You will get Enterprise & Business AI Automation
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Project details
Are manual processes, duplicate data entry, and slow response times taxing your operations? Up to 30% of weekly payroll is lost to manual data movement across disconnected platforms.
This service eliminates operational bottlenecks by building resilient, AI-driven workflow automations tailored to your business stack. Rather than basic, fragile Zapier triggers that fail silently, production-grade automation engines are engineered using n8n or Make, integrated directly with Large Language Models (OpenAI GPT-4o, Anthropic Claude 3.5) and your core apps (CRMs, databases, email, and messaging platforms).
This service eliminates operational bottlenecks by building resilient, AI-driven workflow automations tailored to your business stack. Rather than basic, fragile Zapier triggers that fail silently, production-grade automation engines are engineered using n8n or Make, integrated directly with Large Language Models (OpenAI GPT-4o, Anthropic Claude 3.5) and your core apps (CRMs, databases, email, and messaging platforms).
AI Development Type
Deep Learning, Model TuningAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$4,000
|
Advanced
$8,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 30 days |
Number of Revisions | 3 | 6 | 9 |
AI Model Integration | - | ||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | |
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - |
Frequently asked questions
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AR
Alex Siro R.
Sep 3, 2024
AI Embedding Search
It was amazing to work with Marcelo! He knows how to solve the problem that you are facing! I recommend him to everyone!
SN
Steven N.
Jul 4, 2024
Misspelling detection in keywords
SN
Steven N.
Jul 4, 2024
Image Matching
Marcelo delivered an excellent solution to a difficult problem
MN
Mohamed N.
Aug 8, 2023
Feature extraction for small dataset
MN
Mohamed N.
Aug 8, 2023
Feature extraction for BOT Dataset
About Marcelo H
AI Systems Engineer | Agentic Systems, Production RAG | Python
100%
Job Success
Ciudad Autonoma de Buenos Aires, Argentina - 8:42 pm local time
Senior Systems Engineer focused on building production-grade AI-powered software systems. I work with AI, Agentic AI, Python, FastAPI, Docker, AWS/Azure, MongoDB, SQL, vector databases, LLMs, RAG pipelines, agentic workflows, NLP, and machine learning.
Most corporate AI initiatives fail not because the models are weak, but because prompt architectures hallucinate, API token budgets spiral out of control, and unmonitored production pipelines crash without failure recovery layers.
I close that exact execution gap. I don’t build generic prototypes or fragile low-code workflows. I design resilient, test-driven autonomous software engines optimized for total system stability, cost reduction, and zero data loss.
🛡️ What I Build to Protect Your Bottom Line
• Autonomous Multi-Agent Swarms — Orchestrate rule-based and adaptive multi-agent teams using LangGraph and LangChain to automate complex corporate knowledge funnels.
• Production-Grade RAG Systems — Dual-search indexes (Structured MongoDB + Semantic Pinecone/Weaviate) that safely reference proprietary documentation without hallucinations.
• High-Volume Data Pipelines — Scalable web scrapers and streaming ingestion daemons running 24/7 on AWS/Azure, fully containerized in Docker.
• Automated Deep-Research Content Platform → 500+ articles/month • 99% factual accuracy • Zero manual intervention
• Multi-Agent Corporate Assistant → 36% latency reduction • 50+ concurrent users • Sub-2s response times
• Legal Data Mining & Analytics (Victoria AI) → 300% faster document review • 500+ docs/month • 40% ticket deflection
🔧 Uncompromising Engineering Quality
Every system ships with: ✅ Codebase Private Repository ✅ 250–390+ automated unit & integration tests (pytest, CI/CD) ✅ Architectural diagrams (Mermaid/Excalidraw) ✅ Migration runbooks — next engineer maintains it effortlessly ✅ Observability — LangSmith/Logfire monitoring, structured logging, alerting ✅ Dockerized deployments (AWS, Azure, GCP)
🤝 How I Work
• Clean, maintainable code — typed, linted, documented • Clear communication — no jargon, regular syncs • Realistic estimates — fixed-scope pilots before retainers • Production mindset — monitoring, rollback, disaster recovery built in
🎯 Let’s Map Your Build
Click “Message” or “Invite to Job” for a free 30-minute AI system design consultation — I’ll give you a clear blueprint.
Engagements: Paid Discovery ($500) → 2-Week Pilot ($3–5K) → Monthly Retainer ($8–15K/mo) Capacity: Limited to 3 concurrent clients
Steps for completing your project
After purchasing the project, send requirements so Marcelo H can start the project.
Delivery time starts when Marcelo H receives requirements from you.
Marcelo H works on your project following the steps below.
Revisions may occur after the delivery date.
Onboarding & Discovery Call
We align on requirements, review your manual workflow, verify API credentials, and map system logic during a kick-off call to build a rock-solid blueprint before coding.
Workflow Engineering & Delivery
We develop custom n8n/Make automation engines, integrate APIs & LLMs (OpenAI/Claude), implement error handling, and test with real data to ensure maximum reliability.