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Free Audit β†’
RAG Pipeline Architecture: Query β†’ Embedding β†’ Vector DB β†’ Context Ranking β†’ LLM β†’ Response

Is Your Chatbot Giving Generic Answers?I'll Help You Implement Production-Ready RAG Systems in 8 Weeks

72% of RAG implementations fail within the first year. I guarantee success with production-ready architecture from day 1.

πŸ“… Schedule 30-min DemoπŸ’¬ Talk to Expert
72%
Industry Fail Rate
(Production-ready architecture prevents this)
99.95%
Guaranteed Uptime
6-8
Weeks to Production
AWS Certified
Azure AI Engineer
Production-Ready

The Problem: Your Chatbot Costs €5k/month and Frustrates Customers

While you pay thousands in AI tools, your customers keep waiting for answers that never come

Comparison generic chatbot vs RAG: generic answers without context vs specific answers with verified sources
❌

Incorrect Answers

  • β€’40% of queries without relevant answers
  • β€’Frustrated customers abandon
  • β€’Cost: 150 human support tickets/day
🚫

Zero Business Context

  • β€’No access to your internal documentation
  • β€’Generic ChatGPT answers
  • β€’Cost: 30% conversion loss
β›”

Impossible to Scale

  • β€’Adding new info = retraining model
  • β€’Cost: $8k each update
  • β€’Time: 3-4 weeks

The Real Cost of an Inefficient Chatbot

$900/day
60 tickets Γ— $15 human support
$180k/year
30% lost conversions
$24k/year
Manual engineering updates

Total: $25k/year in direct losses

The Solution: RAG Systems That Learn From YOUR Documentation

I Transform Your Corporate Data Into Intelligent and Reliable Answers

3 RAG Components: Retrieval (95% recall), Ranking (40% faster), Generation (85% accuracy)
1

Ingest

Your Docs β†’ Vector DB

(Automated)

2

Retrieve

Query β†’ Relevant Context

(Real-time)

3

Generate

Precise Answer + Sources

(Verifiable)

66% Ticket Reduction

Verified Salesforce real case

Verifiable Answers

Cites documentation sources

Instant Updates

Add doc, available in minutes

Predictable Cost

$500-2k/month vs $8k retraining

4 Use Cases with Proven ROI

Real timelines, verifiable results

Customer Support RAG Dashboard: 1,247 tickets resolved (72%), resolution time 4.2 min (-66%), CSAT 4.8/5
πŸ’¬

Customer Service Chatbot

For: SaaS, E-commerce ($10k+ MRR)

Pain: 200+ daily tickets, 4h response time

Solution: RAG with FAQs + docs + historical tickets

ROI:

50% ticket reduction = $45k/year savings

Price

From $8k

Timeline

6 weeks

RAG Knowledge Base Interface: 342 indexed product documents with vectorized chunks
πŸ₯

Healthcare Knowledge Assistant

For: Hospitals, Clinics, HealthTech

Pain: Slow access to medical knowledge base

Solution: RAG with EHR + HIPAA-compliant guidelines

ROI:

30min β†’ 2min search = 300h/month savings

Price

From $12k

HIPAA premium

Timeline

8 weeks

πŸ’³

Financial Compliance Bot

For: Banks, Fintech, Investment Firms

Pain: Regulations change weekly

Solution: RAG tracking real-time regulatory updates

ROI:

Avoid 1 fine = $150k+ saved

Price

From $15k

Timeline

10 weeks

🏒

Enterprise Knowledge Management

For: Corporate 500+ employees

Pain: Info scattered across Confluence/SharePoint/Slack

Solution: RAG unifying all systems

ROI:

20min β†’ 2min search = 5,000h/month

Price

From $10k

Timeline

8 weeks

Want to see the detailed plan for YOUR case?

