatic extraction of investment parameters into structured JSON: ticket, asset class, geography, horizon, ESG constraints, expected track record.
On-Premise deployment
100% on-premise infrastructure with Mistral-Nemo (12B, 128K context). No data leaves iMGP servers. Full GDPR and financial regulation compliance.
Before / After AI
| Metric | Before (manual) | After (AI RAG) |
|---|---|---|
| Volume of RFPs processed | Baseline | +50% |
| RFP success rate | Baseline | +30% |
| Compilation time per RFP | Several days | A few hours |
| Cross-site consistency | Variable | AI-standardized |
| Data security | Third-party cloud | On-Premise 100% |
From audit to AI pipeline
9 months to design, deploy and optimize an on-premise AI solution that transforms the RFP process of a global asset management leader.
RFP process analysis
Audit of existing RFP response workflows. Identification of bottlenecks and AI automation opportunities.
RAG architecture
Design and deployment of the RAG architecture: vectorization of historical RFPs, embeddings, semantic retrieval pipeline.
On-premise MVP
Local deployment of Mistral-Nemo 12B. Integration of the complete pipeline: extraction, matching, generation, human validation.
Optimization & production
Prompt fine-tuning, few-shot calibration on validated responses. Production deployment with success metrics monitoring.
Stack & Infrastructure
Artificial Intelligence
Back-End
Infrastructure
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On-premise AI, document RAG, business process automation - we have the expertise to deploy artificial intelligence in the most demanding environments.