<NP/>
Loading LLM modules... [████████] 100%
Connecting vector database... [████████] 100%
Initializing neural network... [████████] 100%
SYSTEM ONLINE

> PROJECTS.DEPLOYED

Production AI systems shipping real value

LIVE2022 → 2025 (when speed was everything, still is)

HYBRID_RECSYS

Sub-100ms recs • collaborative + vector search • e-commerce

EmbeddingsSemantic RankingVector SearchCollaborative Filtering
Response Time<100ms
LIVE2024 → Present (agents doing the heavy lifting)

DEV_VELOCITY_MCP

SSOT via Confluence+Slack+Jira → AI coding assistants

ClaudeGeminiLangGraphMCP
Team Velocity+60-70%
LIVE2024 (because humans hate writing JSON-LD)

GEO_SEO_ENGINE

Auto-gen product content • FAQs • JSON-LD • multilingual

OpenAIFastAPIKnowledge GraphsNLP
Time Saved80%
LIVE2023 → 2025 (plot twist: now with graphs)

LEGAL_RAG_v2

100K+ docs • Neo4j knowledge graph • cross-citation

LangChainNeo4jPineconeGPT-4
Retrieval Accuracy91%
Answer Relevance89%
LIVE2023 (teaching computers to shop)

VISION_CLASSIFY

CNN page classification • image similarity • product discovery

PyTorchQdrantTransfer LearningONNX
Full Automation100%
LIVE2023 → 2025 (RAG got an upgrade)

HR_ASSISTANT

RAG-powered HR assistant • vector search • Supabase

LangChainSupabaseRAGVector Search
Query Accuracy+45%

> TECH.ARSENAL

Production-grade stack for enterprise AI

OpenAI

95%

GPT-4, GPT-4o, o1, o3

Claude

95%

Anthropic Claude API, Sonnet, Opus

Gemini

90%

Google Gemini Pro, Flash

LangChain

95%

Chains, Agents, Tools

LangGraph

95%

Multi-Agent Orchestration

MCP

90%

Model Context Protocol

RAG

95%

Hybrid Search, Knowledge Graphs

Prompt Engineering

95%

Advanced prompting, few-shot, CoT

Function Calling

90%

Tool use, structured outputs

GEO & SEO AI

85%

Generative Engine Optimization

> SYSTEM.INFO

Background and credentials

> Bio

AI-focused Software Engineer and AI Unit Lead with 4+ years of experience in NLP, RAG architectures, Generative AI, and Computer Vision. Led a team of 5+ engineers delivering 10+ enterprise AI solutions. Expert in production-grade multi-agent systems, advanced RAG pipelines, and GEO/SEO AI optimization for e-commerce. Proven track record reducing manual workflows by up to 100% and boosting developer productivity by ~60-70% through AI-powered automation and multi-agent orchestration.

> Mission

"Building AI that ships, not just demos."

> Work Experience

Head of Artificial Intelligence Business Unit

S.I. 2001 SpA

Bergamo

Apr 2021 – Present
Team: 5+ engineers
Projects: 10+ enterprise AI solutions
  • ▸Led and scaled an AI team of 5+ engineers, managing high-impact AI/ML projects for enterprise clients using Agile/Scrum methodologies
  • ▸Owned end-to-end delivery of 10+ AI solutions, driving automation efficiencies and improved customer experience across legal, e-commerce, industrial, and HR domains
  • ▸Architected multimodal RAG systems across legal, industrial, and e-commerce domains, implementing hybrid search (semantic + lexical), knowledge graphs (Neo4j), domain-specific embeddings, and vector databases (Pinecone, Qdrant, Weaviate)
  • ▸Designed and deployed LLM-powered AI agents automating business workflows using LangGraph, LangChain, OpenAI Function Calling, and MCP, implementing reliability layers including guardrails, fallback policies, and human-in-the-loop escalation
  • ▸Architected MCP-based integrations connecting Confluence, Slack, and Jira as Single Source of Truth (SSOT), enabling AI coding assistants (Claude Code, Cursor) to access real-time project context and improving team development velocity by ~60-70%
  • ▸Developed AI-powered product feed optimization pipelines using latest OpenAI models for GEO (Generative Engine Optimization) and SEO discoverability, reducing content optimization time by ~80%
  • ▸Developed and fine-tuned CNN-based computer vision models using transfer learning and custom architectures, integrated AI workflows into production using FastAPI microservices, Docker, and Azure AKS with monitoring pipelines tracking latency, cost, and success rates

> Education

Master's Degree in Computer Engineering

Università degli Studi di Bergamo

Bergamo

Sep 2019 – Mar 2022

Summa cum laude (110/110 with honors)

Extraction of Semantic Topological Maps from 2D Occupational Maps

Developed algorithms for semantic topological mapping to improve robot navigation through graph-based spatial representations.

Bachelor's Degree in Computer Engineering

Università degli Studi di Bergamo

Bergamo

Sep 2016 – Dec 2019

Iridology Analysis Using Computer Vision for Eye Feature Detection

Applied computer vision for automated iris analysis, implementing feature extraction for pattern and anomaly detection.

> Hobbies

●Tattoos
●JDM Cars
●Guitar solos nobody asked for

> Languages

ItalianNative
EnglishProfessional

Location: Bergamo, Italy[45.6945, 9.67]

> CONNECT.INIT

Let's build something together

contact_terminal.sh

$ ./initiate_connection.sh --mode=contact

> PROTOCOL: EMAIL

nicholasprevitali96@gmail.com
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> PROTOCOL: LINKEDIN

LinkedIn Profile
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> PROTOCOL: GITHUB

GitHub Profile
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> PROTOCOL: GITLAB

GitLab Profile
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ENCRYPTION:TLS_v1.3 [SECURE]
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