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Data & Applied AI Solutions Architect | Data Steward @ Claro Brasil | Founder @ Datano
Sao Paulo, Brazil
My professional focus is Data & Applied AI Solutions Architecture: designing data pipelines, integrations and AI-powered automation that connect business requirements to reliable implementations.
Since October 1, 2026, I have been part of the CNX Mobile (CNX Móvel) squad at Claro Brasil as a Data Steward / Data Translation Specialist. My focus is data quality, integrity and traceability: connecting technical information with business needs, documenting definitions and rules, and supporting source reconciliation and validation.
My background in Anti-Fraud, Marketing, Data Engineering and Backend Development shapes how I approach this role. I build pipelines and automation, and help teams understand what the data means and how it supports decisions.
Founder of Datano — a consultancy focused on data solution architecture, data engineering, systems integration and applied AI, using Azure, AWS, Python, SQL and Power BI.
My work combines data governance & quality, AI/LLM agents & MCP tooling, data engineering & ML pipelines, cloud/DevOps & VPS orchestration, Microsoft 365 / SharePoint / Graph API integrations, and network automation (MikroTik, RouterOS, proxies).
Creator of pyaccelerate — a Python acceleration engine with multi-GPU, NPU, IoT, and Kubernetes support — and Animus, a self-hosted AI memory synchronization network.
Currently working on GPU-aware optimization for ollama and contributing to the AI inference ecosystem.
| Period | Role | Focus |
|---|---|---|
| Oct 1, 2026 – Present | Data Steward / Data Translation Specialist — CNX Mobile | Data quality, integrity, traceability, business definitions, metadata, source reconciliation and validation criteria |
| Dec 2024 – Sep 2026 | Marketing Specialist | Data engineering, automated workflows, strategic reporting and business indicators |
| Oct 2023 – Dec 2024 | Senior Marketing Analyst | Process automation, reporting and data solutions for business decisions |
| May 2022 – Oct 2023 | Senior Anti-Fraud Analyst | Fraud-prevention indicators, analysis and operational automation |
Across my previous roles at Claro, I reduced data processing time by 97.22% through workflow redesign and automation, built indicators that supported fraud-prevention decisions, and developed BI dashboards and data environments. I bring that engineering experience to my current work connecting data, technology and business teams.
| Domain | What I build | Key tech |
|---|---|---|
| Data Governance & Quality | Business definitions, data dictionaries, metadata and lineage documentation, source reconciliation, validation and acceptance criteria | SQL, PL/SQL, Python, BI, collaborative documentation |
| AI / LLM / Agents | Memory sync networks, agent squads, MCP toolkits, local LLM optimization, transcription & diarization | Python, FastAPI, MCP, Ollama, Whisper, SQLite FTS5 |
| Data Engineering & ML | ETL/ELT pipelines, GPU-accelerated analytics, NPS/verbatim classification, data warehouses, visual workflow orchestration | Python, Java, SQL, PL/SQL, CUDA, scikit-learn, KNIME, Pandas |
| Cloud, DevOps & VPS | Multi-project VPS orchestration, Docker stacks, CI/CD, licensing systems, boot/recovery tools | Docker, Nginx, PostgreSQL, Redis, Linux, PowerShell |
| Microsoft 365 & SharePoint | Graph API integrations, Power Automate MCP, SharePoint CRUD, mail archiving | TypeScript, PowerShell, Microsoft Graph, SharePoint |
| Network & Infrastructure | MikroTik/RouterOS automation, load balancers, proxies, hotspot managers, network optimizers | RouterOS Script, Python, Shell, C |
| Mobile & Embedded | Android toolkit, device rooting, multiboot USB, cross-platform legacy browsers | Python, Kotlin, Swift, Java, JavaScript |
| ERP & Web | Integrated ERPs, portals, landing pages, Markdown-to-HTML pipelines | Python, TypeScript, JavaScript, HTML/CSS |
| Project | Description | Tech |
|---|---|---|
