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Néstor Martínez
  • RAG
  • CRM
  • Copilot
  • Supabase

Sales Advisory Platform — CRM + RAG Copilot for 250+ Financial Advisors

TL;DR: Full platform (CRM + AI copilot) for financial advisory teams that had no system at all — replacing spreadsheets and manual lookups. 248 active advisors on the largest deployment. Includes a RAG engine over insurance policy documents, delivered as an AI copilot built into the platform's web app.

Advisor CRM — full pipeline from lead to signed client, with referral tracking.
Advisor CRM — full pipeline from lead to signed client, with referral tracking.
The RAG assistant answering a product-cost question, with figures pulled from official policy documentation.
The RAG assistant answering a product-cost question, with figures pulled from official policy documentation.
Structured onboarding and training tracks inside the platform.
Structured onboarding and training tracks inside the platform.
One portal, three advisor toolsCRM → RAG → Copilot
CRM syncAdvisor portalCRM pipelineTrainingRAG assistantProduct RAGpgvectorAI copilotinside the portalSupabasePostgres

Context

Two financial advisory teams (Spain and Greece) within a large European financial distribution network ran their entire operation on Google Sheets, Excel and scattered PDFs. Checking what an insurance policy covers meant digging through documents manually — or asking the one admin who knew.

The problem

  • No CRM: client management, advisor onboarding and follow-ups were untracked.
  • Policy questions (coverage, costs, exclusions, product comparison) required manual reading of dense legal documents ("condicionados").
  • Advisors work from their phones, in the field.

What I built

  • CRM platform (React 19 SPA + Supabase): clients, pipeline, advisor onboarding.
  • RAG engine over policy documents: coverage lookup, cross-document comparison and product-vs-product answers, grounded in the actual policy text. Corpus grows as new insurers are added.
  • Coaching knowledge layer: sales and communication books processed into the assistant so it can coach advisors, not just answer policy questions.
  • AI copilot inside the web app: advisors ask it from the platform itself, with access to the same knowledge base, for coverage lookups, product comparisons and sales coaching.
  • WhatsApp assistant per advisor: developed, but not rolled out. The copilot lives in the web app today.

Results

Metric Value
Active advisors (largest team) 248
Second deployment ~15 advisors, growing
Before Sheets/Excel, manual document lookup, no CRM
Policy lookup Minutes of manual reading → seconds, grounded answers

Stack

React 19 · Vite · TypeScript · Supabase (Postgres + pgvector + RLS) · Tailwind/shadcn · TanStack Query · n8n