You will get a private local AI system with zero cloud dependencies
Rising Talent
Rising Talent
Project details
Need AI that processes sensitive documents without data leaving your infrastructure? I build 100% local AI systems — no cloud, no external APIs, no data leakage.
I built exactly this for a US tax/compliance client: 50+ IRS documents, Ollama + Qdrant + FastAPI, deployed in Docker. PII never leaves the machine. Three-layer isolation (database, API, UI).
What you get: local LLM (Ollama), vector database (Qdrant), FastAPI backend with streaming, Docker containerized. Works on your hardware, zero cloud dependencies.
Perfect for law firms, tax/accounting, healthcare (HIPAA), or any business where data privacy is non-negotiable.
Public reference: github.com/egtimer/fastapi-rag-lab (79 tests, 6 ADRs, RAGAS evaluation pipeline).
I built exactly this for a US tax/compliance client: 50+ IRS documents, Ollama + Qdrant + FastAPI, deployed in Docker. PII never leaves the machine. Three-layer isolation (database, API, UI).
What you get: local LLM (Ollama), vector database (Qdrant), FastAPI backend with streaming, Docker containerized. Works on your hardware, zero cloud dependencies.
Perfect for law firms, tax/accounting, healthcare (HIPAA), or any business where data privacy is non-negotiable.
Public reference: github.com/egtimer/fastapi-rag-lab (79 tests, 6 ADRs, RAGAS evaluation pipeline).
Machine Learning Tools
Python, PyTorch, Tesseract OCRWhat's included
| Service Tiers |
Starter
$800
|
Standard
$1,500
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 5 |
Number of Scenarios | 1 | 5 | 10 |
Number of Graphs/Charts | 0 | 0 | 2 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
Frequently asked questions
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AG
Ander G.
May 4, 2026
AI Automation Specialist (n8n + Database + Web Form Automation) – Long-term collaboration possible
About Eduardo
AI Engineer | RAG, LLM Fine-Tuning & Document AI | Production Systems
Santa Cruz de Tenerife, Spain - 10:03 pm local time
Production track record:
US tax compliance RAG over 50+ IRS documents — 100% local Docker, zero cloud, hybrid retrieval (Recall@5 0.98 benchmarked on a 270-point golden dataset, RAGAS metrics)
Spanish legal form automation — OCR + LLM extraction + n8n workflows reducing manual completion time 75–90%
As AI Tech Lead at Icod Systems — multilingual document classification (IT/ES/EN), LoRA/QLoRA fine-tuning with +25–40% accuracy on domain tasks
Currently AI Engineer in the in-house AI department of a multinational (Verisure – Securitas Direct).
See Portfolio for two public production repos:
fastapi-rag-lab: 9 retrieval configs benchmarked, 79 tests, Langfuse tracing, 6 ADRs
agentic-sql-assistant: LangGraph agent, autonomous tool calling, 138 tests
Best fit if you need:
RAG over your documents (legal, tax, compliance)
Document automation: OCR + LLM extraction + workflow integration
Local/private LLM deployment (Ollama, Qdrant) for data sovereignty
Production discipline: golden datasets, evaluation, observability
Stack: Python, FastAPI, Qdrant, Ollama, OpenAI/Anthropic API, LangGraph, Hugging Face, Docker, n8n, Tesseract/PaddleOCR.
Native Spanish, professional English. Available 15–25 hrs/week for long-term engagements. Based in Tenerife (UTC+0/+1, full EU overlap, US morning overlap).
Steps for completing your project
After purchasing the project, send requirements so Eduardo can start the project.
Delivery time starts when Eduardo receives requirements from you.
Eduardo works on your project following the steps below.
Revisions may occur after the delivery date.
Assess your hardware, documents, and compliance requirements
Deploy local LLM (Ollama) and vector database (Qdrant) in Docker