Download my project template with timeline and estimated costs

Your Project in 6 Clear Steps (6-8 Weeks Total)

Total transparency: what I do, what I need from you, what deliverables you receive

RAG implementation timeline: Week 1-2 Discovery, 3-4 Build, 5-6 Testing, 7-8 Launch with deliverables
1-2

Discovery & Architecture

I handle:

  • β€’ Audit existing documentation
  • β€’ Design RAG architecture
  • β€’ Vector DB selection

You provide:

  • β€’ API/docs access
  • β€’ Requirements clarification

Deliverables:

  • βœ… Architecture doc
  • βœ… Project timeline
3-4

MVP Development

I handle:

  • β€’ Setup vector database
  • β€’ Embeddings pipeline
  • β€’ LLM integration (GPT-4/Claude)

You provide:

  • β€’ Review test results
  • β€’ Accuracy feedback

Deliverables:

  • βœ… Functional MVP staging
  • βœ… Interactive demo
5

Integration & Testing

I handle:

  • β€’ API development
  • β€’ Integrate existing systems
  • β€’ Test accuracy + performance

You provide:

  • β€’ UAT testing
  • β€’ Edge case scenarios

Deliverables:

  • βœ… Production-ready API
  • βœ… Test report
6

Deployment & Training

I handle:

  • β€’ Production deployment with CI/CD
  • β€’ Monitoring setup (Grafana)
  • β€’ Team training

You provide:

  • β€’ Initial user feedback
  • β€’ Production credentials

Deliverables:

  • βœ… Live system
  • βœ… Complete documentation
7-8

Optimization

I handle:

  • β€’ Fine-tuning prompts
  • β€’ Cost optimization
  • β€’ Performance tuning

You provide:

  • β€’ Real user feedback
  • β€’ Production metrics review

Deliverables:

  • βœ… Optimized system
  • βœ… Performance report

Post-Launch: Ongoing Support

Ongoing support available:

  • βœ“ New features implementation
  • βœ“ Continuous optimization
  • βœ“ 24/7 monitoring & alerts
  • βœ“ Cost optimization ongoing
  • βœ“ Priority technical support
  • βœ“ Monthly performance reviews

Production-Grade Technology Stack

Enterprise-ready tools with 99.95% guaranteed uptime

Vector Databases

Pinecone

Managed, 50ms latency, $70/month

Weaviate

Self-hosted, GDPR-compliant

Chroma

Lightweight, perfect startups

LLM APIs

OpenAI GPT-4

Best accuracy, $0.03/1k tokens

Anthropic Claude

Longer context, $0.015/1k

AWS Bedrock

Enterprise, compliance built-in

Cloud Infrastructure

AWS Lambda

Serverless, auto-scaling

S3

Document storage

DynamoDB

Metadata tracking

Frameworks

LangChain

LLM orchestration

LlamaIndex

Data connectors

Haystack

NLP pipelines

Monitoring

Grafana

Real-time dashboards

CloudWatch

Alerting & logs

Custom Metrics

Accuracy tracking

Certifications

AWS DevOps Professional

Azure AI Engineer Associate

Data Scientist Associate

MasterSuiteAI case study: 66% response time reduction, $38.4k/year savings, CSAT 4.8/5

RAG vs Fine-Tuning vs API Calls: Choose the Right Solution

Comparison based on real experience implementing AI solutions in production

Comparison table RAG vs Fine-Tuning vs API Calls: costs, deployment time, accuracy, flexibility

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Complement your RAG system with optimized cloud infrastructure

MLOps & Model Deployment

I implement CI/CD pipelines to deploy custom ML models alongside your RAG system

See service β†’

Cloud Cost Optimization

I reduce LLM API costs (OpenAI, Anthropic) by 30-70% with FinOps audits

See service β†’

Autonomous AI Agents

Evolve RAG to agents that execute automatic actions with LangGraph

See service β†’
← See all services

Ready to Reduce Tickets by 50% in 8 Weeks?

Choose the option that best fits your situation

πŸ“…

Schedule 30-min Demo

See RAG working with YOUR docs. No commitment, 100% technical.

Book Slot β†’

Slots available this week

πŸ’¬

Talk to Expert

+34 631 360 378. Response <24h. Free consultation.

Send WhatsApp β†’

No-commitment consultation

πŸ“₯

Download Checklist

30 points to verify before implementing RAG + cost estimator.

Architecture template included

πŸ”’ No spam guarantee
πŸ“ž Response in 24h
βœ… 100% confidential (NDA available)

Join companies that already reduced tickets 50%+ with production-ready RAG systems.

Related Services

Complement your infrastructure with our specialized AI/ML services

MLOps & Model Deployment

Complete CI/CD pipelines to deploy ML models to production with SageMaker/Vertex AI

Learn more

Cloud Cost Optimization & FinOps

I reduce cloud costs by 30-70% with technical audits and LLM API optimization

Learn more

Autonomous AI Agents

I develop multi-step agents with LangGraph that execute automatic actions

Learn more
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  • MLOps & Deployment
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