Documents & KnowledgePhase 3 — Build
Multimodal RAG for Financial Documents
Financial PDFs contain tables, charts, and precise numbers that pure text-RAG misses — answers come back confidently wrong.
What we build
- 1Two-stage pipeline: text extraction + image extraction with semantic chunking that preserves table context
- 2Hybrid search combining keyword precision (SWIFT, IBAN, dates) with semantic similarity
- 3GPT-4o multimodal answers with page-number citations and inline figure references
Timeline
6–8 weeks
Price band
Enterprise only
Enterprise $90k–$220k
Sustainment
$5k–$18k / mo
Technology stack
Azure AI SearchAzure AI VisionGPT-4oHybrid SearchPython
Reference metrics
94.2%
Text Accuracy
91.8%
Chart Understanding
100%
Citation Coverage
2.1s
Query Latency
Paired course
AI in Financial Services
Note: Reference architecture from prior banking work — code transferable to client tenant.
Ready to scope this PoC?
Book a 30-minute discovery call. We’ll write a fixed-scope, fixed-price proposal within 5 working days.