Néstor Martínez
  • RAG
  • CRM
  • WhatsApp
  • 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 and a personal AI assistant living in each advisor's own WhatsApp.

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 → WhatsApp
CRM syncAdvisor portalCRM pipelineTrainingRAG assistantProduct RAGpgvectorWhatsApp agentagenda + queriesSupabasePostgres

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.
  • Personal WhatsApp agent per advisor: runs on the advisor's own number via Evolution API — answers clients on their behalf with access to the knowledge base, books meetings into their calendar, handles first-line attention.

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 · Evolution API (WhatsApp) · n8n