Consultor RAG Empresarial Madrid · Knowledge Base privada B2B

Consultor RAG Empresarial Madrid · Knowledge Base privada B2B con embeddings + vector DB + LLM (Claude/GPT-4). Cronuts.digital senior accountability Madrid en modelo híbrido remoto + sprints presenciales. RAG production-grade compliance EU GDPR + casos uso customer support/sales enablement/legal Q&A.

Servicio Consultor RAG Empresarial Madrid · qué incluye

  • RAG architecture design · embeddings + vector DB + LLM + orchestration.
  • Ingestion pipeline · Notion + Drive + SharePoint + Confluence + tickets + CRM.
  • Vector DB setup · Pinecone (managed) / Qdrant (self-hosted) / pgvector EU.
  • LLM integration · Claude 3.5 Sonnet / Opus 4 + GPT-4o backup + routing layer.
  • Eval framework · golden dataset + accuracy/recall/F1 + LLM-as-judge.
  • Governance + audit logs · GDPR + EU AI Act compliance.
  • Maintenance retainer · re-embedding + eval iteration + new use cases.

Qué es RAG · Retrieval Augmented Generation

RAG combina retrieval information (vector DB) con generación LLM para responder consultas sobre knowledge base privada sin fine-tuning. Citations auditables + update real-time + privacidad preservada. Ver detalle RAG glossary.

Casos uso B2B canónicos

  • Customer support tier-1 agent · responde docs + tickets + product KB. 24/7 SLA.
  • Internal knowledge assistant · empleados consultan políticas + procesos + onboarding.
  • Sales enablement · SDR/AE pregunta sobre product + pricing + competitor + case studies.
  • Compliance Q&A · legal team consulta sobre RGPD + contracts library + jurisprudence.
  • Marketing content ops · briefing + research desde KB + competitive intel.
  • HR knowledge base · employee Q&A políticas + benefits + procedures.

Stack RAG B2B mid-market canónico

  • LLM · Claude 3.5 Sonnet (default) / Opus 4 (complex reasoning) / GPT-4o (backup).
  • Embeddings · voyage-large-2 / text-embedding-3-large.
  • Vector DB · Pinecone (managed cloud) / Qdrant (self-hosted EU) / pgvector (Postgres extension).
  • Orchestration · LangChain / LlamaIndex / custom Python.
  • Ingestion · Unstructured.io / custom parsers per source.
  • Reranking · Cohere Rerank / Voyage Rerank-1.
  • Hosting · AWS Frankfurt / Azure West Europe / on-premise GPU según compliance.

Eval framework mandatory

  • Golden dataset · 50-200 input-output pairs validated humanly.
  • Accuracy metric · % responses correct factualy.
  • Recall metric · % relevant chunks retrieved.
  • Faithfulness · % response grounded in retrieved context (no hallucination).
  • LLM-as-judge · secondary LLM scores response quality.
  • Regression testing · cada cambio pipeline re-ejecutar eval.

Compliance EU GDPR + EU AI Act

  • Data residency EU · vector DB + LLM en EU jurisdiction (AWS Frankfurt / Azure West Europe).
  • DPA con Anthropic/OpenAI Enterprise · no training on customer data.
  • Encryption at rest + transit · TLS 1.3 + AES-256.
  • Access control + audit logs · cada query logged + retention controlled.
  • PII detection + masking · Presidio Microsoft / custom regex en ingestion.
  • Right to erasure (GDPR Art. 17) · embedded user data removable on request.

Resultados típicos RAG B2B

  • -40% tiempo respuesta customer support.
  • 24/7 SLA tier-1 ticket resolution.
  • -60% horas onboarding empleados · self-serve Q&A.
  • +30% sales enablement velocity · SDR/AE acceso instant case studies + product info.
  • Payback 4-7 meses · según volume queries + horas humanas ahorradas.

Precios transparentes

  • Setup PoC RAG · 8.500-15.000€ proyecto inicial (1 caso uso).
  • Production stack RAG · 15.000-25.000€ proyecto (multiple sources + governance).
  • Retainer integrado · 2.500-5.500€/mes (re-embedding + eval + maintenance).
  • RAG Privado Empresarial premium · 5.600€ pago único 60d a producción · ver RAG Privado Empresarial.
  • Hosting + LLM tokens · 200-2.000€/mes según volume queries.

FAQ Consultor RAG Madrid

¿RAG o fine-tuning B2B?

RAG default para knowledge base evolutiva (update real-time + citations auditables). Fine-tuning para tone/style fix + reduce token cost high-volume queries. Híbrido común enterprise: fine-tune base + RAG knowledge layer.

¿Cuánto tarda RAG production B2B?

PoC 4-6 semanas. Production deployment +6-12 semanas (compliance + audit logs + eval framework). Total 12-20 semanas mid-market production-grade.

¿Cumple EU AI Act + GDPR?

Sí mandatory. Stack EU residency (Frankfurt/Azure West Europe) + DPA Anthropic/OpenAI Enterprise + encryption + audit logs + PII detection + right to erasure GDPR Art. 17.

¿RAG B2B Madrid sin eval framework? Diagnóstico digital gratuito →