You will get EU AI Act & AI Governance Assessment (Risk, Annex IV, Controls)
Top Rated
Top Rated
Project details
If you’re looking for a professional AI Act & Governance Assessment, you’re in the right place. I support companies in understanding, assessing, and preparing their AI systems for compliance with the EU AI Act, reducing regulatory risk and enabling safe deployment.
I work with AI providers and deployers, from early-stage products to production systems, delivering clear, actionable compliance roadmaps instead of generic theory.
Services I offer:
✅ AI Act applicability & risk classification
✅ Gap analysis against AI Act requirements
✅ Governance & compliance framework design
✅ Annex IV documentation outline & evidence checklist
✅ Monitoring, human oversight & PII governance guidance
Why work with me?
🔒 Security- and compliance-first approach
🧩 Strong mix of product thinking and AI governance
📄 Clear documentation, audit-ready structure
⏱️ Reliable delivery and pragmatic recommendations
Whether you need a quick gap check, a full governance assessment, or a compliance dossier, I’ll help you move forward with clarity and confidence.
Contact me to discuss your AI system, use case, and compliance goals.
I work with AI providers and deployers, from early-stage products to production systems, delivering clear, actionable compliance roadmaps instead of generic theory.
Services I offer:
✅ AI Act applicability & risk classification
✅ Gap analysis against AI Act requirements
✅ Governance & compliance framework design
✅ Annex IV documentation outline & evidence checklist
✅ Monitoring, human oversight & PII governance guidance
Why work with me?
🔒 Security- and compliance-first approach
🧩 Strong mix of product thinking and AI governance
📄 Clear documentation, audit-ready structure
⏱️ Reliable delivery and pragmatic recommendations
Whether you need a quick gap check, a full governance assessment, or a compliance dossier, I’ll help you move forward with clarity and confidence.
Contact me to discuss your AI system, use case, and compliance goals.
AI Algorithms
Generative Adversarial Network, Large Language Model, Linear Discriminant Analysis, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Radial Basis Function Network, Recurrent Neural Network, Regression Analysis, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Classification, AI-Enhanced Medical Imaging, AI-Generated Code, AI-Generated Music, AI-Generated Video, AIOps, Conversational AIAI Development Language
PythonAI Tools
Azure OpenAI, Bing AI, Gradio, Hugging Face, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
AlphaCode, BERT, BLOOM, ChatGPT, DALL-E, Dolly, GPT-4, GPT-J, GPT-Neo, LaMDA, LLaMA, OpenAI CodexWhat's included
| Service Tiers |
Starter
$997
|
Standard
$3,497
|
Advanced
$9,997
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 20 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | - | - |
Model Documentation | |||
Model Monitoring | - | ||
Model Testing & Optimization | - | ||
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$397 - $2,997
Additional Revision
+$497
AI Inventory & Use-Case Register
(+ 2 Days)
+$597
30-Day Async Q&A Support
+$997
Supplier / Vendor Due Diligence Pack
(+ 2 Days)
+$597Frequently asked questions
4 reviews
(4)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
DT
Dimitris T.
Feb 24, 2026
AI productivity consultant for engineering/dev team (1-hour session)
DS
Davide S.
Feb 15, 2026
Critical bug fix on a platform about to launch on AWS written in node.js
Absolutely a luck sender to solve in a very short time the critical problem.
Directly to the point, without esitation.
Will hire for more work on the same project for fix and build already planned features.
Directly to the point, without esitation.
Will hire for more work on the same project for fix and build already planned features.
MI
Mariia I.
Jan 19, 2026
AI Integration Expert
Claudio is truly an AI Integration Expert. He approached his work meticulously, completed the task efficiently, and provided valuable recommendations.
JS
John S.
Jan 15, 2026
AI Chatbot Development
Claudio, an excellent AI chatbot developer, conducted a detailed review of our current flow and provided a solution.
About Claudio
AI Integration | AI Chatbot Development | Architect | AWS Certified
100%
Job Success
Milan, Italy - 7:06 am local time
Need AI chatbot development, AI integration, or AI automation that delivers measurable ROI (conversion uplift, fewer tickets, faster ops), not a demo?
I’m an AWS-certified engineer and ex co-founder/CTO, so I’m business-oriented by default: every llm, machine learning, api, n8n, AI automation, and ai agent choice is evaluated against KPIs, risk, and cost.
I wrote my first lines of code at 10. By 14, I was already building and selling software online. That “build-it-for-real” mindset is why clients hire me for AI integration and AI chatbot development: I design, implement, harden, and scale production systems end-to-end, and I bring 20+ years of experience doing it.
