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danimuhammad_k

Dani M

@danimuhammad_k

AI Automation Engineer, LLM Workflows, Make com and Applied ML

Indonésie
Anglais, Indonésien
Certaines informations sont présentées en anglais.
À propos de moi
I design and build AI-powered automation systems that replace manual work and create real operational leverage. I don’t build AI demos. I build production-ready workflows businesses actually use. I’ve delivered AI systems for sales automation, research generation, content repurposing, and data intake pipelines, saving clients 10–20+ hours per week. I specialize in end-to-end automation using Make.com, OpenAI, Airtable, Google Workspace, and no-code tools. If you want AI automation that actually runs in real operations, I’m the right partner.... Plus d’infos
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danimuhammad_k
Dani M
hors ligne • 
Temps de réponse moyen de 1 heure

Voir mes services

Mise en œuvre et déploiement de l’IA
I will automate your client marketing reports with ai and n8n
De145 $US / projetPlus de détails

Expérience professionnelle

ANAGATA

AI Engineer

ANAGATA • Freelance

Dec 2025 - May 2026 • 5 mos

• Built a conversational AI agent (RAGFlow + LLM) that parses natural-language requests into structured JSON and autonomously generates formatted advertising reports — no manual exports, no spreadsheets touched by hand. • Integrated 4 ad platforms — Google Ads, Yahoo Search, Yahoo Display, and Meta/Instagram — via their APIs with OAuth 2.0 and service-account authentication, unifying fragmented reporting into one pipeline. • Architected a config-driven, multi-tenant system powering 5 report types (daily, segment, keyword, banner, post-delivery) for two Japanese media clients (broadcast & live-events); new clients onboard via a Google Sheet with zero code changes. • Cut report-generation time ~80% (from ~3 minutes to under 40 seconds) by parallelizing platform API calls with Python concurrency and engineering around the runtime's sandbox memory and execution-timeout limits. • Automated delivery into clients' existing Google Drive Excel templates while preserving their live formula sheets — output lands in the exact file stakeholders already use, share link unchanged. • Authored complete handover documentation (architecture, deployment, credential rotation, troubleshooting), enabling the client team to operate and extend the system independently.

Machine Monitoring System Developer

PT CS2 Pola Sehat • Temps plein

Mar 2025 - Jul 2025 • 4 mos

• Built real-time industrial data pipelines using Node-RED, MQTT, and InfluxDB to ingest, process, and visualize machine energy data, supporting daily operational decisions by Plant Managers and department leads. • Designed role-based access control and 24/7 system visibility, enabling continuous monitoring and reducing operational downtime across multiple departments. • Delivered a production-ready automation system adopted company-wide, demonstrating ability to design, deploy, and maintain scalable monitoring infrastructure. • Extended the automation system with machine learning models (Random Forest) to predict short-interval energy usage, improving forecasting accuracy for operational planning. • Co-authored a research paper accepted at IEEE SOFTT 2025, validating the integration of industrial IoT data, automation pipelines, and predictive analytics in a real-world setting.