| pyaccelerate | High-performance Python acceleration engine -- CPU, multi-GPU, NPU, IoT, K8s, auto-tuning | Python, CUDA, Cython, Rust |
| ollama-accelerate | Automatic hardware detection and performance optimization for Ollama | Python |
| python-gpu-statistical-analysis | GPU-accelerated statistical analysis with CuPy/CUDA and NumPy fallback | Python, CUDA |
| win-inventory-portable | Portable Windows inventory toolkit for collecting and exporting system information | PowerShell |
| bf6-optimizer | Battlefield 6 performance & network optimization scripts for Windows | PowerShell |
| CSVToolBox | Toolkit for processing CSV, Excel and tabular formats | Python |
| CSVSplitter | Split large CSV files preserving charset, separator and formatting | Python |
| Loader | CLI tool for loading CSV data into Oracle databases | Java |
| Spooler | Efficient Oracle Database spool execution and CSV report generation | Java |
| adb-toolkit | Complete Android backup, recovery & transfer with GPU acceleration | Python |
| IEPortable | Cross-platform legacy IE browser with Wine ActiveX for DVRs/cameras | JavaScript |
| PyExeBuilder | Simple compiler for Python scripts | Python |
Beyond public repos, I maintain 67 private projects spanning:
| Language | Projects |
|---|---|
| Python | 25 |
| TypeScript | 7 |
| PowerShell | 7 |
| Shell | 4 |
| Other | 4 |
| HTML | 4 |
| JavaScript | 3 |
| RouterOS Script | 3 |
| Java | 2 |
| C# | 2 |
| PHP | 1 |
| TSQL | 1 |
| Go | 1 |
| VBA | 1 |
| Jupyter Notebook | 1 |
| Batchfile | 1 |
Areas include data engineering, web apps, network automation, enterprise integrations, and tooling.
| Metric | Value |
|---|---|
| Version | v0.11.2 |
| Modules | 27 |
| Test Files | 20 |
| Stars | 0 |
| GPU Vendors | NVIDIA, AMD, Intel, ARM |
| Platforms | Linux, Windows, macOS, Android/Termux, IoT/SBC |
Animus is a private, self-hosted memory synchronization network for AI assistants. It collects, indexes, curates, and syncs context across machines through a secured hub:
The MCP interface makes the network practical day-to-day: assistants can retrieve relevant notes, prior decisions, project conventions, and previous sessions on demand without exposing infrastructure details publicly.
Tech: Python, FastAPI, Pydantic, SQLite FTS5, HTTPS, HMAC-SHA256, Obsidian, Mermaid, Docker, systemd, Windows Task Scheduler, MCP.
Private platform for coordinating specialist AI squads through reusable workflows, explicit task routing, contextual memory, and Builder/Validator quality gates. Publicly shareable patterns include multi-stage execution, specialist handoffs, and evidence-based validation; agent definitions, infrastructure, and operational data remain private.
Enterprise feedback classification system for NPS verbatims. It runs an auditable cascade that separates customer feedback from operational boilerplate and classifies each record by product, reason, sub-reason, sentiment, root cause, and recommended action.
| Layer | Technique | Role |
|---|---|---|
| 0 | Separator | Extracts customer feedback vs. operator boilerplate |
| 1 | Deterministic rules | Priority regex -- fast and auditable |
| 2 | Custom ML model | TF-IDF (word + char) + ensemble (LogReg + ComplementNB) |
| 3 | Pluggable AI | Low-confidence escalation to LLM (opt-in) |
| -- | Fallback | Manual review when confidence is too low |
Key design decisions:
top1 / (top1 + top2).core/ engine + profiles/ plug-ins; the first profile is verbatim NPS, new domains add new profiles without touching core.CLASSIFICADO (≥ 0.90), PENDENTE (0.40–0.90), ANÁLISE_MANUAL (< 0.40).Tech: Python, scikit-learn, pandas, regex-based rules, pluggable LLM layer.
Repository is private and corporate-bound, so only technical approach and public patterns are shared here.
Proprietary desktop ETL workflow orchestrator built from scratch with Java 23 + Swing. It provides a visual, graphical interface for designing, scheduling, and executing data pipelines without relying on enterprise ETL suites.
Tech: Java 23, Swing, JDBC, ExecutorService, JSON/YAML, Maven, Oracle, SQL Server, PostgreSQL, MySQL.
