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You will get a production-ready RAG pipeline for your codebase or knowledge base

Ignazio D.Status: Offline
Ignazio D. Ignazio D.
Rising Talent
Preview image

Let a pro handle the details

Buy Generative AI services from Ignazio, priced and ready to go.
Ignazio D.Status: Offline
Ignazio D. Ignazio D.
Rising Talent
Preview image

Let a pro handle the details

Buy Generative AI services from Ignazio, priced and ready to go.

Project details

You will get a production-ready RAG (Retrieval-Augmented Generation) pipeline that connects your data sources to a powerful LLM, delivering accurate, grounded answers with source citations — not hallucinations.

I build retrieval pipelines that hold up under real operating conditions. Every system I ship includes proper chunking strategies, embedding pipelines, vector store setup, and a clean FastAPI query interface. I'm not locked into a single AI provider — I work with OpenAI, Anthropic, Mistral, and more.

Whether you need a simple internal knowledge base, a customer-facing Q&A bot, or a multi-source research assistant, I'll design the architecture that fits your actual use case and deliver clean, documented code you can maintain and extend.
AI Algorithms
Large Language Model
AI Applications
Natural Language Understanding
AI Development Language
Python
AI Models
ChatGPT, OpenAI Codex
What's included
Service Tiers Starter
$500
Standard
$900
Advanced
$1,500
Delivery Time 5 days 7 days 10 days
Number of Revisions
123
AI Model Integration
Batch Normalization
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Database Integration
Detailed Code Comments
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Image Upscaling
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MLOps
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Model Deployment
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Model Documentation
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Model Monitoring
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Model Testing & Optimization
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Model Tuning
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Natural Language Processing
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NLP Tokenization
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Pre-Training
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Prompt Engineering
Setup File
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Source Code
Ignazio D.Status: Offline

About Ignazio

Ignazio D.Status: Offline
Software Engineer working on AI systems. Retrieval, agents, evaluation
Padova, Italy - 3:54 am local time
Most AI systems fail somewhere between a working demo and a working system. Retrieval that drifts, agents that don't recover, evaluation that catches nothing. I work in that gap.

I build reliable AI systems for teams that have outgrown the prototype phase: RAG with measurable retrieval quality, agent workflows with persistent state and approval gates, FastAPI backends purpose-built for LLM products, and the evaluation layer most teams skip between prototype and production.

WHAT I DELIVER

Retrieval Contracts for RAG
Hybrid retrieval (pgvector + BM25) with reranking, instrumented end-to-end. Built for the gap between a demo that retrieves and a system that survives the next 10,000 queries.

LLM Agent Infrastructure
Multi-step agent workflows on LangGraph with persistent state, tool orchestration, approval gates, retry logic, and deterministic evaluation.

FastAPI Backends for AI Products
Async FastAPI backends purpose-built for LLM apps. pgvector, Alembic migrations, health checks, and operational readiness on day one.

AI Reliability Engineering
Deterministic evaluation frameworks, structured output validation, cost and latency observability, and regression detection.

Everything I ship runs on four laws: deterministic evaluation (no "it worked when I tried it"), cost control by architecture, latency as a feature, and operational reliability under load and failure.

Tech stack: Python, FastAPI, LangGraph, pgvector, Anthropic Claude API, OpenAI API, React, TypeScript, Next.js, Tauri, Rust, PostgreSQL, Docker.

My work ships as source in your repo, and all my systems are public on GitHub with live deploys. If you need AI systems that actually work in production, let's talk.

Steps for completing your project

After purchasing the project, send requirements so Ignazio can start the project.

Delivery time starts when Ignazio receives requirements from you.

Ignazio works on your project following the steps below.

Revisions may occur after the delivery date.

Discovery & Setup

Review requirements, set up project environment, configure embeddings and vector store.

Pipeline Development

Build ingestion, chunking, embedding, and retrieval layers with the FastAPI endpoint.

Review the work, release payment, and leave feedback to Ignazio.