IT consulting
Modern architectures, cloud, system integration, security and operational continuity: technical decisions explained in management language, with explicit trade-offs.
- Architecture review
- Cloud migrations
- Security & DR
Curi SRL · Lecce · Italy
We build the software
your business deserves.
>_ code is law
IT consulting, technology innovation and governed AI solutions. We bring a method proven across startups and scale-ups to the territory, with CuriStack as the operating backbone — patented software and registered trademark.
- AI Act-ready approach
- Traceable decisions
- CuriStack — registered trademark
- 0% Decisions translated into code, tests and verifiable controls.
- 0 No demo for the demo's sake: every POC is measurable, every release defensible.
- 0 One method, CuriStack, from discovery to maintenance.
- 0h Average first-response time to email enquiries.
01 — What we do
Four pillars, one method.
We support SMEs, corporates and product teams that need to accelerate without losing control over quality, security and compliance. Our vocabulary is the one of outcomes, not the one of tech fashion.
Technology innovation
Product roadmaps, measurable proofs of concept and knowledge transfer to the in-house team: no demos for the demo's sake, only evidence of value.
- Discovery & POC
- Evolutionary roadmaps
- Technical coaching
AI solutions
Model-assisted applications with verifiable context (RAG), guided automation, continuous output and cost evaluation: useful AI, not self-celebration.
- RAG with citations
- Governed agents
- Evals & drift
Software lifecycle
From discovery to release, with traceability and acceptance: when audits, compliance or handover come, the technical perimeter is already defined and defensible.
- End-to-end SDLC
- Audit-ready
- Clean handover
02 — The method
CuriStack ties product, AI and governance together.
Patented software and methodological framework, registered trademark: it orchestrates requirements, implementation, quality and deployment, including the role of AI where it boosts productivity and clarity, always with accountability and versioning of deliverables.
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Discovery
Goals, regulatory constraints, available data, risks: the perimeter is defined here, not after the fact.
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Design
Architecture, data model, AI use-case classification: every choice motivated, every alternative weighed.
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Build
Code, infrastructure, models and agents: consistent production with verifiable automation where useful.
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Quality
Tests, evals, hardening, component audits: quality that is measured, not declared.
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Operate
Drift and cost monitoring, maintenance cycles, clean handover to in-house teams or vendors.
- One thread from “what” to “how we measure value”.
- Policies and procedures translated into verifiable automation where it makes sense.
- Internal teams and vendors aligned on the same operating model.
03 — Why us
Founder mindset, engineering rigour.
We are an SRL based in Lecce, led by local entrepreneurs with a decade of experience, founders of multiple startups and with an exit behind them. We know how to run — and how to formalise.
Speed with method
We know MVPs, fundraising, scale-ups and exits: we keep the same pace while making traceability and perimeter explicit.
Measurable trust
Clear roadmaps, declared risks, shared metrics: the goal is not to impress with the vocabulary of tech fashion.
Local, but global
Roots in Salento, projects distributed across Italy and abroad: structured remote teams and documented governance.
04 — Manifesto
Build for failure modes, not just for the demo.
In 2024–2026, AI is not a “module”: it is the orchestration of flows where models, data and tools must coexist with operating limits, human oversight and measurable costs. Whoever builds serious products designs for failure modes, not only for the demo.
Retrieval-augmented generation (RAG) and corporate knowledge bases win when answers are citable, updatable and quality-controlled: less “generic confidence”, more traceability about why an answer is admitted into production.
Continuous evaluation (evals) — quality, latency, stability, budget — is not a dashboard nice-to-have: it's how a team keeps products, risk and roadmap together when models and providers ship a new version every quarter.
With the AI Act and market expectations, compliance and accountability become engineering requirements: use-case classification, documentation, data and vendor governance must be embedded in design. Legal opinions need licensed professionals: we make the technical perimeter defensible.
The attack surface grows: prompt injection, secret leakage, model supply chain and sensitive-data handling require continuous hardening and processes, not a checklist filled in only once the system is already live.
This is where code is law shows its operational meaning: critical policies and decisions translated into code, tests and verifiable controls. With CuriStack we bring this discipline into the software lifecycle, from value definition to commissioning and maintenance.
From Salento to national and international clients, CuriLex is the lab where founder expertise, technical rigour and CuriStack (patented solution, registered trademark) keep prudence and innovation together.
05 — FAQ
Frequently asked questions.
What is CuriStack?
It is the patented software and methodological framework with which we manage the full software development lifecycle, including AI models and agents in a traceable and measurable way. CuriStack is a registered trademark.
What does «code is law» mean for CuriLex?
Critical decisions translated into code, tests and verifiable controls: less ambiguity between business, legal and engineering once the system is in production.
Do you only work in Apulia?
Headquarters and roots in Lecce; projects distributed across Italy and abroad with structured remote teams and clear governance.
How do we get started together?
An alignment session on goals, risks, available data and regulatory constraints; then we propose a measurable scope of work — often a POC — before scaling.
How do you handle compliance and risk in the AI Act era?
Governance as a product requirement: use-case classification, documentation, impact assessment where required, decision traceability and controls over data and models. We do not replace legal advisors: we embed regulatory constraints into technical design.
Which risks do you mitigate around AI agents, RAG and the model supply chain?
Operating limits and human oversight on agents, citations and source verification in document retrieval, drift and cost monitoring, data segregation and prompt-injection mitigations; where useful, review of model components and versions.
06 — Contact
Ready to build something defensible?
Tell us the problem in a few lines: risks, regulatory constraints, data on hand. We'll reply with a clear scope of work — not a generic proposal.