🧠 Why clients hire me
1️⃣ CTO & Co-founder perspective: every AI integration decision supports product, risk, costs, and ROI.
2️⃣ Production-first engineering: secure api, monitored llm, traceable ai agent, auditable n8n + AI automation.
3️⃣ Outcomes-driven delivery: machine learning + AI chatbot development tied to measurable KPIs.
📈 Proof in outcomes
💳 Nexi (EU payments): AI integration + machine learning recommender + low-latency api → +50% conversion on millisecond checkout flows.
🧾 Accountants copilot: AI chatbot development (llm + RAG) + RBAC + audit logs → faster compliant replies and +30% NPS.
🎟️ Tap to Donate: AI integration + secure api + offline-first mobile POS → ~50% faster donation flow, shorter queues, higher donor capture.
📊 Analytics assistant: AI chatbot development (llm) + semantic/SQL routing + access controls → ~30% fewer support requests.
⚙️ Ops delivery: AI automation with n8n + api connectors → 30–60% fewer manual steps and faster cycle time.
🤖 Workflow ops: ai agent + llm tools + approvals → 25–40% faster handling time with full traceability.
🎯 How I drive ROI (what you get)
📌 AI automation with n8n: n8n approvals + n8n retries + n8n run logs + an extra n8n safety layer → fewer errors, auditable delivery.
📌 ai agent workflows: each ai agent has explicit tools, permissions, rate limits, and guardrails — one more ai agent check for risky actions.
📌 api hardening: api contracts, api tests, api observability → predictable latency and fewer incidents.
📌 machine learning in production: machine learning evaluation + drift monitoring + another machine learning KPI loop → sustained uplift, not one-off spikes.
📌 llm safety by design: llm grounding + PII masking + llm fallbacks → higher trust and lower compliance risk.
📌 AI integration at scale: AI integration patterns + tenant isolation + staged rollout → safer launches across teams.
📌 AI chatbot development that converts: AI chatbot development tuned on metrics + AI chatbot development UX iterations → higher CSAT/NPS, fewer escalations.
🚀 Core services
✅ AI integration: connect data + tools with secure api layers, monitoring, and governance.
✅ AI chatbot development: llm + RAG, escalation flows, evals, and full traceability.
✅ AI automation: n8n orchestration, policy checks, retries, and auditable logs.
✅ AI agent builds: tool calling + permissions + safe fallbacks, integrated via api.
✅ Machine Learning & MLOps: training, evaluation, drift, retraining — tied to ROI.
🛠 Tech (production-first)
AWS (Lambda/ECS/EKS, DynamoDB, S3, CloudFront) + Terraform/CDK. Backend: Python (FastAPI) and Node.js/TypeScript. Data: Postgres (pgvector), MySQL, MongoDB. Frontend: React/Next.js, React Native.
LLM stack: OpenAI/ChatGPT API and AWS Bedrock, LangChain-style RAG pipelines, tool calling, structured outputs, and ai agent patterns.
Automation: n8n for AI automation workflows (webhooks, retries, approvals) and api-driven integrations.
Hardening: IAM least privilege, KMS encryption, RBAC, PII masking/redaction, audit logs, integration testing, observability, CI/CD.
🎁 Bonus (free)
After our first chat, I’ll send a short “AI Readiness” checklist covering data access, permissions, llm safety, machine learning evaluation, api design, and n8n automation.
✉️ 𝗦𝗲𝗻𝗱 𝗺𝗲 𝘆𝗼𝘂𝗿 𝘂𝘀𝗲-𝗰𝗮𝘀𝗲 (𝗔𝗜 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 / 𝗔𝗜 𝗰𝗵𝗮𝘁𝗯𝗼𝘁 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 / 𝗔𝗜 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻). 𝗜’𝗹𝗹 𝗿𝗲𝗽𝗹𝘆 𝘄𝗶𝘁𝗵 𝗮 𝗳𝗿𝗲𝗲 𝟯𝟬-𝗺𝗶𝗻 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗿𝗲𝘃𝗶𝗲𝘄 + 𝗮 𝟭-𝘄𝗲𝗲𝗸 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗽𝗹𝗮𝗻.
📆 Last Updated: 2026-05-07
Steps for completing your project
After purchasing the project, send requirements so Claudio can start the project.
Delivery time starts when Claudio receives requirements from you.
Claudio works on your project following the steps below.
Revisions may occur after the delivery date.
Intake & Scope Confirmation
Review requirements, define AI system boundaries, role (provider/deployer), users, geography, and success criteria. Confirm scope, assumptions, and exclusions.
AI Act Applicability & Classification
Assess AI Act applicability, risk category (minimal/limited/high), exemptions, and obligations. Identify relevant articles and compliance requirements.