Repository is private and proprietary; only the technical approach and public architecture patterns are shared here.
| System | Public architecture summary |
|---|---|
| Integrated operations ERP | Modular commercial, field-service, project, inventory, finance, HR, accounting, supplier, fleet, and contract workflows |
| Franchise operations platform | Web portals for operational workflows, feedback, authentication, and structured business data |
| Secure network operations portal | Controlled remote network management with encrypted connectivity, auditability, and role-based access |
| Microsoft 365 integration gateway | Application-authenticated automation for mail, files, and collaboration services with least-privilege access |
| Accessible music technology | Assistive score interpretation combining optical recognition, structured music notation, audio, and accessible interaction |
Client identities, domains, hostnames, repositories, environment topology, credentials, and business-specific rules are intentionally omitted.
| Fork | Upstream | Branch | Status |
|---|---|---|---|
| ADModule | samratashok/ADModule | feature/ad-query-tool-v2 | PR Open |
| Aios | harshitgavita-07/Aios | feat/sdk-streaming-hardware-aware | PR Merged |
| kedro | kedro-org/kedro | 2973-enable-access-to-omegaconfigloader-dictconfig-instead-of-dict-only, base-0.19.15, chore/reflection_system | -- |
| kedro-mlflow | Galileo-Galilei/kedro-mlflow | 645-on_pipeline_error-raises-an-error-when-the-pipeline-fails-and-threadrunner-is-used, dependabot/pip/mlflow-gte-2.7.0-and-lt-4.0.0, dependabot/pip/pytest-cov-gte-2.8.0-and-lt-8.0.0 | PR Open |
| kedro-viz | kedro-org/kedro-viz | 2660-metadata-backup, bug/icon-color, chore/backend_v2_strat | PR Open |
| mcp-server-excel | sbroenne/mcp-server-excel | analytics-data, dependabot/npm_and_yarn/multi-c5ebbb4833, dependabot/npm_and_yarn/vscode-extension/fast-uri-3.1.7 | -- |
| mcp-windows | sbroenne/mcp-windows | dependabot/npm_and_yarn/vscode-extension/oxlint-1.82.0, dependabot/npm_and_yarn/vscode-extension/types/node-26.5.1, dependabot/pip/tests/Sbroenne.WindowsMcp.LLM.Tests/anyio-4.15.1 | -- |
| ollama | ollama/ollama | api, bmizerany/client-registry, bmizerany/embedspeedup | PR Open |
| phpmixbill | ibnux/phpmixbill | GuilhermeP96-patch-1, GuilhermeP96-patch-2 | -- |
| PR | Repository | Status | Date |
|---|---|---|---|
| perf: index outgoing edges for transitive traversal | kedro-org/kedro-viz |  | 2026-10-08 |
| Add opt-in synchronous batching for metric histories | Galileo-Galilei/kedro-mlflow | | 2026-10-08 |
| fix: prevent re.sub backreference corruption in README section updates | GuilhermeP96/GuilhermeP96 |  | 2026-03-29 |
| feat: Ollama SDK integration, streaming UI, hardware-aware model selection | harshitgavita-07/Aios | | 2026-03-27 |
| feat: autotune - automatic hardware-based performance optimization | ollama/ollama | | 2026-03-26 |
| feat: weekly PyPI download stats via GitHub Actions + README badges | GuilhermeP96/pyaccelerate | | 2026-03-24 |
| feat: Add comprehensive AD user query tool v2.0 | samratashok/ADModule | | 2026-01-06 |
| Added Brazilian Portuguese language. | GuilhermeP96/phpmixbill | | 2017-04-03 |
| Brazilian Portuguese language added | GuilhermeP96/phpmixbill | | 2017-04-03 |
26 public repos | 67 private repos | 10 followers | 9 PRs | 5 merged
Last updated: 2026-10-14 00:00 UTC
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Uma ferramenta para dividir arquivos CSV em múltiplos arquivos com base na quantidade de registros especificada, mantendo a integridade dos dados e permitindo configurações de charset, separador e formatação. Ideal para lidar com grandes arquivos CSV que precisam ser fragmentados para melhor manuseio e processamento.
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