logika.studiologika.studio

About Us

The human mind and AI force behind logika.studio

Our Operating Model

logika.studio is an Italian AI-augmented digital studio: one senior human owner coordinates swarms of specialized AI agents to deliver software, AI and algorithmic trading with boutique quality and 3-5× faster turnaround than a traditional agency.

How We Work

A linear, transparent five-stage process with a single human point-of-contact from start to finish.

  1. 01

    Discovery

    30-min call, requirement analysis, measurable goals and technical roadmap.

  2. 02

    Design & Architecture

    Visual prototype, design contract and data-first architecture built for the long run.

  3. 03

    AI-augmented Build

    Parallel development with specialized agents (dev, QA, ops) coordinated step by step.

  4. 04

    Human Review

    Every commit, test and UX gets reviewed manually before shipping to production.

  5. 05

    Deploy & Iterate

    Automated deploy (Vercel / AWS), live monitoring and rapid iteration on feedback.

What Makes Us Different

3-5×
Execution speed

Parallel AI pipelines drastically cut delivery time compared to traditional teams.

1
Single point-of-contact

One senior person to talk to — no account manager, no email chain, same-day decisions.

100%
Human-reviewed

Every AI output goes through human review: senior quality, zero blind outputs in production.

Frequently Asked Questions

Who checks the quality of the work produced by AI agents?+

Every output — code, copy, design, tests — is manually reviewed by the founder before delivery. No line of code reaches production without passing through expert human eyes.

What does the human do and what does the AI do?+

The human defines strategy, architecture, tone and quality standards, then supervises every output. AI agents execute repetitive or high-volume tasks in parallel (coding, refactoring, testing, research), amplifying operational capacity without diluting senior judgment.

Does the client own the code?+

Yes, always. The client gets full ownership of the source code, technical documentation and infrastructure, with full portability across any cloud provider.

Stack & Technologies

Next.jsReactTypeScriptNode.jsPythonC#/.NETRustRFastAPILangChainLangGraphPydantic AIMCPQdrantpgvectorPolarsNumPySciPyStatsmodelsProphetCCXTSupabasePostgreSQLDockern8nOllamaVercelAWSSelf-hosted / On-premiseLLM (OpenAI, Anthropic, Gemini, Mistral, Groq)

The Founder

Luigi Garone, fondatore logika.studio

Luigi Garone

Founder & AI Orchestrator

Luigi Garone is the founder of logika.studio, an AI-augmented digital studio based in Italy. A data scientist and full-stack developer, he combines two roles that usually sit in separate teams: the statistical analysis of data and the engineering that puts that data to work.

For SMEs and startups he builds custom web apps and business systems, SaaS platforms, native iOS and Android apps, AI integration, IoT monitoring with predictive maintenance, and data-driven digital marketing. For training providers, public bodies and funded programmes he builds complete e-learning platforms and MOOCs, from the platform itself to video course production — script, voice and video generated with AI. For trading houses, trading rooms and banking institutions he builds algorithmic trading, analytical platforms and high-frequency trading (HFT) systems.

Expertise

Background in statistics, data mining and quantitative research: statistical modelling and inference, pattern extraction from large volumes of data, time series, machine learning and data pipelines (Polars, NumPy, SciPy, Statsmodels, Prophet, HMM, FFT/Goertzel, DSP and spectral analysis), with rigorous validation — no lookahead, no results that can't be reproduced.

On the engineering side: multi-language full-stack (Next.js, React, TypeScript, Node.js, C#/.NET, Rust, Python, R), mobile with React Native and Expo, PostgreSQL/Supabase databases, Docker and CI/CD, deployed on cloud, hybrid or on-premise. He architects production-ready AI systems: RAG pipelines with vector DBs (Qdrant, pgvector) and embedding models, multi-agent systems (LangChain, LangGraph, Pydantic AI), fine-tuning of open-source LLMs, integration of Claude, OpenAI, Gemini, Mistral and Groq, custom MCP (Model Context Protocol) servers, n8n workflow automation and local inference with Ollama.

Approach

Every project is handled personally: discovery, architecture, code review, delivery. No chain of intermediaries, no account manager — a single point of contact from idea to go-live. It's the method of quantitative research applied to digital products: hypothesis, measurement, validation. Decisions are made on numbers, not impressions.

Full-stack Data Science AI Engineering Quant Research
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